Ex IGtbrta SEYMOUR DURST ~t ' ~Fort nt&utu ^4m/?ere/am- oj> Je Mcrnhatans Avery Architectural and Fine Arts Library Gift of Seymour B. Dlrst Old York Library Digitized by the Internet Archive in 2014 https://archive.org/details/incomedistributiOOmill A 1960 Census Monograph INCOME DISTRIBUTION in the United States HERMAN P. MILLER Bureau of the Census Prepared for and in Cooperation with the Social Science Research Council U.S. DEPARTMENT OF COMMERCE John T. Connor, Secretary BUREAU OF THE CENSUS A. Ross Eckler, Director by He no .15 BUREAU OF THE CENSUS A. Ross Eckler, Director Howard C. Grieves, Deputy Director Conrad F. Taeuber, Assistant Director for Demographic Fields Second Printing December 1968 Library of Congress Catalog No. A66-7107 Suggested Citation: U.S. Bureau of the Census, Income Distribution in the United States, by Herman P. Miller (A 1960 Census Monograph) . U.S. Government Printing Office, Washington, D.C., 1966. For sale by the Superintendent of Documents, U.S. Government Printing Office Washington, D.C. 20402 - Price $2.25 FOREWORD The Decennial Census of Population is the most important single source of information about social trends in the United States. Its data on the people and families who make up the population give an insight into the major social changes occurring in our country. Data on age, sex, color, and national origin provide the essential basis for determining the changes occurring in the com- position of our population. The census results make it possible to learn much about the family organization, settlement patterns, education, work relation- ships, income, and other important characteristics of our people. Relationships such as that of age and education to occupation and industry, or of race and education to occupation and income, tell a great deal about how our society functions. The census provides an unequalled set of statistics to meet national and local needs. The advent of electronic computers has increased the avail- ability of census results and the exploration of interrelationships which defied analysis previously. The regular statistical reports resulting from a decennial census can supply only a fraction of the information and insights that are available from this important source. These reports present only those results which are believed to meet the general public needs. Comprehensive analyses of the results, and comparisons with other current data and with past censuses, open the door to many illuminating findings. It has long been recognized that the public would reap additional benefits from its investment in the censuses if some of the analyses that are readily possi- ble could be provided along with the basic data. A series of Census monographs was issued by the Bureau of the Census after the 1920 Census results had been published. A series of Census monographs followed the 1950 Census through the cooperation of the Social Science Research Council. These monographs filled a real need and were so well received that it was felt desirable to initiate plans for a similar series following the 1960 Census. The Council again took the lead in the formulation of these plans in 1958 when it appointed a Committee on Population Census Monographs. This Committee included: Dudley Kirk, Population Council, Chairman Robert W. Burgess, Bureau of the Census John D. Durand, Population Branch, United Nations Ronald Freedman, University of Michigan Daniel O. Price, University of North Carolina John W. Riley, Jr., Equitable Life Assurance Society of the United States George J. Stolnitz, Indiana University. iii iv FOREWORD Paul Webbink, of the Social Science Research Council, and Conrad Taeuber, of the Census Bureau staff, met regularly with the Committee, which reviewed proposals for Census monographs and aided in the selection of authors for specific publications. The Council, gratefully acknowledges a grant of funds from the Russell Sage Foundation for the planning and initiation of the program. The Foundation had provided similar assistance in the 1950 program. In 1960, the Equitable Life Assurance Society of the United States, because of its concern with the expansion in knowledge of the ever-changing structure and functioning of the larger society of the United States, began a program of basic social research. As one of the first steps in this development, it has joined in encouraging and supporting a series of studies of which this monograph is a part. The assistance from the sources named above made it possible to arrange for the time of some of the authors and to provide special tabulations and statistical and research services which were essential to the preparation of the monographs. The program has received the active encouragement of scholars in the Fed- eral Government and a number of universities, and we are glad to acknowledge the debt to these individuals and the institutions they represent. This co- operation was essential for the preparation of the monographs. The monograph authors were asked to provide interpretations of census and related statistics that would illuminate major current problem areas. The au- thors were also asked to take a critical look at the data and to make any recom- mendations which in their opinion would contribute to better development and use of the data. The views expressed in the monograph series are those of the individual authors, each of whom has been given the freedom to interpret available ma- terials in the light of his technical knowledge and competence. These views are not necessarily those of the Bureau of the Census or the Social Science Research Council. A. Ross Eckler, Director Bureau of the Census Pendleton Herring, President Social Science Research Council PREFACE This study has as its focus an analysis of changes in the distribution of income in the United States based largely on information collected in the past three decennial censuses. The first two chapters present data for families and the remaining four chapters deal with persons, with primary emphasis on changes within occupational groups. The major finding of the study is that there was a reduction of inequality in the distribution of income between 1940 and 1950 but little, if any, change in this respect during the following decade. This pat- tern emerges not only in the overall distribution of families by income levels but also in the more detailed analyses that were made for families classified by age, sex, residence, and various other characteristics, and for men employed in 116 different occupations. The consistency of the evidence from a variety of sources strongly suggests that the observed changes in income distribution during this period reflect real changes in underlying economic relationships and are not mere statistical artifacts. Changes in the definitions of income and occupations make it difficult to analyze trends in income distribution for occupation groups on the basis of the published census data. Those who are interested in this type of analysis will find a considerable body of new data on the subject in this monograph. Chapter IV and appendix C present information on changes in the level and distribution of wage and salary income for men in 116 different occupations in 1940, 1950, and 1960. These sections update and revise information origi- nally published in the 1950 Census Monograph, Income of the American Peo- ple. In addition, new information showing the wages and salaries reported in 1940, 1950, and 1960 for skilled, semiskilled, and unskilled workers in manu- facturing industries, by States, has been added in chapter V and appendix D. These sections have been included not only for the light they shed on income distribution, but also in the hope that they will provide a rich new source of data for labor economists. No Census monograph would be complete without an evaluation of the underlying data. Appendix A is intended to meet this need. In general, it shows that there was considerable improvement in the family income statistics between 1950 and 1960 and that the Census income data compare favorably with those available from other sources. This study was originally undertaken as a joint project with the late Selma Goldsmith. Were it not for her encouragement and her willingness to be a coauthor I would never have agreed to write it. Before her untimely death in 1962 she helped prepare the outline and developed plans for several chapters. V vi PREFACE Had she lived this undoubtedly would have been a different and far better study. Her death deprived the field of income distribution of one of its most creative, energetic, and beloved workers. So many people have assisted in the preparation of this monograph that it is hard to know just where to begin giving thanks. Indispensable assistance was provided by five Census Bureau employees without whose help this mono- graph would never have been completed. Evadean Lint and Jacquin Kahn did much of the computer programming; Helen Zitter and Vivian Simmons, much of the clerical work; and Esther Goldstein typed the entire manuscript from the unreadable first drafts to the final copy. Auxiliary help was provided by Mary Henson and Arno Winard who read and checked large sections of the text. Dorothy Brady, Conrad Taeuber, and Norman Lawrence read the entire manuscript and provided many significant and useful comments. Jose- phine Hemphill not only read the jnanuscript, but capably edited it as well. Leah Anderson and Louise Douglas edited the tables and handled all copy and galley proofs through the publications process. Elma Beynon prepared the index. The Office of Business Economics provided unpublished data which were indispensable in the evaluation of the Census income statistics. I not only thank my coworkers in this organization within the Department of Commerce for their invaluable assistance, but also absolve them of guilt in any possible misuse I have made of their statistics. My thanks to the Census Bureau as an organization cannot be adequately expressed in words. I deem it a privilege to have worked for 20 years with men and women who are outstanding scholars, public servants, and most im- portant of all, searchers for truth. Washington, D.C. March 1966 Herman P. Miller CONTENTS Chapter Page I. Recent Trends in Family Income 1 Introduction 1 Problems of interpretation 3 Average income per family, 1929 to 1962 6 Distribution by income levels, 1929 to 1962 12 Trends in income inequality 15 II. Changes in the Composition of Broad Income Groups: 1947 to 1960 , J. 29 Measures of income status 29 Socioeconomic composition of broad income groups, 1960. . 33 Composition of broad income groups in constant dollars: 1947 to 1960 50 Composition of fifths of families ranked by income: 1947 to 1960 m& £ 64 III. Wage and Salary Trends for Major Occupation Groups. . 75 Introduction 75 Wage differentials by skill (BLS data) 76 Wage differentials among major occupation groups, 1939 to 1960 80 Inequality of wages within major occupation groups, 1939 to 1960 88 IV. Wage and Salary Trends for Detailed Occupations: 1939 to 1959 93 Source and limitations of the data 93 Occupations ranked by wage level, 1939 to 1959 95 Occupations ranked by dispersion of wages, 1939 to 1959. . . 98 Changes in average wages among occupations 101 Changes in the dispersion of wages within occupations 1 04 V. Wage and Salary Trends by Skills for Selected Manu- facturing Industries: 1939 to 1959 107 Introduction 107 Primary metals 1 09 Fabricated metals 110 Primary and fabricated metals 112 Machinery manufacturing 113 Transportation equipment manufacturing 114 Food processing 115 Textile and apparel manufacturing 117 Furniture and lumber and wood products 118 • • Vll vni CONTENTS Chapter p age V. Wage and Salary Trends by Skills for Selected Manu- facturing Industries: 1939 to 1959 — Continued Chemicals and allied products 119 Stone, clay, and glass products 1 20 VI. Income and Education 123 Introduction 123 Problems of interpreting the data 124 Annual income and education 138 Lifetime income and education 162 Appendix A. Evaluation of Census Income Data 169 Sources of data for evaluation 169 Comparison of Census and OBE aggregates and distributions . 1 72 Comparison of Census and Sales Management estimates of aggregate income by counties : 1959 190 Comparison of CPS and Census 197 CPS-Census matching study 205 Results of reinterview surveys 209 B. Computation of Constant Dollars, Quintiles, Aggregates, and Gini Ratios 213 Constant dollar computations 213 Computation of distributions by quintiles 215 Computation of aggregates 215 Computation of Gini Index of Concentration 220 C. Occupational Classification and Statistical Tables Used To Measure Wage Trends for Detailed Occupations. . . 223 D. Statistical Tables for Wage and Salary Trends by Skills for Selected Manufacturing Industries, 1939 to 1959. . 257 E. Statistical Tables Showing Lifetime Earnings by Education, Color, and Region, for Selected Occupations 269 Index 297 CHAPTER I RECENT TRENDS IN FAMILY INCOME Introduction Few statistics reveal as much about the operation of an economy as do those on income distribution. Although the levels of living that are possible in any society are prescribed by the size of the national product, a given output can be distributed in many different ways. It can provide palaces for live kings and pyramids for dead ones, but hovels and hunger for the mass of mankind; or it can be widely distributed and provide reasonably uniform levels of living for all. In view of the complex questions that income statistics are used to answer, it would be surprising indeed if the data were easy to collect or to interpret. The difficulties of measurement and interpretation are attested to by Simon Kuznets, who, after plowing this field for a lifetime, has called measures of in- come distribution ". . . preliminary informed guesses . ..." 1 and by Dorothy S. Brady, who has referred to income statistics in general as ". . . deficient in both quantity and quality." 2 These judgments, however, can be made about all statistics. The more one knows about a set of numbers the less likely he is to be entirely satisfied with them. Numbers at best provide a very thorny path to the truth. Thus, the income statistician may find himself in a position not too different from that of Stephen Crane's "Wayfarer." The wayfarer, Perceiving the pathway to truth, Was struck with astonishment. It was thickly grown with weeds. "Ha," he said, "I see that no one has passed here In a long time." Later he saw that each weed Was a singular knife. "Well," he mumbled at last, "Doubtless there are other roads." As the story unfolds, the numerous and serious shortcomings of income statis- tics will be discussed in some detail. It would be a mistake, however, to dwell on the limitations of the data, for although there are still many unanswered ques- tions, much more is now known about income distribution than ever before. The primary purpose of this monograph is to summarize and synthesize the 1 2 INCOME DISTRIBUTION IN THE UNITED STATES information. It has been collected from many sources, but principally from the results of the past three decennial censuses, the annual surveys conducted by the Bureau of the Census since 1945, and data published by the Office of Business Economics of the Department of Commerce. The available data permit us to answer questions that would have been regarded as impossible to answer only a generation ago. We can now quantify with some degree of certainty the annual changes in the distribution of income among families (using several different definitions of income and the family) , changes in the com- position of lower and upper income groups, and the amount and direction of income changes among occupations and industries. We can also shed light on a host of other important economic questions. To begin with, we might examine the widely held opinion that incomes in the United States are gradually becoming more evenly distributed. This view is held by prominent economists and is shared by influential writers and editors. Arthur F. Burns stated in 1951 that the ". . . transformation in the distribution of our national income . . . may already be counted as one of the great social revolutions of history." 3 Paul Samuelson remarked in 1961 that there are studies which suggest that ". . . the American income pyramid is becoming less unequal." 4 Several major stories on this subject have appeared in The New York Times, and the editors of Fortune announced in 1953 that "Though not a head has been raised aloft on a pikestaff, nor a railway station seized, the U.S. has been for some time now in a revolution." 5 What are the facts about trends in the inequality of income distribution in the United States? Few would question that real incomes have risen for most of the population; or that even those who have been left behind enjoy a far higher level of living than most people in other parts of the world. 'Despite the generally high levels of living, we remain concerned about income shares. Has there been any narrowing of this gap between the rich and the poor? If we stick to the figures, the answers are clear, unambiguous, and contrary to widely held beliefs. The statistics show no appreciable change in income shares for nearly 20 years. The heart of the story is told in table 1-1, which was obtained by ranking families and unrelated individuals from lowest to highest according to income and cumulating the amount of income each received. The table shows the percent (or share) of the total income paid out each year that went to each fifth of the families and individuals, and to the top 5 percent. The share received by the top 5 percent is large because their incomes were so much larger than those of others. In 1962. families and individuals in the top 5 percent on the average received $17,200 or more, whereas those in the lowest 20 percent made $2,900 or less (about $55 a week) . During the depression of the thirties there was a distinct drop in the share of the income received by the upper income groups. In 1929, the last year of the prosperous twenties, the top 5 percent received 30 percent of the income. Their share, which dropped regularly during the depression, amounted to about one- fourth of the income at the time we entered World War II. The decline RECENT TRENDS IN FAMILY INCOME 3 Table 1-1.— Percent Distribution of Families and Unrelated Individuals, by Family Personal Income Received by Each Fifth and by the Top 5 Percent, for Selected Years, 1929 to 1962 Inc onie T*flnlf 1962 1961 1960 1944 1941 1935-36 1929 FAMILIES AND UNRELATED INDIVIDUALS 100 10:j 100 100 100 100 100 Lowest fifth 5 5 5 5 4 } « Second fifth 11 11 11 11 10 9 Middle fifth . 16 16 16 16 15 14 14 23 23 23 22 22 21 19 46 46 45 46 49 52 54 20 20 20 21 24 27 30 FAMILIES 100 100 100 100 100 100 (NA) 6 6 6 6 5 (NA) (NA) (NA) (NA) (NA) (NA) 12 12 12 12 10 9 17 17 17 16 16 14 Fourth fifth 23 22 22 22 22 21 Highest fifth 43 43 43 44 48 52 18 18 18 20 24 27 NA Not available. Source: Data for families and individuals from U.S. Bureau of the Census, Historical Statistics of the United States: Colonial Times to 1957, p. 166, and Survey of Current Business, April 1964, p. 8. Data for families for 1960-62 computed from Survey of Current Business, April 1964, p. 6; and for 1935-36, 1941, and 1944 from Selma F. Gold- smith, et al., "Size Distribution of Income Since the Mid-Thirties," Review of Economics and Statistics, February 1954, p. 9. continued during the war years and in 1944 their share dropped to 21 percent. Since that time there has been no significant change in the percent of income received by the top 5 percent, and a similar trend applies to the top 20 percent. At the bottom of the income scale, the data show that in 1935-1936 the lowest 20 percent of the families and individuals received only 4 percent of the income, and that in 1944 their share rose to 5 percent, where it has remained ever since. The stability of the shares received by each of the other quintiles is equally striking. These figures hardly support the view held by many Americans that incomes in our society are becoming more evenly distributed. The changes that took place — ending about a quarter of a century ago — involved in large measure a redistribution of income among families in the top and middle brackets. Although the share received by the lowest income groups increased slightly during the war, since then it has not changed. 6 Problems of interpretation The stability of income shares shown in table 1-1 does not necessarily imply a stability of economic welfare; it is conceivable that a proportional increase in everybody's real income means more to the poor than to the rich. How can we compare the utility of a loaf of bread to the man who is starving, with the utility of another Cadillac to the man who already has three? Exact comparisons cannot be made; yet many people believe that satisfying the most urgent and 4 INCOME DISTRIBUTION IN THE UNITED STATES basic needs of the poor implies some leveling up in the comforts of life, even though income shares have remained constant. To cite further and similar examples, it is likely that the extension of govern- ment services which provide better housing, more adequate medical care, and improved educational facilities has been of more benefit to low-income families than to those with higher incomes. And the increase in paid vacations has surely brought a more equal distribution of leisure time — a good that is almost as precious as money. Furthermore, improved working conditions, including air conditioning, better lighting, mechanization of routine work, and the like, have undoubtedly benefited more manual workers than those in higher paid and more responsible positions. When allowance is made for these and other factors, it may well be that some progress has been made during recent years in diminishing the inequality of levels of living. But we do not know how much allowance to make, and our judg- ments could be wrong. Moreover, most opinions regarding changes in inequality, including those held by professional economists, are based on statis- tical measures of income rather than on philosophic concepts. With all their limitations, the income figures may well serve as a first approximation of changes in welfare. The picture presented in table 1-1 is further complicated by taxes. The figures shown are for income before taxes. Since families in the higher income groups pay a large share of the taxes, their share would be smaller on an after- tax basis. It is smaller, but not by as much as one might suppose. In recent years the top 5 percent received 20 percent of the income before taxes, and about 18 percent of the income after Federal individual income tax payments were deducted. 7 Since the graduated income tax falls more heavily on the upper income groups than do most other major tax measures, it is not surprising that their share of the income is decreased when individual income tax payments are deducted. This tax, however, accounts for only 37 percent of the $124 billion collected in 1962 by Federal, State, and local governments from all sources. 8 Many of the other taxes — the sales tax, for example — are paid dis- proportionately by the lower income groups. Taking into account all tax pay- ments, the equalization of income as a result of taxation would be less than that shown for the Federal individual income tax alone. 9 Still restricting our attention to the interpretation of results shown in table 1-1, numerous other problems come to mind — problems centering largely on the definition of the income-receiving unit, on the accounting period over which income is cumulated, on concepts of income, and on the accuracy of the under- lying data. 10 To begin with definitions, the income-receiving unit shown in table 1-1 is the family or the unrelated individual. The family is defined as a group of two or more persons related by blood, marriage, or adoption, and living together. The income of the family is the combined total received by all family members RECENT TRENDS IN FAMILY INCOME 5 during the calendar year. An unrelated individual is denned as a person (other than an inmate of an institution) who is not living with relatives. These persons are called unattached individuals in statistics compiled by the OBE. For all practical purposes the terms are interchangeable. When these definitions are examined critically a host of problems emerge. Since the end of World War II, a very sharp increase has taken place in the number of older people who maintain their own households rather than share living quarters with children or other relatives. This type of living arrangement has been made possible, for the most part, by the small measure of financial independence provided by the Social Security System, and by the prosperous conditions of the postwar years. For the income statistician, the increasing tendency for older people to con- tinue to maintain their own households creates serious problems. Today there are proportionately far more unrelated individuals than there were in the forties. These groups typically have very low incomes; thus their inclusion in the distri- bution tends to increase its inequality, since it creates relatively large numbers of units with little or no income at the bottom of the distribution. Therefore, even though the definition of the income-receiving unit has remained constant over time, changes in living arrangements of the population may have produced variations in the statistics. The impact of this change is minimized considerably by showing figures for families alone rather than for families and individuals combined. Table 1-1 shows that trends in income distribution for families alone are almost identical with those for families and individuals combined. Other methods of reducing the impact of changes in living arrangements on the measure of income concentration are described near the end of this chapter. Closely related to the definition of the income-receiving unit is the accounting period covered by the figures. Simon Kuznets has referred to the classification of families by their income in a single year as the major limitation of income statistics for purposes of measuring income inequality. 11 Family income is defined as the combined receipts of all members of a family during a calendar year. Since the family includes only those persons living together at the time of the survey, some obvious distortions may arise. For example, a widow who had been supported by her husband during the year preceding the survey would be tabulated as an unrelated individual without income if she happened to be living alone at the time of the survey. Newly married couples who had been living with and supported by their parents during the preceding year would also appear at the bottom of the distribution. Here, of course, there is a dual problem — a change in family status, plus the fact that income is counted for only a single year. For a young family, low income has a significance entirely different from that for a middle-aged family. Turning now to the income concept itself, we find that it presents several important limitations that complicate interpretation. The figures in table 1-1 represent money and nonmoney income; in this respect they are much more 6 INCOME DISTRIBUTION IN THE UNITED STATES complete than the census figures, which relate only to cash receipts. Since it is not feasible in a census to try to collect information on imputed income, the data necessary for adjustment were not available. However, much of what is counted as nonmoney income in table 1-1 is included, not because it provides a more realistic portrayal of the funds available for consumption or saving by the average family, but for the sake of consistency with the national income accounts. 12 Few would argue about adding the value of nonmoney food or housing received by farmers or farm laborers. These items, however, accounted for only a little more than $3 billion of a total of about $25 billion of nonmoney income included in the aggregate that underlies the distribution for 1960 shown in table 1-1. About $11 billion of the total represents imputed interest (largely the value of free banking services received by the owners of checking accounts, and the estimated amount that policy holders would receive if insurance com- panies distributed their property income), and about $6 billion is imputed rental income assumed to have been received by nonfarm homeowners who served as their own landlords. 13 Money income includes the items usually thought of as income: cash wages and salaries; net income (after expenses) from self-employment; and cash income from other sources such as interest^ dividends, net rental income, Social Security and unemployment benefits, private pensions, public assistance, and regular contributions for support from persons not living in the household. Both the family personal income concept (used in table 1-1) and the money income concept exclude imputed income from paid vacations, fringe benefits, and from many other receipts not normally counted as income. These concepts also exclude capital gains and losses, which have become more important during recent years for the upper income groups. While income from this source is of prime importance in many individual cases, it does not have a major impact on the overall income curve because it represents only about 2.5 percent of total family personal income. An attempt made in 1958 to adjust the distribu- tion of family personal income to include capital gains and losses showed that there was little if any change in the share of the aggregate received by each of the four lowest quintiles, and that the share received by the top 5 percent increased only slightly — from 19.9 percent to 20.3 percent. 14 A variety of problems comes to the fore when the accuracy of the income statistics is considered. This subject is treated in detail in appendix A. Average income per family, 1929 to 1962 Growth measured in current dollars. Although this study deals primarily with income distribution, it starts with a look at national trends during recent years in aggregate income, family formation, and average income per family. Since these measures define the levels of living that are possible at a given time, they are in some respects even more important than the distribution by income classes. REGENT TRENDS IN FAMILY INCOME 7 Detailed analyses of trends in aggregate and average income have been made in numerous other studies. 15 The subject is touched on here, rather briefly, to provide a background for the income distribution data that follow. The figures in table 1-2, prepared by the Office of Business Economics, are statistically and conceptually consistent with the national income accounts. They are end-of- year estimates of the numbers of families and unrelated individuals as defined by the Bureau of the Census. Family personal income includes money income as previously defined (see p. 5), as well as nonmoney income. The nonmoney items included are wages in kind, food and fuels produced and consumed on farms, net imputed rental value of owner-occupied homes, and imputed interest. 16 Table 1-2.— Families and Unrelated Individuals and Their Aggregate and Average Family Personal Income, for Selected Years, 1929 to 1962 Year Families and unrelated individuals (millions) Aggregate family- personal income (billions of current dollars) Average (mean) family personal income 1962 57.9 $420.4 $7,260 1961 57.3 397.0 6,930 1960 56.1 382.3 6,820 1959 55.3 365.8 6,620 1958 54.6 343.3 6,280 1957 53.7 334.6 6,240 1956 52.9 317.4 6,010 1955 52.2 294.2 5,640 1954 51.2 274.0 5,360 1953 50.5 272.2 5,390 1952 50.2 257.2 5,120 1951 49.5 242.7 4,900 1950 48.9 217.3 4,440 1949 47.8 199.3 4,170 1948 46.3 201.4 4,350 1947 44.7 184.6 4,130 1946 43.3 170.7 3,940 1944 40.9 147.7 3,610 1941 41.4 91.4 2,210 1935-36 38.4 62.7 1,630 1929 36.1 84.3 2,340 Source: Data for 1929 and 1947-62 from Jeannette M. Fitzwilliams, "Size Distribution of Income in 1963," Survey of Current Business, April 1964, p. 5; and for 1935-36 from U.S. Bureau of the Census, Historical Statistics of the United States: Colonial Times to 1957, pp. 163 and 166. Since 1929, the number of families and unrelated individuals increased by about 22 million, or about 60 percent. Expressed as an annual average for the entire period, this increase amounted to almost 700,000, or 1.4 percent, per year. Household formation during this period took place at a considerably faster rate. Between 1929 and 1962, the number of households increased from 29.6 million to 54.7 million, representing a gain of about 85 percent, or an average growth rate of about 2.6 percent per year. 17 The main reason for the more rapid rate of household formation is the increased tendency, particularly among unrelated individuals, to maintain their own homes or apartments rather than live with relatives or move into existing households as roomers, lodgers, and so forth. In 1940, for example, 3 million out of about 9 million unrelated individuals maintained their own residences; the others lived in other people's 8 INCOME DISTRIBUTION IN THE UNITED STATES homes, generally as roomers or boarders. In 1962, the number of unrelated individuals rose to 11.5 million, but nearly three-fourths maintained their own homes. 18 As previously noted, one important reason for this change in living arrangements is the increase in Social Security payments which has made it economically feasible for many people to retain their homes or apartments in old age. Before the Social Security System was established, and during the early stages of that System, when payments were quite low, many persons were forced to give up their homes when they were too old or too ill to obtain employment, or when their spouses died. For example, many widows who could not afford to pay rent, utilities, and other household expenses after their husbands died, usually found that their only recourse was to move in with their children, or to obtain lodging which, although much cheaper than they were used to, provided a far lower level of living. The housing problem has been considerably alleviated by the Social Security System's guaranteed income in old age, which makes it possible for many older people to keep their own homes or apartments. Furthermore, the generally full employment conditions that prevailed during most of the postwar period furnished job opportunities for young and old. These prosperous years pro- vided not only the current income required to maintain a home, but also a back- log of savings which in many cases permitted mortgages to be paid off, thereby reducing current living costs appreciably. Aggregate family personal income rose at a much more rapid rate than the number of families and individuals during the postwar years, although, as will be shown, much of this rise simply represented an inflation of dollar values. In dollar terms, however, aggregate income, unadjusted for price changes, rose from $84 billion in 1929 to $420 billion in 1962, or at a rate of about 10 percent per year. As a result of the sharp increase in the aggregate during this period, average family personal income tripled, rising from $2,300 in 1929 to $7,300 in 1962. Despite a general increase in the number of families and individuals and in aggregate income throughout the period, there were marked variations for different years. Most of the years between 1929 and 1941 were characterized by economic depression. It is not surprising that during this time there was little growth; indeed, the average annual rate of increase in the number of families and individuals exceeded the increase in aggregate income, so that average family income dropped slightly — from $2,300 in 1929 to $2,200 in 1941. The normal rate of family formation was interrupted during the war years when millions of young men were inducted into the Armed Forces. Between 1941 and 1944, the number of families and individuals dropped slightly, but aggregate income — because of full employment engendered by wartime de- mand — showed a marked increase. During these years aggregate and average family income rose at an annual rate of about 20 percent; this was by far the highest recorded during the 33-year period (1929 to 1962) under consideration. RECENT TRENDS IN FAMILY INCOME 9 With the cessation of hostilities in 1945, millions of men returned home and family formation took place at an accelerated rate. Between 1946 and 1950, the number of families and individuals increased at the rate of about 1 .4 million, or 3 percent per year. The prosperous conditions throughout this period also produced substantial annual increases in income, with the result that average family income rose at the rate of about 3 percent per year. This was also, of course, a period of rapid inflation ; as will be shown later, much of the increase in dollars received did not produce an increase in purchasing power. Since 1950, the number of families and individuals has grown at a much slower rate — about 750,000, or 1.4 percent, per year — about half the rate that prevailed just after World War II. Aggregate income, on the other hand, has continued to grow at the rate of about 8 percent per year, and average family income has grown at an annual rate of about 5 percent. The impact of the recessions of 1953-1954 and 1957-1958 is clearly reflected in table 1-2. During 1953-1954, average family income dropped slightly; in 1957-1958 the average rose by less than 1 percent. The annual increase in income in every other year during the postwar period far exceeded these rela- tively small changes. Growth in average real income. The income averages presented above were in current dollars. Such comparisons do not reflect changes in purchasing power because the general level of prices rose substantially, particularly during the postwar period. In order to eliminate the effect of the rise in prices insofar as the available data permit, the averages are presented in table 1-3 in terms of constant (1962) dollars. Table 1-3.— Average Family Personal Income Before and After Federal Individual Income Tax Liability, for Selected Years, 1929 to 1962 [Includes income of unrelated individuals] Before tax After tax Year Current 1962 Current 1962 dollars dollars dollars dollars 1962 $7,140 $7,140 $6,400 $6,400 1961 6,920 6,980 6,210 6,270 1960 6,810 6,930 6,130 6,230 1959 6,620 6,810 5,940 6,120 1958 6,280 6,560 5,670 5,920 1957 6,240 6,640 5,610 5,970 1956 6,010 6,580 5,400 5,920 1955 5,640 6,280 5,090 5,670 1954 5,360 5,990 4,840 5,420 1953 5,390 6,090 4,810 5,430 1952 5,120 5,850 4,570 5,220 1951 4,900 5,720 4,420 5,150 1950 4,440 5,520 4,070 5,060 1949 4,170 5,250 3,860 4,870 1948 4,350 5,430 4,010 5,010 1947 4,130 5,450 3,720 4,910 1946 3,940 5,760 3,580 5,230 1944 3,610 5,910 3,210 5,260 1941 2,210 4,650 2,110 4,440 1935-36 1,630 3,740 1,610 3,690 1929 2,340 4,250 2,320 4,220 Source: Jeannette M. Fitzwilliams, "Size Distribution of Income in 1962," Survey of Current Business, April 1 963. Figures for 1936-36, 1941, 1944, and 1946 based on unpublished data. 10 INCOME DISTRIBUTION IN THE UNITED STATES The adjustment for price change was made by dividing the aggregate income for each year by a price index for that year, using the implicit price deflator for personal consumption expenditures in the national income accounts (1962—100). This adjustment assumes that the same index can be used for families at all income levels; and that price changes for personal consumption are the same as those for total income, which includes family savings and income tax payments in addition to personal consumption expenditures. Besides the adjustment for price changes, table 1-3 shows average family income excluding Federal individual income tax liability. This adjustment provides a measure of purchasing power in 1962 dollars, showing what might loosely be regarded as real disposable income available per family. This esti- mate actually represents more than disposable income, since only Federal in- dividual income taxes — not total tax payments — are deducted. Although a strong case can be made for the deduction of taxes to obtain a measure of dis- cretionary purchasing power, it can also be argued that tax payments simply represent one form of expenditure for which goods and services are received, and as such should not be singled out for adjustment. In the first place, the consumer is faced with other obligatory payments, such as those made to retire- ment funds, which reduce his current purchasing power. A more important consideration is the fact that a large part of the tax dollar is used for public health activities, highway construction, and to provide other goods and services that are needed because of the concentration of the popula- tion in large cities. Defense expenditures, for example, which consume the largest share of the tax dollar, are a form of protective service purchased by individuals collectively. The fact that we need more of this service now than we needed 25 years ago is ignored when tax payments are deducted from income — presumably to place different periods of time on a comparable base with respect to purchasing power. Table 1-3 shows that before World War II real income and current income tended to move in the same direction, although the amplitude of the movement was much smaller for real income. Both series fell between 1929 and 1936; however, the drop in current dollars was 30 percent compared with only 12 percent in real income. Similarly, both series rose between the depth of the depression and the outbreak of war in Europe, but average income in current dollars rose somewhat more rapidly. Since the immediate postwar period wit- nessed rather serious inflation in the United States, it is not surprising to see a marked divergence between the two series. Between 1946 and 1951, current income rose by about one-fourth, whereas there was little change in real income. Since 1951 there has been a general rise in both series with no marked divergences. Before World War II, the differences in average income before and after Federal income tax liability were quite small, amounting in most years to less than $100 per consumer unit. During the war, the Federal income tax rose on the average to about $400 per consumer unit, and from 1947 to 1956 it RECENT TRENDS IN FAMILY INCOME 11 averaged about $500. Since then it has risen to about $700 per consumer unit. The real "purchasing power" of consumer units rose by about $1,400 between 1946 and 1962, or about $90 per year. The current dollar values were roughly twice that amount. Comparison of Census and Office of Business Economics (OBE) data. Trends in aggregate and average income for the postwar period can be obtained from the annual income surveys conducted by the Bureau of the Census as well as from the Office of Business Economics estimates cited above. Similar data are also available from the 1950 and 1960 Censuses. Since this study uses both annual and decennial census data, it is of interest to compare the figures with each other, and to compare both sets of data with the OBE estimates prepared on an entirely independent basis. These comparisons are shown in table I-4. 19 Table 1-4.— Bureau of the Census and Office of Business Economics Estimates of Total Money Income and Average Money Income, for Families and Unrelated Individuals: 1944 to 1962 Year Families and unrelated individuals (millions) (1) Census Total money income (billions) (2) Average (mean) money income (3) OBE Total money income (billions) (4) Average (mean) money income (5) Ratio of Census to OBE (Col. 2) (Col. 4) (6) 1962 1961 1960 1959: Census 1 CPS 1958 1957 1956 1955 195-4 1953 1952 1951 1950 1949: Census 1 CPS 1948 1947 1946 1945 1944 58.0 57.5 56.3 58.3 55.8 55.0 54.0 53.1 52.6 51.6 50.7 50.5 49.7 49.3 49.4 48.3 47.0 45.4 (NA) 40.1 40.8 $354 339 320 332 303 280 265 257 235 218 216 203 189 171 157 156 157 148 130 114 111 $6,106 5,896 5,684 5,696 5,430 5,091 4,907 4,840 4,468 4,225 4,260 4,020 3,803 3,469 3,178 3,230 3,340 3,260 (NA) 2,843 2,721 $405 381 368 352 328 321 305 284 263 263 245 231 208 190 191 180 166 154 140 $6,966 6,626 6,536 6,308 5,964 5,944 5,744 5,399 5,097 5,187 4,851 4,648 4,219 3,934 4,064 3,965 (NA) 3,766 3,431 .87 .89 .87 .94 .86 .85 .83 .84 .83 .83 .82 .83 .82 .82 .83 .82 .82 .82 .78 .74 .79 NA Not available. 1 Based on decennial census; other census figures in this table are based on the Current Population Surveys. All census aggregates shown here were computed from distributions for families and unrelated individuals. In all cases except the 1950 Census data there is close agreement between the aggregates computed in this way and those based on distributions for persons 14 years old and over. The 1950 Census aggregates based on distributions for persons were 91 percent of the comparable OBE total in contrast to the 83 percent shown here. The difference is due to methods used to collect and process income statistics in the 1950 Census. See appendix A for a more complete discussion of this point. Source: Data for 1953-60 from unpublished data of the Bureau of the Census and Office of Business Economics; and for 1944-52 from Selma F. Goldsmith, "The Relation of Census Income Distribution Statistics to Other Income Data," Studies in Income and Wealth, Vol. 23, Princeton University Press, 1958, p. 71. The most significant finding in table 1-4 is that despite marked differences in level between the Census and OBE series, there is a striking similarity in trend. In every year for which comparisons can be made, annual changes in average 12 INCOME DISTRIBUTION IN THE UNITED STATES income in both series have been in the same direction. Moreover, the magni- tudes as well as the direction of change have been quite similar. The greatest difference in trend occurred between 1944 and 1945, when the OBE average rose by about $300, or 10 percent, whereas the Census Bureau survey average rose by only about $100, or 4 percent. The survey estimates for these years may have been erratic because of unsettled wartime conditions, and also because the technique of collecting income information in household surveys was still in its infancy. Since 1947, both series have had essentially the same year-to-year movements. Differences of $100 or more occurred in only two of the postwar years; in most periods the annual changes in income level were insignificant when measured in either absolute or relative terms. 20 Distribution by income levels, 1929 to 1962 Since the depression of the thirties the increase in the aggregate and average family income has been widespread throughout the population, resulting in a general movement of families up the income scale. There have, of course, been many exceptions. The aged, uneducated, and unskilled have not moved ahead as fast as the others; but even for these groups the sharp edge of poverty has been blunted. 21 The more typical picture, especially during the postwar years, has been one of gradually rising family incomes due not only to the full-time employment of chief breadwinners, but also to the rising tendency for families to send secondary workers into the labor market. These factors, combined with the increasing productivity of American industry, have caused a persistent drop in the number and proportion of families at the lower income levels, and a corresponding increase in the middle and upper levels. Although part of the rise is due to an inflation of dollar values, even after adjustments are made for price changes, there has been a very marked increase in real family income. The extent of the increase can be seen most dramatically in a single statistic. In 1929, at the height of the prosperous twenties, 31 percent of the families and individuals had incomes under $2,000. Using the same dollar standard, adjusted for price changes, we find that 32 years later only 12 percent of the families and individuals had incomes this low. This decrease clearly means that there has been a very sharp drop in the proportion of persons living at near- subsistence levels, and that for millions of people absolute want has been eliminated. Numerous studies have been made of trends in the overall distribution of families by income levels, and the factors associated with these trends are rea- sonably well known. The main reason for summarizing the data here is to provide a background for the more detailed analysis that will follow. More- over, the summary data permit a comparison of figures from two of the major sources of information on the subject — the Census and OBE estimates. Tables 1-5 and 1-6 show the OBE data in current and constant dollars, respectively. Table 1-7 shows corresponding, although not exactly comparable, estimates based on Census data. 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O «r> «r> ©9- &9 • o -P - o o o o C CM -P -P -P -P co «e- o o o o o f-i u o o o o co co O O O m r OS Os u •s CO >t > rH O «r> p § o o o o o o O m _ rH rH 69- «r> «r> -p a) bO CO bo 5f OS OS as os OS OS O e*i m • o •P - o o C CM -P -P CO 69- o o o U fn O O CO CO o o 0-, -a ~ - SSi^ Os OS OS OS ri as os -sco >t OS si- > - - rH O t> OS 69- -a o 2 O O -P a) P -P O O O O O Q o o o o O m - - ~ - o m SO O rH rH «(9-«r>«r><«- 14 INCOME DISTRIBUTION IN THE UNITED STATES One dramatic change shown by these figures is a precipitous drop in the proportion of families and individuals with incomes under $40 a week (less than $2,000 a year) . During the depression of the 1930's about 3 out of every 4 families and individuals received incomes less than this; by 1941, the proportion had dropped to 3 out of 5, and by 1950, to 1 out of 4. In 1962 only 1 of each 8 were receiving incomes this low. Another view of this same change may be had in terms of share of all incomes received by families and individuals with incomes below $2,000 per year. Dur- ing the thirties, this group received nearly half of all incomes, and its share fell to about 1 in 4 by the start of World War II, and to about 1 in 50 in 1962. It is true that the change in the value of the dollar during the last 30 years makes it hard to extricate the real change from the apparent change, but the figures suggest strongly, as does other information to be dealt with later, that there has been an impressive decline in the proportion of families and individuals at the lowest income levels. During the same period, equally impressive changes were taking place at the other end of the income scale among the top income groups. During the thirties, and even as recently as 1941, only 1 percent of the families in these groups had incomes over $10,000. By 1950, the proportion had increased fivefold, and in 1962, nearly one-fifth of the families and individuals were in this income class. In terms of aggregate income, this top class received only one- eighth of the total in the prewar period, compared with 45 percent in 1962. Table 1-6.— Percent Distribution of Families and Unrelated Individuals, by Family Personal Income Level in 1962 Dollars, for Selected Years, 1929 to 1962 Family personal income level (1962 dollars) 1962 1961 1960 1959 1947 1941 1929 Families and unrelated individuals millions. . 58.6 57.3 56.1 55.3 44.1 41.4 36.1 100 100 100 100 100 100 100 12 12 13 13 16 27 31 19 19 19 20 28 29 39 21 22 22 22 26 22 15 18 18 18 18 14 12 7 $8,000 to $9,999 $10,000 to $U,999 11 11 11 11 7 4 3 12 11 11 10 6 } « 5 n 7 6 6 3 Source: Jeannette M. Fitzwilliams, "Size Distribution of Income in 1962," Survey of Current Business, April 1963, p. 15. The figures in table 1-6 on income distribution, adjusted for price changes, show that although some of the preceding analysis must be modified, the basic conclusions are substantially unchanged. Starting at the bottom, we find that even during the boom of the twenties about one-third of the families and indi- viduals had incomes under $2,000. This proportion dropped to about one- fourth (27 percent) at the outbreak of World War II, but was only 12 percent in 1962. Thus, in a third of a century, the proportion of families and individuals RECENT TRENDS IN FAMILY INCOME 15 with real incomes under $2,000 has been reduced by about two-thirds. During the same period, there was also a significant bulge in the proportions in the middle and upper income levels. In 1962, for example, the $6,000 to $10,000 income group contained nearly three-tenths of the total, compared with only one-tenth in the prewar period. The purchasing power of this middle income group rose proportionately. The top income class — $10,000 and over — has also had a fourfold rise since the depression. The Census figures corresponding to the OBE figures previously discussed are presented in table 1-7; but it is the comparison of both series at selected points in the distribution, shown in table 1-8, that clearly portrays the similarity of the trends in these data. At the lowest quintile both series show a relatively large increase between 1950 and 1951, moderate gains during the next 2 years, and a drop during the 1954 recession. The years 1955 and 1956 show a rela- tively strong recovery in both serjes — stronger in Census than in OBE — followed by 4 years of slow-to-moderate growth. Similar patterns of change are also found at the middle and top quintiles. Trends in income inequality Starting with Pareto in the latter part of the 19th century, interest in income distribution centered largely on the construction of Lorenz curves and the measurement of inequality rather than on other aspects of the subject. The early emphasis on the measurement of inequality may have been due partly to the fact that the statistical evidence was based on tax return figures for Western Europe, which could provide reasonable measures of income concentration, even though the figures did not represent the entire population. However, since tax returns lacked the demographic and sociological data now commonplace in household surveys, it was not possible to analyze many of the factors that affect income distribution. A further reason for the early em- phasis on the measurement of inequality was the search for broad generalizations about the nature of the income curve. One such formulation, the "Pareto Law," was discussed in much of the literature of the early 1900's. During recent years emphasis has shifted from the measurement of inequality toward an analysis of various parts of the income curve and the causes that underlie changes in income distribution. During the past decade, for example, two congressional hearings were held on the low-income problem in the United States, and a good deal of research has gone into the measurement and analysis of the causes of poverty. Much other research has centered on measuring the financial returns from investments in education — a type of analysis first touched on in the twenties but not revived seriously until the sixties. Figures showing trends in the inequality of income distribution between the outbreak of World War I and the years immediately after the end of World War II are found in the work of Simon Kuznets, using data from Federal individual income tax returns. The major findings with respect to trends in income in- equality based on Kuznets' work are summarized in table 1-9. The method 16 INCOME DISTRIBUTION IN THE UNITED STATES s tC 3 ON -J- CM IT\ VO -J- -n* to -tf rH vfr 1T\ \0 CM o co cm on in to" -tf Cl o 1> C- rH On CO CM N >f ch «lrlrlO> eg CM -J- CM n ^ o» n 1-1 On CO ON ON CO N n h O vO CO tO NO t- O (M> CM OJ Nf .-H NO CO CM rH "A \0 O 1*1 On ON On CM O O CO CM CM CO CM rH □ m h M 1 r\\f n Q tf\ vO M" C\J H w r> cu h K 3 m (> n h co i CM ^ io ri vDto On CM r> vO CM rH h n N h CM CO r-H -J- rH NO C- 1A \0 <0 i-l CM CM CM rH 10 ?3 cm 2 1-1 2* ON o 8* O On CO -tf NO CM co co no >r °* 5m Fm S "* 1-1 3 CO O CO O CM IT\ vO CM -nJ CO ^ rH CM c CO On >t <*> On CM IA rH CM CM CM •J t- v£) n| On O at 8 ON in n >J ^N co m co ON >t nO nO IA On t— I CO nO ' CM CM CM CO m ON : w n \f h ■>> o ■Nt n O h m * ^ 3 8 o co C~- On rH >}• r- n to o m to <*\ CM rH CM CM On £ rH CO CO CO IA vO CO CO O f- O \0 >A CO CO O SrH 3 O 3 T3 T3 C -H o > •si 3 . ON ON ON On ON ON ON ON » ' ON ON On -\t O n m o> » C €r> T3 o o c «. O O O -r> as CM ■!->+> Cr> Q Q c 3 «r> O f NO rH rH {r> ^> r I on . ON ON ON ON &4 ' On On CJn •> 91 • ON 0> ON Vf > ' o «r> «r>«r> TJ o c > O O +> as CM +5 -P -> «r> i§ ; 3 1 REGENT TRENDS IN FAMILY INCOME at rH 100.0 tO vO tO m CO rH o ..... rH • iB O W m m O CM CO CM rH •> o CO rH 19.1 31.6 26.1 6.1 $3,957 to Nf ON rH 100.0 27.9 31.3 22.8 $3,454 100.0 tO NO CM CM CM tO NO On CM NO no m to rH CO CM rH - CO Nf CJN. rH Census 100.0 «MO>trlvt H O CM to* rH co* nJ- CM; o n CM fM ri - C CO rH •» 23.9 29.7 25.1 5.3 $3,772 CPS 100.0 CM rH to CO O nJ O r> rl H mvf 1*1 O CM CO CM rH - O CO rH CO rH rH NO ON ^ rH CM m NO Nf to CM CO CM rH CO 1950 100.0 27.6 28.8 23.6 15.3 4.8 $3,613 100.0 19.8 29.5 26.7 18.2 5.7 $4,036 1951 100.0 to rH 1> On NO CM O NO Nf ON Nf vO -si- t> O CM CM CM rH - O CO rH Cr> 17.9 29.3 27.8 19.7 5.4 $4,164 1952 100.0 25.2 28.3 23.8 T7 Q 4.8 $3,785 100.0 17.2 28.4 27.2 5.8 $4,277 1953 100.0 CO O Nf m rH O O t> Nf Nf Nf O no O O CM CM CM CM - O to vO to Nf CO i> CM NO CO t> Nf t> NO rH CM N CM - Nf m o> rH 100.0 rH CM NO ON CM to O nO Nf CO On NO On O CM CM CM rH - O CO rH €r> rH rH t> NO m O CO to Nf no co m rH CM CM CM - 1955 100.0 Q\ O UN IH rl CJN o CO CO CO CO CM t>- CM O CM CM CM CM - O cS o m vO nO CO IN rH nO CM nO nO to to rH CM CM CM •> & nO m ON rH 100.0 CO rH ON Ni Nf m O CO cm rH co Ni- to m o CM CM CM CM - O CM NO CO O O CJN CM Nf O NO CJN O rH rH CM CM CM rH in «r> 1957 100.0 m O CO CM rH On : rH (NH-jNtCO fl O CM CM CM CM - O NT rH Cf> CM CO rH [> NO to Nf Nf O t> tO ON rH rH CM CM CM m €r> 1958 100.0 m cm on t> t> m o o CM rH CO co to m o CM CM CM CM - O Nf rH «r> rH t>- O rH CO CO Nf Nf O NO CO O rH rH CM CM CM rH in £r> 1959 Census 100.0 CO t> ON rH rH rH ~ ON CO to O m CM O o CM rH CM CM rH - O $ rH CO CO CO rH O NO co t> co o m vo rH rH CM CO rH in €r> CPS 0*001 MJMOvON Ol O rH on cm in o t> o CM rH CM CM rH - O Ni" rH «r> Nf Nf ON O CO r- rH CO ON Nf O CM Nf rH rH CM CO rH - m €r> 1960 100.0 O O O to Nf o o to rH O CM to to to O CM CM CM CM - O CM On Nf CO O CO CO CO O* CO 1$ rH rH CM CO rH m €r> 1961 100.0 co no on no m o o to rH On O m CM tO O CM rH CM CM rH - O Nf rH «r> cm co no m o r- ON co co cm o m m r— 1 rH CM CO rH - m €r> 1962 100.0 m to t> m m t> o NO O to O no CO o o CM rH CM CM rH - O m rH Cr> CM Nf Nf rH O t>- Nf CM CO CM rH NO £> rH rH CM CO rH - m Cr> • ON ON ON U • CJN CJN CJN CD • ON CJN ON > -P . » o a> n O co m on S cu O Cr> €r> Cr> o o O C o u •n O O O CO c CD CM p p p •H PL, Cr> O o o o o c u o o o o co 01 o o o - •H -a -> ~ -o ■a a CM Nf NO rH !=> Cr> Cf> Cr> cu 2 • CJN ON CJN • CJN ON On CD • ON ON ON > . ~. ^ ^ o 0) C O CO m On e 0> O Cr> Cr> 13 o o o c o u •n O O O CO c 01 CM p P -P •rl p* €r> Q O O O O c U O O O O co 0) O O O « •H ■a ~ - ~o ■a C CM Nf NO rH ED €r> CrV Cr> Me 18 INCOME DISTRIBUTION IN THE UNITED STATES Q Z < CO o CO z o t-H H C/5 co U s o Z cm o ^ (J C\ w ^ ^ o Z ' CQ O uu 3.3 x - n s o z aa to" - < Q Q Z < to CO z H U H X H u- Q O Z 3o UJ - CQ £ - a: O Z CO ,D u D < > pq j H z 5 Q H U UJ I. 00 I H 0) bo CO s a oj o 0) u >> (H a) E? CO -H a) -a QJ cu f-, o o cu C ^ W ft CU CU PL, O t> O O -o m >t -vt to cr> nI- o -j- o m OOOOO OOOOO OO-— >}■ On nO nO C"! vO^HvOO r-H O X NT CO Z Z Z CO C~- O nO nO in a) T3 CU CU U O o cu u c CU CU PL, O to £>- <"i <**i \C nto ri HHHn^^ • ^ >tnin^«i oj no m o C- ^ H vO h ^ — - lf\ vOO"C h o no m on on H O H vO to 00 Nf OJ Nt" sr o <*> oj t> ^ oj in to vD in x ONt cnnc-CMr""! >tOOt>OC\l moc*«OH n«>otinH>o 0 lf\H H f- >t On nO C~- m On to 00 C- O nO \D nO n£> «m^^>»>i cu cT 0) *H C 0> OJ nO -J- On On >t nO OJr-^. — v^-^ x «: «< «: m rH (*n, >f O OJ NO m rH Nf — - Z Z Z O O Nf in «r> • o o lo1 M OOOOO rH m OJ r> no rH OJ OJ I rH o O »■> ^-x^^ on o x 00C-OJOO C> l> >0 m CM OJ rH On C- ooo .-^«-~-n h n w << < <; no o z z z -nT -vj -\t Nt >t n f*^ f\ ^ c CU OJ PL, O vO «1 H (M n m O ^ «\ w n to i> o rH OJ vO \D OJ . m m o m — - o cu H ft stOtOHH On n£> vO 00 -n* >0 >OH\t - OJ OJ in On to O nO rH O O to ^ MD H X OJ rtH ,— i OJ OJ i OJ CI rH l rH OJ o o to >jN^cir-\r^ n n r\ cm n ojojojojojoj to oj rH m o rH -vt OJ r-l «>JHO<0 COC^-xl-OjnOl ^ c cu cu PL, U O r-i 00 m o n <^ o O <^ t^- rH OJ vO 00 OJ >t oo m — ^ — - ^ • • X < < r-i ia 2 z Z O O O^'—^'^ 00 op X < ■< < OJ^Z z z OOOOO Q O O o> >f o> <\ ri n SO O o 0> rH < r rH to ->t vO m I> OJ H *o OJ 0> NO O 00 ^> • • ■ • • x o >f m to <-i — - OJ I cu C CO *H a) t3 cu cu fc, o o cu c u M ft PI CTn r"i OJ rH 00 <-l OJ S3 a- t> rH nrionooN J>>f>T o on h >o * l"l (NJHOONtO r-NOin-Nl-tn OJrHOONOOr- vOvOvOmm mm «> nm minin ^ CJNONONCJNCJN C7NCJNC3NONON ONCTNCJNCJNCT'O^ a 03 3 CS '3 > es cu CO l» S 8 K 5 i Si 4 o| s — .. — Or; O 1 1 CD •= I $ ll "I ^ cu o Is Z -5 CO a RECENT TRENDS IN FAMILY INCOME 19 used to prepare these data will be reported here only in brief, since it has been described elsewhere in detail. 22 Briefly — and at the risk of oversimplification — Kuznets' method involves the calculation, for each net income class shown annually in Statistics of Income, of the amount of net income per tax return and the population represented by the returns. Net income in this case is defined as the sum of wages and salaries, net income from self-employment, interest, dividends, rents, and royalties; excluded are capital gains and deductions from income except for business losses. The population represented by the returns includes those for whom income is reported as well as those listed as dependents. Per capita income is computed for each income class and the classes are ranked in descending order of per capita income. The cumulative totals of population and income recorded on the returns are then converted to percentages of the total population and of the aggregate income received, and the share of income received by the top 1 percent and the top 5 percent of the population is estimated by interpolation Table 1-9 shows that there was no change in the share of income received by the top 1 percent or the top 5 percent of the population between 1913 and 1930. In 1914, at the outbreak of war in Europe, the top 1 percent received between 13 and 14 percent of the income. This range prevailed in all but 2 years during the twenties and showed some tendency to rise during the latter part of the period. There was a slight drop in income inequality during the thirties, a marked drop during World War II, and relative stability throughout the early postwar years. Table 1-9.— Percentage Share of Total Income Received by the 1 Percent and Top 5 Percent of the Population: 1913 to 1948 Top [Total income is defined here as the sum of employee compensation, entrepreneurial income, rent, interest, and dividends] Year Top 1 percent Top 5 percent Year Top 1 percent 1948, 1947, 1946, 1945, 1944, 1943 1942 1941 1940, 1939 1938 1937, 1936, 1935 1934 1933 1932 1931 1930 8.38 8.49 8.98 8.81 8.58 9.38 10.06 11.39 11.89 11.80 11.45 12.84 13.14 12.05 12.48 12.48 13.25 13.31 14.12 17.63 17.41 18.20 17.39 16.62 17.75 18.94 21.89 22.71 23.45 22.80 23.80 24.35 23.73 24.88 25.34 26.71 26.27 26.19 1929 1 19 29 2 1928. 1927. 1926. 1925. 1924. 1923. 1922. 1921. 1920. 1919 1 1919 2 1918. 1917. 1916. 1915. 1914. 1913. 14.50 26.09 14.65 26.36 14.94 26.78 14.39 25.96 13.93 25.25 13.73 25.20 12.91 24.29 12.28 22.89 13.38 24.79 13.50 25.47 12.34 22.07 12.96 23.13 12.84 22.91 12.69 22.69 14.16 24.60 15.58 (NA) 14.32 (NA) 13.07 (NA) 14.98 (NA) NA Not available. 1 Comparable with earlier years. 2 Comparable with later years. Source: U.S. Bureau of the Census, Historical Statistics of the United States: Colonial Times to 1957, p. 167. 20 INCOME DISTRIBUTION IN THE UNITED STATES Trends in inequality of income distribution for recent years, based on data published by OBE and the Bureau of the Census, are shown in table I-10. 23 These figures show changes in income shares not only for the top income groups, as in the Kuznets series, but throughout the whole range of the distribution. Focusing first on the top income group during 1929-1947, we can see that the OBE series shows much the same picture as the previously described Kuznets series. According to OBE the share of the aggregate income received by the top 5 percent of families and individuals dropped progressively from 30 percent in 1929 to 21 percent in 1947; while for the same period the Kuznets series shows a drop from 26 percent to 1 7 percent in the share received by the top 5 percent of the population. Neither the Census nor the OBE data show any change during the postwar period in income shares at any point in the income distribution. According to OBE the poorest 20 percent of the families may have received a very slight gain in the share of income during the war years; but since 1944 the share has been constant at about 5 percent. The Census data confirm this finding. Similarly, the wealthiest 5 percent of the families and individuals received a constant share (about 20 percent) of the aggregate in each year during the post- war period. This finding is also confirmed by the Census data (about 18 percent) . Even though all available evidence points to a stability in the overall income curve during the fifties, this stability may be more apparent than real. Accord- ing to one theory, there is a good possibility that the equalization of incomes during World War II and the years immediately preceding the outbreak of the war continued into the postwar period but was obscured by other statistical factors. Simon Kuznets has summarized this theory as follows: . . . even in the 1950's there may have been forces making for narrower income inequality, but their effects may have been offset by the greater fractionalization of consuming units at both ends of the age distribution of heads. 21 In other words, the splitting up of family groups, made possible by the growing importance of Social Security payments, would tend to increase the inequality of income by creating a relatively large number of low-income families. Else- where, Kuznets has hypothesized that the increasing urbanization of the popu- lation has tended to increase inequality of income because, ". . . all other conditions being equal, the increasing weight of urban population means an increasing share for the more unequal of the two component distributions." 25 These hypotheses were tested by constructing Lorenz curves for various demo- graphic characteristics for each year in the postwar period, and ascertaining which groups, if any, have had appreciable changes in income distribution. A summary of selected characteristics based on these data is shown in table 1-1 1 ; full details have been published elsewhere. 26 These figures show rather clearly that stability in the overall income curve reflects in large measure stability in the component distributions. For example, during 1947-1960, there was no change at all in the distribution of income groups among urban families; the RECENT TRENDS IN FAMILY INCOME 21 o u •p to J3 v P A O m m st \D m in en cm cm C- st St st st st O On H o rH to to t> st vO VO m to rH sf sf st st st m in r> o o <£> m sf en en m m sf en rH - — - * — - o to cm o n en en st en cn \0 \D vD vD \Q cn en st st vO vO vD \D vO O O PI HtO rH rH rH rH Hi OS O O O O O* O* O* i-I rind H St Cn ON ■ rH rH O* O rH O m CM rH rH O O^" ON* v0 vD O st* st-" st-* si-' st* f> to to to st sf* st* st" st" O O «0 • st* m" st* OOOiriHH m in st st st o o o o o o o o o o o o o o o o o o o o" o o" o* o* o" o o o o o o H rH rH H rH rH CICMOnvOO tOinOOvO 0>vD(VO>H CM CM m en st st" m' st st* en* st st st st st HOOJ moi vOvDHOtO m sf en vo o in \£> t> vo o ci H H o< cn o st vD to O-" t>* tN* t>-° D-* omstmin cm m cm rH rH m o en sf O o" o" o" o" o* to \0 vO CM to O O* O* O O t> CM st m t> cn en st st m n n n n m sf Cn rH CM d 1^1 P\ m in cm ci vo en en en en en O O O O O o o o o o o o o o o ooooo ooooo ooooo ooooo r-< r4 r-t r4 r-l i-{ r-{ r-i r-t r-t OOOOO OOOOO rH rH rH rH rH to 2 — --^ — - St ^^-W^^- CM rH ' S — . — - — • — - — . cn*II?gi O — »wv»< — - t>- vo m sf en vomm in m m in m CJ\ (Jn (J* CT» O cmji c> rHHrHrHH riHHHH CM rH O O to m m in st st ON ON On On O^ 1 rH rH rH rH rH C- vO sf H m O sf st st st en CM ON 0^ CJi o^ rlHHHHH CP «1 5? S <$ 8 o "S °° $ & •~ 03 *i s g '•S en .2 S c: CQ a, -a •*i — C o * 1 2 1 p • S t> ^ c* W C35 >h a OS *« 00* O 1 1 I J 1 1 3 e o i ■si O ;g S 8 3 "« « § a 3 fl a X! C3 ■§ o -S s i s i o o 03 22 INCOME DISTRIBUTION IN THE UNITED STATES top 5 percent and the top 20 percent received about the same share of the aggregate income in every year during the decade. Thus there is no evidence of an equalization in the distribution of urban incomes offset by an increase in the proportion of urban families; nor is there any evidence that urban incomes are more unequally distributed than rural incomes. In fact, for the money income figures shown in table 1-11, the reverse is evidently true. But even when total income is used, farm incomes appear to be more unequally distributed than urban incomes. 27 The idea that farm incomes are more equally distributed than nonfarm incomes (which appears elsewhere in the literature on income distribution) is without solid foundation. 28 Of course it could still be argued that the overall stability of income distribu- tion for the urban population masks important changes which have taken place for various subgroups within that population. But this hypothesis — like the idea that farm incomes are more equally distributed than nonfarm incomes — does not appear to be supported by the facts. As shown in table I— 11, income distribution within the urban population has not shifted even when that popula- tion is further classified by labor force status of wife, age of head, or size of family. During the postwar years, for example, among urban families where the wife was in the paid labor force, there was no change in the share of income received by the wealthiest fifth and the top 5 percent. The same is true for urban families with the wife not in the paid labor force. However, it should be noted that incomes are much more equally distributed among families where the wife is working than where she is not working; the sizable increase in the proportion of families with working wives has therefore- tended to decrease income inequality during the past decade. The figures in table 1-1 1 also suggest that the stability of income distribution during these years can be explained without reference to the increased tendency for older people to live alone. The figures for families headed by persons aged 35 to 44 and 45 to 54 show the same stability in income shares that appears in the total. It is conceivable, but not very likely, that the income distribution among younger families has been affected by the splitting off of elderly persons. This hypothesis cannot be tested; there is no way to add elderly persons back to family groups they would have joined had they lacked sufficient income to maintain their own households. In general, however, the incomes of elderly people tend to be quite low; it is doubtful that the addition of their income to the family total would have caused a significant change. All available evidence presented in this chapter points to stability in the distribution of family income during the fifties, following a period of rather rapid change during World War II. The data presented in table 1-1 1 show that the Lorenz curves for most of the major component parts of the overall income curve were quite stable during the fifties. These curves, however, constitute only one element in determining the shape of the overall curve. Also important are the changes in the relative weights assigned to the various components and in their mean incomes. By RECENT TRENDS IN FAMILY INCOME 23 W -rl U i-H CD *ri Pi E I a St -p to cu H rH i-H O i NT St St to \d c- r> to t> d t*\ n c*^ ^CT> ON O ; co st CM H O H H st Sf Sf Sf St O to TO TO TO C\ t> vO TO TO O C- ■ co cm cm cm cm cm cm cm m co cm co . rlrirlrirl H H H rl H H H OS - T3 a = Q. o a » o hi & a, O O — JS - a a. 3 CO JS a JS it a) Sf U ■i a a u ^-«o o ; < st sr >0 >f irnfl \0 r)HI"l(M(M St St St st St ntMoni'i st sf co cm St st St st St St St St St vO CO t> £> (M O H (M st st st st O (M (M H n st st st st st 3 3' r> v£> \£J ^O 'JD n n n n \D v0 vD TO \D n t^ o n mOHOO rH CM O rH H St St St St St CO CM CM rH St St st St vO \o m in \o t> f> st vO vO TO t> C- rH i-H O O O st st st st st O O O rH O st st st st st CM i-H rH rH rH CM CM rH CM CM CO CO CO CO stsfstsfsf ststststst stststst D- vO vO v£> vO rH rH rH rH rH r> vO \D TO [> O- t> t> CO O O TO 1> vO lA st CO CM rH O O CO t> iO m ifiin m in m m m m m st st st O^OO^OCT* O CT* CT* CT* O 0^(7*0^ O CO O- vO m st CO CM rH OOTOO otfi^min m in ia in in >n st st st 01 Oi (Ji CMJ 1 O CT» O O O ON C> CX» CT* i-H rH rH rH rH rHrHrHrHrH HHHH «P 05 "3 > CS — o » m CU T3 O O •H & U oo O rH Cm T3 O O C iH .O w M cd co O Q.rH Cm M rM cu *ri a E bo CO ■ CU > M < < O CO «|HHO ft «M ft ft cm N z z n cm znnn -J- iH Nf vO t> f\ ro n n n n n el co >t o o CO CM H -J- ft ft ft lf»H CU f OJ ITl CM t> rH rHOOOO CO C*> Q> ^ a> nnnnn oj cm cm cm cm < rH O CM z n n n nvo o> cm \o o o c~ ia cr> o vo . -i ft ft ft ^ cm ft cm inn n n n n n ri cn c\ n ft ft ia CM ia ia *o rH o o> «"» cm ri\0 — — * o o c> c- r> co <; <; C\J CM CM CM CM CM CM Z 5! O £ rH t> rH nOHHPl c\ c\ n ft O - — *-~v£>CO CM rH vO rH C < < CM rH >f -J ft Z Z ft ft ftftftft t> ia CO O t> tf\ IC\ vO \D n c^i ft n n CI> H O f O O ^ rH IT\ tS>Oftr>so to to r> \£ ftftftftft ftftftft 1ft ^ H O 0> CM rH .-I rH rH ftftftftft O oi in co m rH CM rH rH fr> ftftftftft CO CO t> CO O ftftftftft t> ^ H CM lf\ iS r .^iflioio to S < < ftftftftft ftftsssc IA rH ft O to co co eo CM CM CM CM C£ ft CM CJ tC CO rH t0 CM CM ft CM 8 cb < < ft ft 2 2 33 >r >f >t >j >f O CO ft r> to t> o> ->t >* >f O « Ji H H vO t> cm ft >n ftftftftft ■f CMHftvO «A t> ^ m >A ftftftftft ft ft^ m cm m ft ft ft ftftft ftftftftft ><) -1 H 1 \OftO>»rH \£> o *a ia »a vor>vOf>vo ftftftftft ftftftftft moflico o r> vo t> ftftftft OOCOt>vO IA -nJ- ft CM rH OOCOt> vO ia ia ia ia m ia ia ia ia ia >f >* cjv cr* cr* cj* cy* cr* cy* cy* cy* cy* o Z 03 o c 49 u CD Eh 3 ■ C © O e» 3 eS — 3 CQ CO E> I a* 05 C3 c C3 S m -3 Su i2 '3 > 03 O rM Z co RECENT TRENDS IN FAMILY INCOME 25 the use of a standardization procedure it can be shown that changes in the weights assigned to the component distributions had no major impact on the overall distribution ; that is, the actual overall distributions did not vary signifi- cantly from the distributions that would have been obtained if there had been no change in population weights throughout the period. Table 1-12 shows the actual income shares received by the top 5 percent and the top 20 percent of the families for 1947 to I960, and shares obtained from standardization procedures applied to the data. Similar information is shown Table 1-12.— Actual and Standardized Gini Concentration Ratios of and Shares of Aggregate Total Money Income Received by the Top 20 Percent and Top 5 Percent of Families: 1947 to I960 Standardized Actual distributions with 1960 1960 distributions with Year and income ranlc iiC UUaX population weights actual population weights lype 01 Age of oize oi iype oi Age of family head family family head (i) (2) (3) (4) (5) (6) TOP 20 PERCENT I960 42 42 42 42 42 42 1959 41 41 41 41 42 42 1958 41 41 41 41 42 42 1957 41 An An 42 a? 1956 41 41 41 41 42 42 1955 42 41 42 42 43 42 1954. 42 41 42 (NA) 43 42 1953 41 40 41 (NA) 43 42 42 42 42 42 43 42 1951 42 41 42 41 43 42 1950 43 42 (NA) (NA) 43 42 1949 42 43 42 43 (NA) 194-8 43 (NA) 42 42 (NA) 43 1 Q47 (NA) 43 42 (NA) 43 TOP 5 PERCENT 1960 17 17 17 17 17 17 1959 16 16 16 16 17 17 1958 16 16 16 16 17 17 1957 16 16 16 16 17 17 1956 16 16 16 16 17 17 1955 17 17 17 17 17 17 1954 16 16 17 (NA) 17 17 1953 16 15 16 (NA) 18 17 1952 18 17 18 17 17 17 1951 17 16 17 16 18 17 1950 17 17 (NA) (NA) 18 17 1949 17 16 17 17 18 (NA) 194-8 17 (NA) 17 17 (NA) 17 1947 18 (NA) 17 17 (NA) 17 GINI RATIO 1960 .369 .369 .369 .369 .369 .369 1959 .366 .360 .363 .365 .370 .367 1958 .354 .348 .351 .349 .375 .373 1957 .351 .346 .349 .346 .375 .370 1956 .355 .353 .362 .355 .375 .372 1955 .366 .357' .365 .359 .378 .374 1954 .373 .363 .371 (NA) .381 .372 1953 .360 .346 .356 (NA) .376 .372 1952 .374 .359 .365 .363 .377 .373 1951 .361 .357 .361 .356 .379 .372 1950 .375 .366 (NA) (NA) .380 (NA) 1949 .379 .362 .371 .371 .382 .374 1948 .369 (NA) .363 .360 (NA) .378 1947 .378 (NA) .365 .360 (NA) .375 NA Not available. Source: Table 1-11. See text for explanation of computations. 26 INCOME DISTRIBUTION IN THE UNITED STATES in this table for Gini Concentration Ratios. The standardized figures for type of family (col. 2) were obtained in the following way. Percent distributions were obtained from the Current Population Survey for each year for each of the following 12 groups: Urban — Husband-wife families, wife in paid labor force Husband-wife families, wife not in paid labor force Families with other male head Families with female head Rural nonfarm — Same as for urban Rural farm — Same as for urban These percent distributions were weighted by the number of families in each group in March 1960, and the results were summed to obtain a new total and percent distribution for the country as a whole. The difference between the original and the adjusted (or standardized) distribution is entirely due to changes in the weights assigned to the component parts of the overall total. A similar procedure using residence by age of head (in 10-year age groups) was applied to obtain the data in column 3 ; and it was again applied using residence and size of family (2 to 7 or more persons) for column 4. Table 1-12 shows that in no case were the results based on the standardized distributions significantly different from the actual distributions. In no year did the share received by the top 5 percent or the top 20 percent of the families in the standard- ized distribution differ from the original distribution by more than one per- centage point. The differences in the concentration ratios were equally small. The figures shown in columns 5 and 6 were prepared by using the 1960 percent distributions for each group for each year and weighting the distributions by the actual number of families in the group. The results were then summed to obtain an adjusted (standardized) distribution for the country as a whole. In this case, the difference between the original and the standardized distribution for the country as a whole is entirely due to changes in the component distribu- tions. Here again, the differences between the actual and the standardized distributions are not significant. NOTES 1 Simon Kuznets, "Economic Growth and Income Inequality," American Economic Review, March 1955, p. 4. 2 Dorothy S. Brady, "Research on the Size Distribution of Income," Studies in Income and Wealth, Vol. 13, National Bureau of Economic Research, New York, 1951. p. 4. 3 Arthur F. Burns, Looking Forward, 31st Annual Report of the National Bureau of Economic Research, p. 4. * Paul Samuelson, Economics, McGraw-Hill Book Co., Inc., New York, fifth edition, 1961, p. 114. s The Changing American Market, Editors of Fortune, 1953, p. 52. RECENT TRENDS IN FAMILY INCOME 27 NOTES— Continued 8 For an entirely different view of trends in income distribution see Gabriel Kolko, Wealth and Power in America, New York, Praeger, 1962. Kolko concludes that "A radically unequal distribution of income has been characteristic of the American social structure since at least 1910, and despite minor year-to-year fluctuations in the shares of the income-tenths, no significant trend toward income equality has appeared" (p. 13). This conclusion is based on data for 1910 to 1937 prepared by the National Industrial Conference Board and for 1941 to 1959 by the Survey Research Center of the University of Michigan. Kolko states that the NICB data are the best material on income distribution by tenths for the period prior to 1941. This statement is very questionable. The NICB data were considered so poor by a panel of experts, including Selma F. Goldsmith and Simon Kuznets, that they were excluded from U.S. Bureau of the Census, Historical Statistics of the United States: Colonial Times to 1957, even though they had appeared in the earlier version of that book, Historical Statistics of the United States, 1789-1945. The figures for 1929 and 1935—1936 shown in table 1-1 are thought to be much more reliable than those used by Kolko. An examination of the figures used by Kolko shows that the share of income received by the highest tenth of income recipients dropped from 38 and 39 percent in 1921 and 1929, to 34 percent in 1927 and 1941, to 29 percent in 1958. He dismisses the figures for 1921 and 1929 without further explanation as representing exceptional years. He then con- cludes that the difference between the prewar and postwar figures can be eliminated when the latter are "corrected to allow for their exclusion of all forms of income in kind and the very substantial understatement of income by the wealthy." The figures in table 1-1 include many types of income in kind and they have also been adjusted for underreporting of income. They do not include various items that accrue primarily to the wealthy which Kolko thinks should be added, notably expense accounts and undistributed profits. Also excluded from the concept and not mentioned by Kolko are various types of fringe benefits such as life insurance, medical care, health insurance and pension plans, as well as government services, which have been increasing rapidly in recent years and are widely distributed thoughout the population. A study published in 1954 by Selma F. Goldsmith and her colleagues showed that incomes were more equally distributed in the postwar period than in 1929, even when allowance is made for undistributed corporate profits (Selma F. Goldsmith, et al., "Size Distribution of Income Since the Mid-Thirties," Review of Economics and Statistics, February 1954, p. 20). A more recent study shows that the addition of capital gains to the distribution increases the share received by the wealthiest 5 percent by only a fraction of a percentage point (Maurice Liebenberg and Jeannette M. Fitzwilliams, "Size Distribution of Personal Income, 1957-60," Survey of Current Business, May 1961, p. 14). 7 Selma F. Goldsmith, et al., "Size Distribution of Income Since the Mid-Thirties," Review of Economics and Statistics, February 1954, p. 132 ; and Survey of Current Business, April 1964, p. 8. 8 U.S. Bureau of the Census, Statistical Abstract of the United States: 1964, p. 416. 9 For figures showing taxes paid as a percent of income by income class in 1958, see Tax Foundation, Allocation of the Tax Burden by Income Class, New York, 1960, p. 17. This source shows no variation in the percent of income paid in Federal, State, and local taxes for each income class below $15,000. In each class, about one-fifth of the income was paid in taxes. 10 Only brief reference to the conceptual problems associated with the interpretation of statistics on income distribution is made here. For a more complete discussion, see Dorothy S. Brady, "Research on the Size Distribution of Income," Studies in Income and Wealth, Vol. 13, National Bureau of Economic Research, New York, 1951. 28 INCOME DISTRIBUTION IN THE UNITED STATES NOTES— Continued n Simon Kuznets, op. cit., p. 3. 12 See Office of Business Economics, Income Distribution in the United States, 1953, p. 20. a Based on data of the Office of Business Economics. For a more complete description of the items included in family personal income see appendix A. 14 Maurice Liebenberg and Jeannette M. Fitzwilliams, "Size Distribution of Personal Income, 1957-60," Survey of Current Business, May 1961, pp. 12—15. 15 See, for example, Office of Business Economics, U.S. Income and Output, 1958. 16 For a more detailed account of the definitions and procedures used to obtain the estimates shown in table 1-2, see Selma F. Goldsmith, "Appraisal of Basic Data Available for Constructing Income Size Distributions," Studies in Income and Wealth, Vol. 13, National Bureau of Economic Research, New York, 1951. See also Selma F. Goldsmith, "Size Distribution of Personal Income," Survey of Current Business, April 1958. 17 Estimate for 1929 from U.S. Bureau of the Census, Historical Statistics of the United States: Colonial Times to 1957, Series A 242; estimate for 1960 from U.S. Bureau of the Census, Current Population Reports — Population Characteristics, Series P-20, No. 119. 18 U.S. Bureau of the Census, Current Population Reports — Household and Family Characteristics, Series P-20, No. 125. 19 The OBE aggregates in table 1-4 differ from those shown in previous tables because several adjustments were made in the OBE data before they could be compared with the census results. These adjustments included the subtraction of nonmoney items not covered in the census surveys and the addition of certain types of income covered in the census but not in OBE. A detailed description of these adjustments is presented in appendix A. For a more technical discussion of the adjustment procedure see Selma F. Goldsmith, "The Relation of Census Income Distribution Statistics to Other Income Data," Studies in Income and Wealth, Vol. 23, Princeton University Press, 1958. 20 For a further discussion of the comparability of CPS, Census, and OBE income aggregates and distributions, see appendix A. 21 For an eloquent description of poverty in the United States, see Michael Harrington, The Other America, Macmillan Co., New York, 1962. 23 Simon Kuznets, Share of Upper Income Groups in Income and Savings, National Bureau of Economic Research, New York, 1953. 23 The figures shown in table I— 1 are for families and unrelated individuals combined. OBE data for families alone are shown in table 1-1 for selected years. Census data for families alone appear in U.S. Bureau of the Census, Trends in the Income of Families and Persons in the United States: 1947 to 1960, Technical Paper No. 8, by Herman P. Miller, 1963, table 1. The trends based on families alone are virtually identical with those based on families and unrelated individuals combined. 2i Simon Kuznets, "Income Distribution and Changes in Consumption," The Changing American Population, Institute of Life Insurance, 1962, pp. 36—37. 88 Simon Kuznets, "Economic Growth and Income Inequality," American Economic Review, March 1955, p. 8. 26 U.S. Bureau of the Census, Trends in the Income of Families and Persons in the United States: 1947 to 1960, Technical Paper No. 8, by Herman P. Miller, 1963. 27 Based on Lorenz curves constructed for data for farm-operator families and nonfarm families shown in Maurice Liebenberg and Jeannette M. Fitzwilliams, "Size Distribution of Personal Income, 1957-60," Survey of Current Business, May 1961. 28 See Morris A. Copeland, "The Social and Economic Determinants of the Distribution of Income in the United States," American Economic Review, March 1947. CHAPTER II CHANGES IN THE COMPOSITION OF BROAD INCOME GROUPS: 1947 TO 1960 Measures of income status Chapter I discussed changes during the past 30 years in the number of families at different income levels for various periods of time, presenting the figures in current dollars and in dollars of constant purchasing power. The continuous drop in the proportion of families at the lower income levels provides an excellent indication of how widely the increases in real incomes have been distributed throughout the population. Only overall trends were discussed in chapter I; nothing was said about changes in the social and economic composition of the various income groups. This chapter focuses on the characteristics of low-, middle-, and high-income families and on the changes in the composition of these groups during the postwar period. Have there been any significant trends in the kinds of families found at different income levels? Do farmers, the aged, and nonwhites each comprise a constant, increasing, or decreasing proportion of the low-income population? What are the dominant population components of the high-income groups, and how has the composition of these groups changed during the past 15 years? These are the kinds of questions to be considered next. In discussing income status, one immediately faces the problem of defining poverty, affluence, or any of the other terms used to describe the various segments of the income curve. It is customary to start with the disclaimer that poverty (or affluence) is relative and cannot be defined objectively, and to state that the lines of demarcation are arbitrarv and that the results are intended to serve as rough descriptions of the bottom or top groups in the income distribution. The first congressional investigation of low-income families ever conducted in the United States began with the explanation that the income limits used (under $2,000 for families and under $1,000 for unrelated individuals) were ". . . not intended to be ... a definition of 'low' income." 1 In 1961, Selma F. Gold- smith wrote : I cannot claim to have made any progress whatsoever ... [in defining poverty] . . . and the following discussion focuses on the composition of the income range under $3,000 in terms of types of multiperson families, and under $2,000 for types of unre- lated individuals. These income points were chosen arbitrarily and are not to be taken as "definitions" of poverty. 2 29 30 INCOME DISTRIBUTION IN THE UNITED STATES The present study is no exception to the rule. Two different methods of selecting income limits are examined in this chapter; both are arbitrary and have merit only as very general bases for exploring changes in broad segments of the income curve. Some economists who have thought about this problem deny the need for definitions — perhaps because they realize the futility of trying to define the undefinable. J. K. Galbraith, for example, starts his discussion of poverty in modern America by stating: "There is no firm definition of this phenomenon and ... no precise definition is needed." 3 This approach can be used so long as one works on a broad philosophical plane where the concepts are discussed in very general terms. But even Galbraith feels compelled even- tually to define poverty in terms of a given point on the income scale. Indeed, once the task of describing the characteristics of high- and low-income families is undertaken, as in the present study, the need for definitions is imperative for the very practical reason that the variables used to describe each group must be numerically sequenced so that they can be analyzed quantitatively. Much needless soul-searching can be avoided if we are reconciled at the outset to the fact that there is no objective definition of poverty any more than there ;s an objective definition of art or beauty. The standards of poverty are cul- turally determined. They can be arbitrarily defined for a given time and place, but they vary from place to place and they differ from time to time for a given place. Over a decade ago Dorothy Brady wrote that : . . . when faced directly with the problem of determining . . . [poverty] . . . for a given time and place, the theorist will deny the possibility of a unique answer and the propagandist will settle for any one of many solutions if the result suits his purposes. 4 The prophetic wisdom of this remark can be seen most clearly by examining the way in which two recent writers on the subject have manipulated the same income figures to meet their particular needs. In The Affluent Society, J. K. Galbraith presents the general thesis that Ameri- can and European society has changed from a world of mass poverty to a world of affluence, but that changes in economic thinking have not kept pace with the change in events. "As a result," he says, "we are guided, in part, by ideas that are relevant to another world . . ." 5 (that is, a world of poverty) . Near the end of this book, when he comes to a discussion of poverty, Galbraith points to the median family income of about $4,000 for the United States as evidence that American poverty can ". . . no longer be presented as a universal or massive affliction." 8 His concept of poverty, which includes people whose ". . . in- come, even if adequate for survival, falls markedly behind that of the community. . . ." identifies the hard core of the poor as those families and individuals with incomes under $1,000 in 1955. 7 In 1962 Leon Keyserling published his study, Poverty and Deprivation in the U.S., which he subtitled "The Plight of Two-Fifths of a Nation." In this pamphlet Keyserling placed the poverty line at $4,000 — which, he states, COMPOSITION OF BROAD INCOME GROUPS 31 . . many authorities fix as the amount required to place the multiple-person family above poverty in the American context today." 8 In a later study, Progress or Poverty, published subsequent to the "attack on poverty" launched by the Johnson Administration, Keyserling changed his estimate of the poverty line to $3,000 for families of two or more persons to conform with official figures in use at the time. 9 The difference between the two estimates ($4,000 and $3,000) is more apparent than real since the former pertains to OBE statistics which include nonmoney income whereas the latter pertains to money income figures prepared by the Bureau of the Census. Without quarreling about the particular level selected or how it was selected, it is interesting to note that the same dollar value ($4,000) was used within a period of several years by two outstanding economists to show on the one hand that poverty has been virtually eliminated, and on the other hand that poverty is very widespread, afflicting 1 out of every 5 persons in the United States. Another recent attempt to measure the low-income population is Robert Lampman's excellent study for the Joint Economic Committee, The Low- Income Population and Economic Growth. Lampman there defines a low- income person as ". . . one with an income equivalent to that of a member of a four-person family with total money income of not more than $2,500 in ^57 dollars." 10 This definition attempts to relate family income to the "needs' ">f the family based on the number of persons and their ages. According to th definition, each member of a 6-person family would be classified in low-income status if the total family income in 1957 was under $3,236. An unrelated indi- vidual with an income under $1,157 would receive the same classification. The poverty line for this study, selected in a very arbitrary way, was largely an exten- sion of the $2,000 value used in the 1949 and 1955 studies of low-income families conducted by the Joint Economic Committee, converted to 1957 dollars and adjusted for size of family. 11 On the basis of this definition Lampman con- cludes that about 1 person out of every 5 was in low-income status in 1957. The study consistently shows a high degree of sophistication and a keen aware- ness of the problems of interpretation in this difficult area; but when, at one point, Lampman asserts that "A more aggressive Government policy could hasten the elimination of poverty and bring about its virtual elimination in one generation," 12 he demonstrates a basic misunderstanding of the relative nature of poverty. There can be no doubt that if the incomes of the poorest families were raised to the levels specified by Lampman, standards would also be raised — but large numbers of families would still be living at substandard levels. Dorothy Brady summarized this problem very well when she stated that : . . . inadequate incomes can never be eliminated in any final sense because we as human beings always tend to judge incomes below the average as inadequate. And if this conclusion is correct, low incomes become a matter not of the size of the income but of the prevailing attitude toward the distribution. 13 32 INCOME DISTRIBUTION IN THE UNITED STATES In this chapter several different measures of income status are used, each focus- ing on a different aspect of the problem. A brief review of the socioeconomic composition of broad income levels in 1960 is followed by a section showing families and unrelated individuals classified into several broad constant-dollar income levels (of 1959 purchasing power) for the years 1947 to I960. 14 Implicit in a tabulation such as this is the consideration of "poverty" and "affluence" as absolutes since no allowance is made for the increase in customary "needs" or standards over time. If this analysis had been extended back to 1929, for example, it would have shown that about one-third of the families and individuals had real incomes under $2,000 (in terms of 1962 purchasing power) , compared with only about one-eighth in 1962. At the turn of the century, it is very likely that the great majority of families had incomes well below $2,000. The use of constant-dollar income limits, therefore, provides a rough measure of the proportion of families that could afford a given level of living at various points in time; but it makes no allowance for the fact that "needs" are relative, and are quite likely to be much different in a society where half the families and individuals have incomes under $2,000, than they are in a society where only one-eighth of the families and individuals are at this low level. In the final section of this chapter families are ranked by income and classified into fifths, and an analysis is made of changes in the composition of each fifth (and of the wealthiest 5 percent) for each year in the postwar period. Under this procedure the income limit is established for each year for the poorest 20 percent of all families, for the next 20 percent, and so on, and characteristics of families with incomes within the dollar limits for each fifth are compared from one year to the next. Only relative income position is considered ; the fact that the income limit for the poorest 20 percent of all families increased from $1,600 in 1947 to $2,800 in 1960 is ignored. Some authorities do not regard this measure as very meaningful, since it creates the impression that there has been no increase in real incomes over time. Leon Keyserling, for example, states that: ... if we were to say that, with more than one-fifth of the American people living in poverty in 1960, we should define as living in poverty the lowest income fifth of the people in 1929, we would reach the palpably wrong conclusion that we have made no actual progress. 15 The fact is, however, that this measure, by focusing on relative income position rather than on absolute income, takes into rough account the increases in "needs" that accompany rising real incomes. The poorest 20 percent of the families in the United States today may have higher standards of living than the wealthiest 20 percent of 50 years ago ; they may also have better food, clothing, and shelter, and greater life expectancy than top-income groups in many other parts of the world. But these facts provide little consolation when the poorest families look about them and see how little they have in comparison with what their neighbors have. If poverty and affluence are relative, then surely in evaluating these concepts relative income position must have meaning. COMPOSITION OF BROAD INCOME GROUPS 33 Socioeconomic composition of broad income groups, 1960 An overall view. Before examining changes in the composition of various income groups over time, it will be profitable to obtain an overall view of the social and economic characteristics of each group by examining the data for a recent year — 1960. These are presented in table II— 1. This background pro- vides a frame of reference against which the changes over time can be compared. In the following section, changes in the socioeconomic composition of each income group are examined for selected years during the postwar period. Families and unrelated individuals are not shown together in table II — 1 because of the great differences in the characteristics, needs, and incomes of the two groups. As previously noted, families are defined by the Census Bureau as groups of two or more persons related by blood, marriage, or adoption, and residing together. The income of the family is the total amount of money received by all family members during the calendar year. 16 Unrelated indi- viduals are persons (other than inmates of institutions) who were not living with relatives at the time each survey was made. As this definition implies, family incomes tend to be much higher than those of unrelated individuals because more than one person can be an income recipient. By the same token, family needs are also greater than those of unrelated individuals because a larger number of people have to be supported out of a given income. However, even a brief look at the characteristics of unrelated individuals shows other and per- haps more important reasons for their lower income status. What kinds of people live alone in a society where the great majority of the population resides in family groups? Figure II— 1 provides an important part of the explanation. About one-third of the unrelated individuals in March 1961 were aged 65 or over, and an additional 10 percent were under 25. Together, the young and the old constitute over two-fifths of all unrelated individuals. It is quite clear that a very large proportion of the unrelated individuals consists of widows and widowers who choose to maintain their own residences rather than move in with their children or enter old-age homes. Younger persons constitute another important segment of the unrelated- individual population, accounting for about one-tenth of the total in March 1961. The median income of those in this group was also relatively low ($1,700), largely because they lacked the skill and experience to command more than minimal wages. Unrelated individuals in the most productive age groups (25 to 64) accounted for about three-fifths of the total. Although their incomes on the average were considerably higher than those of younger and older persons, by most standards they were quite low; in 1960, one-half had incomes under $2,800. The rela- tively low incomes of this group were largely due to inability to work, failure to find work, or having low-paying jobs when they did work. Figure 1 1-2 shows that in March 1961 about one-fourth of the unrelated individuals between 14 and 64 years old were not in the civilian labor force or were unemployed; an 34 INCOME DISTRIBUTION IN THE UNITED STATES Table II- 1.— Selected Characteristics of Families and Unrelated Individuals, by Total Money Income in I960 Selected characteristics Total Under «p J , uuu $3,000 to $4,999 $5,000 to $9,999 $10,000 and over -45,05 9,866 9,229 19,836 6,502 Age of Head Total 100.0 100.0 100.0 100.0 5.1 7.4 8.2 4.0 0.6 19.9 13.3 22.7 24.5 12.1 23.9 14.1 21.2 28.2 29.5 21.6 15.9 18.7 22.3 32.0 15 ft 17.0 15.4 14.4 19.0 li.6 32.2 13.8 6.6 6.8 45.5 54.5 44.0 42.6 47.6 Size of Family Total 100.0 100.0 100.0 100.0 100.0 32.7 52.1 34.0 25.4 23.8 20.9 17.0 22.2 22.1 21.4 20.4 11.9 19.2 24.2 23.8 13.0 7.5 11.4 15.1 17.4 6.6 4.0 6.5 7.5 8.0 6.3 7.5 6.8 5.7 5.6 J . r J. J5 , OO "\ PA J • OO 7 Q7 Number of Earners Total 100.0 100.0 100.0 100.0 100.0 7.3 27.6 4.0 0.8 0.8 92.7 72.4 96.1 99.2 99.2 1 46.4 46.2 57.5 46.0 32.1 2 35.7 21.1 32.5 42.4 42.0 10.6 5.1 6.1 10.8 25.1 1 7ft 1 . f o i m i sft 1 01 i . "i o on Type of Family Total 100.0 100.0 100.0 100.0 100.0 89.8 76.5 89.0 94.6 96.9 87.2 72.9 86.1 92.4 94.7 26.4 13.4 21.9 30.9 38.9 60.8 59.5 64.2 61.5 55.8 2.6 3.6 2.9 2.2 2.2 10.1 23.6 11.0 5.4 3.1 Number of Related Children Total 100.0 100.0 100.0 100.0 100.0 40.3 53.4 39.2 33.7 42.6 1 child 19.4 15.6 20.8 20.7 19.1 18.5 11.9 18.0 21.9 18.8 11.4 ' 8.2 10.2 13.2 12.3 5.5 4.0 6.2 6.3 4.6 2.4 2.8 2.8 2.3 1.4 2.5 4.2 2.8 1.9 1.2 - . 1 . «cO l in 1 9Q Color and Fann-Nonf arm Residence Total 100.0 100.0 100.0 100.0 100.0 White 90.5 79.5 88.5 94.7 96.8 83.7 64.9 80.5 91.2 94.1 6.7 14.6 8.1 3.5 2.7 9.5 20.5 11.5 5.3 3.2 ft a o . o ID, O 1 1 i 1 o 2, c. 7 O ,5 . <: "5 Q U. X cjnp x oyine n u ouauiis ana uccupaxiou oi neaa Total 100.0 100.0 100.0 100.0 100.0 78.1 52.2 75.0 87.5 93.0 5.0 6.7 7.2 4.3 1.8 In Armed Forces or not in labor force 16.9 41.1 17.9 8.2 5.2 100.0 100.0 100.0 100.0 100.0 Profess'l, managerial, & kind, wkrs., exc. farm. 28.2 14.7 17.4 26.5 57.0 9.7 11.4 8.1 7.1 17.3 Salaried 18.5 3.3 9.3 19.4 39.7 6.5 24.1 8.0 2.4 1.9 Clerical, sales, and kindred workers 13.7 7.3 13.5 16.0 12.7 19.3 9.0 16.9 24.7 15.5 18.3 14.3 24.2 20.5 8.4 Service workers, including private household.... 7.3 14.1 10.1 5.6 3.0 Laborers, exc. mine 6.7 16.5 10.0 4.3 1.5 — Represents zero. COMPOSITION OF BROAD INCOME GROUPS 35 Table II- 1.— Selected Characteristics of Families and Unrelated Individuals, by Total Money Income in I960— Con. Selected characteristics Total Und.Gr rH rH i\ rH NT CM CO r— s m i i ci rH m NO o u rH H On <-H m m cm c- vO Nf rH Nf rH >f CO ON Ofl « lOCMOi O t> t> o no m ON - d > Nf rH o m rH CM rH rH CI CM r-4 t-> rH rH rH rH H rH 69- -w- 49- o cn. ■£> r-< r-\ *0 in ^-s NO | | i — t CM CN, rH o o o> rH r-t -t O o m rH o CO CM On NO ON CD o o> to N r rri rH fl \0 m On r m rH CM m ^f o o o* o ~ -p - NO rH NO nO r-1 CJ in o 69 69- c 69 69 •H , .. rH t* St NT rH CNi \0 CM CO vO CO CM i i [> Nf O Nf c O On O rH ■sT m cr> rH rH CO t> rH O O m O t> ON m n co >f n m vO O nD rH CM Nf NO a O O O E ~ -P - c> ntMH rH $ CN. rH cn, Nf Cr> 69 69- CU bO (0 rH OJ -sj- CM rH Nf O CM NO 1 1 O O cn. o b o CI H CO iD in \0 t> CM rH CO iH CO rH m t> rH 8 Sh O nO rr\ m m CM CM Nf CO CO Nf O CM CM NO > B □ <: "O » C CI 5 €r> rH 69 rH rH rH 69 rH rH NO vO to m l> CT> O rH t> CN, | | CN, NO ^f rH rH £> rH m vO -sf O O vD CJ> to CN. m rH ON co ON m >t m CI CO CO NO CM CO rH NO [n m -p in m >f rH NO m rH E-i 69 69- cn, O ci t> m lO CI H NO c^l ~ r- i i Nf CO m a O on rH CN, rH o a o i> m rH 69 69- 69- Nf 3 CO o £> D< ^ CO CM Nf 1 1 m nC i> to m rH r-i on cm O lO iC H CM* O O o O o m CM* O O o O Cf> O CO o ON O O ON rH CN, rH •* -P -V rH CQ in On rH rH h 69- 69- 69- 6% E H O rH O tN o CT» vO O O O rH O o t> 1 1 !> Nf m £> C -O O On O On •H C On ci o l> vO fl vO* O rH CM NO o rH Nf O O CM crH o o cr> o t> o ON cu o - -p - on rH O rH •p ^ :£ 69 69- CI CN. a) ca 69 69- bo C CU O bOi-H a o c-. o-i r> rH C\ O □ O c ON 1 | CO nO o O O 00 Nf | UI V rl O nO O onm rH CM rH CM O CO rH O O CO 3 O m CM rH o rH T3 - S 69 no" rH 69 rH ON 69- rH On o t> t> O ^J- CM CI CN, Nf 1 1 ON Nf ON Nf CO rH rH cm o tO Oi CM ^J" CM rH rH CO o CN, CM* rH O rH a) o o ON -p rH NO rH o nO o E-> CM 69- CM 69 O CM □ co co n n h ■Nf CO O l I ON NO \0 o u CM H rH rl O TJ « m to -J- C"\ -4- ^ m H n H t> ON o Nf rH CM CO g > CO CM o rl Hrl O CD O m CN. rH rH 69- Nf to n vo Nf O rH rH c> O I 1 rH NO rH m o o» (H r> rH O On >* >t CM n m m o rH c> O m Nf CO rH CO o o o O rH rH rH rH o rH rH i-H •a •v -p -V 69- rH NO rH rH rH CD a) a > o o on t> ■4 n st O m c> Nf CO O 1 l O CO Nf o o o Nf rH CN, iH O o co CO rH CO On O t> NO NO no t>- m CO -P -v CO rH rH cn, >f 69- o O CQ ON o m co [> O ff> rH O 1 l O cn, c- CN. o rH H * % • rH r-i u o CM o o c\ t> t> CM ON O CM* Nf Nf ?5 "i CU o m rH r\ CM o CM •a -> o Nf rH c c pj rH & 69 .-- c- o c- CM rH CM C\ CM O l l cn, m m rH nO H Nf rH o -vf C^l [> O m o NT CO O NO c> t> Nf CO rH CM rH rH o rH rH rH o irv CM rH E-i CN, o o In E O V rH 1 p. HH E H 0) CU I CO < o o O T3 o" § rH «r> Q o z o o on m on w 69- ON on o e> ■p - oc on CM tO H St r-i Nf lO CM lO C^l to i> c-- — O CM O CO Nt Cvi Nf ^ m CM rH O rH CO o~i on vo c\j r> M [> >f O ■* r- m m \D (M - — * cm c- o pa -si- cm m — rH m CO m -si- m in cm in am ^ vO CM CO tO 00 t> m Q rH rH CM 3D CM ON t> st CO m iD C~- o m in ^ \D so CD-I- CM m \0^- -st m mi rH>— tD CM rH >t H A to v£) m on co m intpsf m cn in CO 05 CQ CO CM CM ^ en ra co co r-l CN — • io c-\ m vo o cm en m iO v£> t> C\ h ic *o m CO E ii rH o o C -O £ o a) ca bo C 60 rH 9a Q P o 5 o 3 .3 on on b Q CD O •O - 3 CM vfi CMC H O m cn o cm to m rH o m o CM « 8 cm m m io CM* rH rH O CM CM O r-i -~t t- (M in j CM O O O \0 rH vOHH rH CO o N o r> m in K CM CO O O CM rH f \ CM £ °. 5 8 CM rH >f -J n \0 cm rn CM O rH to C*- 4*4 t> CT> CM f*\ 1*1 vO CM O f"i vO CO O f\ rH rH rH m vO O o >C H H rH CM O CM O m rH CM -j- CM to O >!• vO CM rH rH •3 9 > o cu c CJ CO rH | o rH CO O I 8 8 OHO o o p" rH -st CM O CM O 3 cm 1 8 ON t> 0> no(M h eg h a* on m vO >t CM O CO CN OC O CO o $™8 O O I 58 ■ ON \0 vO O l » a> o i*irj»>o o m cm m cm (MiOO <"*> to CM iO CM >r oo en <^ co o > rH rH CM rH CN. 0> O p" iO* o o CM rH rH rH C O SI It CD as r-i cu oi cu i C0 Cm U r-i o E a> G co co as g CO CO )3 Z fc. J O H £ cu co O CO C -P O 4) CO CH ftll •Ha) ■h -o co CD O L 3 iS II s 08 T3 C a> *j C3 1 O o COMPOSITION OF BROAD INCOME GROUPS 45 o o u n pa pa pa pa pp H cp pa cp CP O t3 CD o § o H s ^ ^ ( j . t ^ ^ i i i _ — * , — o on pa pa n pa CP pa CQ CQ CQ CQ o o I o o on * -p * o «r> 2» c •H i i i ^-.^^ 00 III O no ' — ^ 'c o o m" pa pa pa pa CP m £> H CP m" mea o on ts- vo «r> «r> age g s III f"N • ' * p-l p CM III CM t> On IS, Ni t> H no pa pa 00 H CM On rH ,8 > CD O •i << T3 «. £5 cn. rH M H rH rH rH m NO ,-( CO m on H — ' 111 O cNj en 5>HH t> t\ H III CM sj ON S «r> | | | - — s . , , O O Q ^ m pa pa oa pa pa pa • o CP CP CQ CP — * 0*0 o - a > rH o 3 o H r — v s — V l | 1 — s — * — V * — ^ o i i l ^ — V cq cp pa pa cn CP CP • cq pa cp pa Q On O O On O O QC» •s -p - rH CO in o E 69- to a h O rH o o vO o iii st cm m ON (3 "O o on pa pa pa pa cp CP cn •H O ON ON o ON st CM* CI Cm O O ON o NO H H CD O ~ .p « rH ■P r\ st aJ to Cr> «r> SP £ CD O M rH m o III no cm o to o III ON ON O CM bp r-J H O on o ■"1 On cm m O CM m CD o 8 o rH S «r> rH «r> H CM rH Q III in CM rH CM ON III O n0 O 00 o rH CM o sf n MD en CM kO c- Q to m on o cd o cn O NO rH ■P CM rH st rH «r> H o x — , r — V 1 1 1 ' — * r — — * . s ON ^ — ^ 1 1 1 ^vx-^^ r — N O f-i 05 pa CP CP CP CP H pa pa co CP O TI II) „-fl > o 3 o rH ON i i i r-^ O On co pa CP CP CP CP NO H pa cp cp pa O ON ^ — ' v — <* N 'V ' V ' ' — ^ — ' - — - ' — * co T3 -p * 3 m ON cd if* m- rH CO % g o on ON III NO NO ON o o on pa ca cp pa cp 'm rH o o o c3 r> °* ^" On st Cm o* •v -p rH a> C c\ sf 6 -h Cr> fr> o O CO a u st III O C> CM ON CM III rH m CM O M CD o rH H rH H u o O i — 1 \0 On in t> st m in ON um CD O CN, St tO rl H H XI •> rH rH a m NO iii m o vO vO ON III m rH ON Pi rH nD H NO H cd rH m H O st O in cm to t>* P ClrlH st to CM rH rH o rH CM H 5 •H ? 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'. c *3 o co eu fH rH t, 60 K ....... e a o o rH C • • • • • t, caai.ccccc E E-i^lT3 - C"c5 , c3't1 - c3 3 -HH H r[r) H rl 2 J3 -r* tH -H iH «|H «H o js si x: a a a o o o o o o o 2 h en n m \0 O £ -= 3 •rl C a £ o -5 3 Z O E-| 9 is -= c = o 555 I. fc, 3 O Q Z Z W COMPOSITION OF BROAD INCOME GROUPS Nt CO O H N \C i£l to O m O CO tO tO rH O H >fl tfMO O st O 2 g < O to tO v^s_- O rH t> CM m Os SO o m st rH st- t> O O i-l Cl sO to st sO O CO Os st Os -Cl rH ci so o> ST (T- to o O C- st O- O >!• sO O m st st t> CM CO O t> CM to Cl OOlOmflO>rl O Os m ci o to in o to st t> to co m o o st n OKMMHrll^st O rH to in ci to O CO rH vO rH o st O H iO ()\ N ri to C| D- sO o c- rH o r- st m O sj CM H o cm t> to c, O rH m rH rH O 0> rH t> IA CO rH O rltO rllfl ritO O CO r> rH VD rH ft o O st Cl st rH SO rH o so cm t>- o Os t> o so o ci co st m O st CM rH O to m t> O O SO to O CO CO st o c~- so o t> m m O CO O O CM O CM CO rH tO Cl tO O i — I rH Os rH sO Cl O sO CM CS, Os O CM Os rH CO Ci to o o so' rH m n os' O tO O rH SO rH rH st o o O rH O f- Cl rH rH O CO CO O CM sO sO O CM O Os Os OOnHst O CM m CM O CI sO CO CO t> c- O st m m cm st o 8 so m in o so os r-i r-< r. r. 00 rH O CO Os CM t> st 0- Ostrl H O O m m o O cs. to t> rH m c- O CMA CM n m O O t> O rH so CM O m Os CO -st t> O CM rH t>- Cl st st O Os tO r-t CO m O O st rH rH o m st so m o so o o o m st- O Os so CO Ci Ci O O O rH sO CM O rH Cl CI rH Cl Os O Os CM sf rH CM CM O C- O CO m O t> m ci cm cm ci O Os CO O O CM CM O CO t> Os CM C- t> O O- st t> CM O sO tN O m O CM sj- CM O rH so m rH st Os O O CM st O m Os O st O ci t> cm m O i-i t> CM f- st O O m rH rH rH 9) ::::::! tH rH O CO -P CO CQ CO CO CO CO o c c c c c c E-i O O O O CO CO CO CO CO CO u u u u f. u CD CD CD CD CD CD cm ci sj- m so c~- O CM O sO CM O sO C- rH m O CM st CM O o ci m co st ci 2 ::::::& > • co co co co co o •h h h h fa • CO CO CO CO CO TJ rH CD CD CD CD CD C co >>>>>>>>>>« •P O st sj- st st st CO H CM Cl sr in so ^ O O O O O CD 4J *J p JJ 4J >s st m m m m m rH CM Cl st m sO co co fn U (h CD CD CD C C C c3 co c3 CD CD CD rH CM Cl CD O (3 CD Cm O is o o Cm ,0 +3 CO C M rH CO CD O 3 CO £1 T3 -P CD CO 'H CO M rH CO P PV P, CO 0) -H C rH Cm CO *H CO CU -p c o •H P -p t3 -a O CO CD CD CD Eh CD .h Cm Ch cd a CO CO E CD u CD CD 43 rH s g C 2 5 54 INCOME DISTRIBUTION IN THE UNITED STATES c o U I 8 CN t> o to CO o f\ cm m r> O -vf CM r-l 03 BO <<<<<<;<<:<<<<;«a;<<3;< •zzzzzz-zzz-zz-zzzz ocouoocvjr-icMc-- O t> to 2 fM t> 2 z O 00 r-l v_, Oto r> n otocouo^^i>.r--uo,-iNt<tco^oo 8 Cn O -tf CM r-t u I— I H ta S3 2 < u Q w H U uj — J CO vvT < J _l o Q O to t> Q CO vO O O no uo o to to o Wv \0 \0"AOOt>C\lvXim rH Ot>C--rHiH\Or-|lAv£)COt\Ji>CO-^iHm CM UO OtJiO>flO^CMN O >t r-l r-l O CM to — • « ; fiAC>0»vO^HOJ\000 , ^vOO i n 8S 8 OOOOr-ICMCOO--* t> ^-i t> ^ oo f- >J- vO CM CO i-H H (M>f ri Hrl O co o \0 o<— i^t>^i>c\iiAi>ifitn\o»on"Ac\j Ov£)OCM«M>r-l>C O CO C- CM O t> ^O CO O 8CM t> CO m N O N CM CO H H CM^ H HH O N ifl co oCMr>>AtOrHOrHvo>j-i>-uoocM>tCM 8Q >f UO OCVOHaOtOrinnrJlOCOtONfO VO tO O CM r-l i-l OCOuOCOO*Ot>CM 8to to co to cm co >f r-l 1-1 vO v© 00 to HO t> >o V oVi H H CM^ n HH Ovtoo Otot>vOr\vOi— i n h n h o CN l/"N CN OOOtOO-CMr-WO C7> [> CM Nf r-l — I o co t> n Hto cuvoto 8(J> O t> ^J- t> CM no O r> CM H OJ ^ n H H O 0> CO t> OvO^OuOCOr-lt>CMrOO-JCOr-ltOr-l §CMOCMCT>COC~-r-lCOCMC>vOCOCOUOr-l CM r-l r-l ss < C/5 z 5 8 z l-H r* w Z o a < (2 ca c/o UJ 2 < — I. i H O0"><- 1 CO H CM n if> O CM to uo >t CM 00 uo to 8CT\Q h f\ H ~t O r- CM ,_| CM vj- CO rH rH O CT> CO CO 8 CO IN CO UO CO OOi>couOr>Ot>uoc^OuouOr-iuoco 8COOCNitOtOi>rHCOCMO>C\COt>UOt> CM rH r-l OvOtNO-NtCMCOiH co c- cm to uo co -sf >f rlH O vO «l^lO«\rllA 8£8 O H Nt OCO>*C»OC^CMr>OOCOO>J'CCUOCM \0 O 1 QCMOrHvpt--vO.HtOCOtOr>COO>*OCM UO CO O CM rH rH O-vtvOCM^tOuotJv 8Q r> CM CO UO CM CO •A r-t f-H O CO CM rH CO vO CO CO O 8to H to «-im H >f H r> CM rl IM>f n HH O CO CO ^ OtOM\|tMHt\IOiHOO^CMH(rm O i> CO uo OHO'CMMM^CMrvHnOnO'jm 8tM vO O OCOOCM^O*COr-lN*COO*uONrO^C> UO >f O CM rH r-l e J* 1— o ft "5 c o 'c/j 00 v2 o 1- _ a ry) Cv ■o c o <§* £ co 2, '3 > OS o 2 r? COMPOSITION OF BROAD INCOME GROUPS 3 CM O fs st NO H CNJ (> • N O^HOOHO O H win (M H O NO On t> CO O CI CO t> ...<<•• O in rl 2 Z st st CO St on O NO O rH UN rH t> ototoMnmo o o> o\ m o 0\t ^co NO . . . < «• . . O st On Z Z«l«l O TV CNJ NO NO St ^0 o o> O O no C- l> O UN O CM o o O CO On C\J [>- st t> O co i — I to in no o m t> o to in cni O t> 00 On \0 O to O rH On to CJ NO CNJ o o> m in no m o O st O i — I St CN, to o o m on no O CN CN t> e» to C- st CN O UN St CI ON NO St O CNJ to ON st to to O ON rH O CN o to to CNJ vo O CM O St O to O CN st O to to O St O H (M «N O O CN CN CN i-l O O CNJ t> m O O O UN C\J CO rH CN t>- O NO CV CO On O st st 00 NO rH NO O NO NO st to On t> o CV m i/N to t> cn O O CN CN st O NO NO CN CNJ | — I st O O tN IT> O rH NO O St ON t> st ""N rH O On to On CN. 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CD 15 ■ 11 J J O H CD rH CD CD -H rH O fa - o to o c 5 c"e1 • fa a o O X «rC E CD fa •a oi « c c~ CO CO fa CD CO o » fa X fa CD CD O fa > O - co fa 8 6 I fa J2 3 £ . 3 E PQ i! 1 rt °i 1 i ! I cr. 1 5 l-H V - -c a; s I i i r 5 I s ■ 4 ? 9 >-H -C ■2 CL ~ C3 C — c3 as C > £ S cv a: sa COMPOSITION OF BROAD INCOME GROUPS 57 not the full-time job it was once thought to be, especially when the children are of school age. Other factors underlying the general emergence of women as paid workers are the changing needs of the economy and the relatively high in- crease in the educational attainment of women, which enabled many to qualify for employment. The predominant trend in the occupational distribution of the American labor force has been away from the arduous jobs involving manual labor and toward jobs where physical strength is of minor importance. The growing complexity of the American economy created many jobs that could be handled by women as well as men. The increase in the size of firms and technological changes in methods of production and recordkeeping strengthened the need for manage- ment services and other office functions in order to administer and coordinate ad- vertising, research, sales personnel, and other phases of economic activity which require the services of clerical workers such as bookkeepers, office machine opera- tors, secretaries, etc. Finally the high levels of employment and income and the increase in leisure time strengthened the need for sales workers. All of these factors together created jobs that could be filled by women as well as men. Changes in the characteristics of low-income families. As might be expected, the changes in the composition of low-income families were quite different from those described above for families at all income levels. In general there was a tendency toward the greater inclusion of the less productive and the disadvan- taged groups in the lowest income class. As previously explained, this change is partly related to the use of constant dollars as the basis for classification. An examination of the figures in table II-4 for families with incomes under $3,000 shows that in the early postwar period the aged did not represent a signifi- cantly larger proportion of the low-income group than several other age groups. In 1947, for example, about 20 percent of the low-income families were found in each of the following age groups: 25 to 34, 35 to 44, and 65 years and over. This picture started to change in 1951, when families headed by a person 65 years old or over increased to 24 percent of the total in this income class. The proportion of low-income families in this age group increased regularly during the fifties. It reached a high point of 31 percent in 1957 and remained at that level in 1960 (see figure 1 1-5) . The changes by size of family were also significant, but not as striking as the changes noted for age of the family head. In 1947 about two-fifths of the low- income group were 2-person families, probably elderly couples for the most part. This proportion increased regularly during the next 13 years and in 1960 about one-half of the low-income group were 2-person families. The observed changes in the age of family head and size of family for the low-income group point to a greater inclusion of elderly couples in the bottom income groups. The figures by type of family show an increase, in the bottom-income groups, in the proportion of "broken" families (i.e., families headed by a woman with no husband present in the household) . These families are generally dependent 58 INCOME DISTRIBUTION IN THE UNITED STATES Figure II— 5. — Selected Characteristics of Families With Incomes Under $3,000: I960 and 1951 24.2 Family head 65 years old and over Percent 11.7 13.5 Wife in paid labor force 47.0 51.4 2-person families 23.3 18.1 Female head 47.3 32.8 26.2 17.2 No earners 1951 Family head not employed 1960 Source: Herman P. Miller, Trends in the Income of Families and Persons in the United States, 1947 to 1960, U.S. Bureau of the Census, Technical Paper No. 8, 1963. on the earnings of a relatively unskilled breadwinner or, as is often the case, they live on fixed incomes received from alimony, pensions, or public assistance. It should come as no surprise, therefore, that these families have increased in rela- tive importance among the low-income groups. In 1947 only 16 percent of the families with incomes under $3,000 had a female head as compared with 23 percent in 1960. Despite the general increase in the number of married women in the labor force, there was no change in this respect among low-income families during the period under consideration. About the same proportion (13 percent) of the low-income group were families with working wives in 1947 and in 1960. Many low-income families have the dual handicap of a chief breadwinner whose earnings potential is relatively low and a wife whose earnings potential is also low. Often the wife is too old to work, lacks work experience or training, or has household responsibilities that prevent her from working. In the case of elderly couples, who fonn a major part of the low-income group, the reason is almost self-evident. Both members of the family are either in retirement or semiretirement and tend to live on fixed incomes. There is also a strong tend- ency, however, for men with little schooling (another major segment of the low- income group) to marry women who also have little schooling. Here again neither one of the couple can obtain employment that will provide an adequate level of living. The demographic changes in the composition of the lowest income group were accompanied, as might be expected, by marked changes in employment COMPOSITION OF BROAD INCOME GROUPS 59 rates. The increase in the proportion of families in this group living on fixed incomes and transfer payments is reflected in a sharp rise in the relative number headed by a person who was not in the labor force. In 1948, only 16 percent of the families of the bottom-income group were headed by someone who was not working or looking for work, compared with 41 percent in 1960. The occupational distribution of the heads of low-income families has not changed much. Despite the decline in farming for the population as a whole, farmers constituted about one-fourth of the lowest income group in 1948 and in 1960. The proportion of the low-income farmers today who are older persons and who are not engaged in full-time work is larger than in 1948. Changes in the characteristics of high-income families. The demographic characteristics of families with incomes over $10,000 were much more stable than were those of the lower income groups. There was no significant change during the period 1947 to 1960 in the distribution of high-income families by type or size of family or by color. However, the age distribution of these fam- ilies has changed appreciably. In 1947, about one-third of the families of the high-income group were headed by persons over 55 years of age compared with only one-fourth in 1960. These figures are influenced to a large extent by the fact that incomes above $10,000 are much more common today than they were in 1947 (see figure 1 1-6) . Figure II— 6.— Selected Characteristics of Families With Incomes of $10,000 and Over: I960 and 1951 Percent Percent 38.4 Family head 65 years old and over 10.0 Wife in paid labor force 26.7 24.4 23.4 2-person families Female head 3.7 3.0 No earners 1.0 0.8 Family head not employed 7.0 8.6 1951 1960 Source: Herman P. Miller, Trends in the Income of Families and Persons in the United States: 1947 to 1960, U.S. Bureau of the Census, Technical Paper No. 8, 1963. 60 INCOME DISTRIBUTION IN THE UNITED STATES The greatest changes in the characteristics of the high-income groups were in the increased labor force participation of married women and in the occupa- tional distribution of family heads. The proportion of high-income families with wives in paid employment doubled during the past decade, rising from 19 percent in 1949 to 38 percent in 1960. This striking rise in the tendency for married women to work, particularly those whose husbands are in average and slightly higher than average positions, has had a major impact on many aspects of American life. It is in large measure responsible for the growth of a mass market for what were once regarded as luxury goods and status symbols — dish- washers, air conditioners, suburban homes, two-car families, college training at exclusive schools, etc. Although few significant changes occurred in the occupational distribution of low-income family heads, there have been major changes in the high-income group. The most important among these was a decline in the relative impor- tance of self-employed workers and an increase in salaried professional and managerial workers. In 1948, about two-fifths of the families in the high- income group were headed by businessmen, farmers, or self-employed profes- sionals (largely doctors, dentists, and lawyers). By 1960, the proportion in these occupations dropped to only one-fifth. In contrast, during the same period, the proportion of high-income families headed by salaried professional and managerial workers increased from 23 percent to 42 percent. These figures largely reflect the growing importance of scientists, engineers, teachers, and other salaried professional workers in the American economy. Immediately after World War II the high-income group had more families headed by semiskilled factory workers and craftsmen than by salaried professionals. By 1960, this picture had changed completely. Salaried professionals ranked only second to salaried officials and corporation executives in the top income families, and each of these occupations was numerically more important than self-employed businessmen, who once dominated the group. Changes in the characteristics of unrelated individuals. The relatively full employment conditions during the postwar period and increased Social Security payments have made it possible for many older people, particularly widows, to maintain their own households rather than move in with other relatives. As a result, there has been a significant increase in the proportions of the aged and of women among unrelated individuals (see table II— 5) . In 1949, only about one-fourth of all unrelated individuals were over 65 years of age. By 1954, this proportion increased to one-third and it has remained at that level. Similarly, the proportion of unrelated individuals who were women increased from 54 per- cent in 1949 to 62 percent in 1960. The characteristics of unrelated individuals did not change much in other respects, such as color and work status. Unrelated individuals with incomes under $1,000 (in constant dollars) were much more likely to be older, on the average, in 1960 than in 1949. In addi- tion, a larger proportion in 1960 were women and nonworkers than in 1949. The increase in the proportion of women in the bottom income group is perhaps the most significant change. In 1949, 63 percent of the unrelated individuals COMPOSITION OF BROAD INCOME GROUPS 61 vO O to O rH o « to cm >t 8 onN -£>' o rH r-l r-? rH rH O rH Cn s 5 a" NT a* OmWOiOvOr\ O C- r", O m" ■* O W »o O m r to to O CM O C~- Nf O to ' o-* CM O 0* O vD CM C- O CM t- o sr m o O rH C- CO m rH m O O O CM N0 O rH O H H Hm n O H to O m O £> CM CM r- -j- to O PJ vO O >t m O cm O m vo m H O CM C- O C"i vO O CM > O -4- S> o cm OttH to -J- f- CT~ CM CM CM rH rH in r o cn -sj- -j- vo m O B» o cm m o to O rH rH rH CM (•> O ^ m m C"- O O M3 rH rH rH CM PI O C- (•> o* « -* O rno □ H rH >f to to >r vo c- o CM CM CM rH rH to m vO O P> co -vf O to rH O 9 C O n vo rH O vO ON >* in O m to o cm C m o CM m E>- vO in tf> tO vD 0» CM CM CM rH rH to O O -tf m O E'- er o o o O M3 ■* C ~ OCMtC «0>l->OC^rH CM CM CM CM rH Z O NT 10 rH -St rH M3 O to o » ->* O ci <) n* to >o h ir o CM CM CM CM CM 10 o tH 1 43 to p •H b > 4> n ■P C O ■z. <0 HH char a T3 4) M <-> O a> £> rH « CO AI.T, 2 - 41 > • ra ai to m to o . u u u u u • z - r_ - - ~z H m 9 9 m m c CO hj o -j- -< >t >r a H cm ei --r in vO ca O O O O O 0) +> HJ +> -P -P >t «ma m m m M 4) Ct O .C - -P 3 - a fl B -P 3 Z O E- 4) S A *» HP HF ti (-. 3 ■H S A O "3 > C3 H^> O 62 INCOME DISTRIBUTION IN THE UNITED STATES O -st rH CM vD t> O OHO) O m sr o p- ci O tv O ev vO H - H (J < < X u Q - H — -J ta >~ CO «/f a: < - _ ON CN O cm to sj- t> cr> o O TV C\ CM Tv CM O CO vO vO rjv t> Cvl O H i — I -vl" O O Ol vO P- O 000 O >t' vD O in • • • < << < < < < O ^ T> 2 Z 2 2 Z 2 OfflH i-l OOO r.-v^.^.r-^^^, • • • < < Z Z Z Z Z Z OWH ^^^-^^^ rH oc-frv cm cm tv c- O P 0>* CM* rH o ff>° H TV oSrH rvi rv n h h h IN 3 O M<> >o h no O O Nf Tv rvl O Ov O rH rH %f O tv| vO O" iO H vO _ o >- tu 2 < o H — -J < Q — > Q 2 — _ < w a; 2 D I. I/N I CO c o U I o SO- ON ON o 2 Q IS 9 o 3 to a p 3 8 CO o O vO r-i cm >f o vO O CO TV O O O r> O rH -J- O vf vO Q CM t> O CI v£> noiOvoOH O «0 >t TV rH vO C~- C~- TV t> rH CO & HH>f O r> C- 8* Ov CT> 00 O TV TV 8* O (ft O O 00 O >* CO rH o ^ >o 8* O Ov* O rH TV CO O P- 8" rH -V vO rH t> 00* rH H H O >f vD 8cn1R 5P O O n>t h n o> 8cv \d vd o* t> rH H H >f rH ..«•«» b u u u u u • cd co cu r >i- >r -* to H(vin>}ini u as 0) +3 -r> -P H-> -P >» •sf Tv Tv TV TV TV h rvi n ia vo O -sf 8 vi n O >f vO 8 sis' o >r vo 8* H 00* CO rH vO CM CV to ^ Ov C- O O CO rH rH (VI PI n rl rl rl O Tv TV 8CV vO CO rH rH vO CM Tv rH CM CM rv CM rH O <*\ 8" rH 00* 00 rH Tv rH n-i 88 OOO 8" rH O* 00 rH C- O- 00 -vf vO O vO >f 8§S TV fr, ,H fr\ t>- rH ^5 ^ 2 r-l -H C .- ~ : o ■ hJ ■P C CO CI) cd o i A -C J= H-> H^> -P ^ ^ 3 OOO 2 2 CO 0) Si ■H C rC O > 03 o r5 COMPOSITION OF BROAD INCOME GROUPS 63 ON 1 o m no o o f\ no O rH f- eo n to CM O nO in \0 NO -vt ~st O rH in i-h m on no O HrlNHM o o o'o'S o o rH rH O^OOFIHW o o O NO >J- o n O ON -aj C\J CM Nl- nO to nO o m to to . O Nf 00 CM CM CM CM vO O CM CM to O nO CM CM r-i t> CM O CI ifl o ON O sf vO ^ HNt o> m H O CM CM 0\ CM CM O O CM rH CM CM rH rH o r> cm o o rH m to o cm c-- on sf cm o o o h CM CM CM rH CM O CM to to CM On rH O Nf m O 0\ rH O C- t> CM to O On CM m to O nO m rH i> cm m <> O O O nO CM rH O O CM NO O ON O CM nO O nO CM H CM sf sf ON rH Q O M o 5° a o w E-i CD > • I» 01 (0 10 w o • U f-t f-t fn ^ • cd cd cd cd cd t3 rH CD > >> >> >> a) -P E-i CM CM e f-i o cd z w •H C ra -P -P t( h 3 o o o z z w 64 INCOME DISTRIBUTION IN THE UNITED STATES in the lowest income group were women as compared with 73 percent in 1960. The increase in the representation of women among unrelated individuals was not restricted to the lowest income group, but occurred at all income levels throughout the decade. Since a relatively small proportion of unrelated individuals have incomes over $5,000 (in constant dollars), the sample is small and the numbers are unstable. In general, however, it appears that in 1960, unrelated individuals with incomes over $5,000 included a larger proportion of younger people than at the end of the second world war. It also contained a larger proportion of women and em- ployed persons. Immediately after the war about one-fifth of the unrelated individuals with incomes over $5,000 (in constant dollars) were 65 years old or over as compared with only one-tenth in 1960. During this period the pro- portion of women in this group increased from only about one-fifth in the late forties to nearly two-fifths in 1960. Composition of fifths of families ranked by income: 1947 to 1960 Changes in the characteristics of the lowest fifth. In most respects there was considerably more stability in the composition of families classified by fifths than by constant dollars. This tendency can be seen most clearly in the demographic data for the lowest fifth of families ranked from lowest to highest by income in table II— 6 and figure II— 7. The only significant changes that took place within Figure II —7 . — Selected Characteristics of the Lowest Fifth: I960 and 1951 Percent Percent Family head 65 years old and over 2-person families No earners Source: Herman P. Miller, Trends in the Income of Families and Persons in the United States, 1947 to 1960, U. S. Bureau of the Census, Technical Paper No. 8, 1963. COMPOSITION OF BROAD INCOME GROUPS 65 O m sf m cj\ \0 CM O >0 C 1 - in *C O H rl H H (M O O >£> t> tO CM Sf O Htoto n O CM C sf cm O to m - — .^ci CM ...<<.. 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CU CU CO CD CO CD — c- c -_ c_ CM en st m +> cd C ^ rH ra CO o p CO ^3 73 -P CO CO" TH CO rl rH Cd -P P. P. CO CO iH C rH CO -H CO ■H P. -P 3 -P *H C O rl T3 « fl a co co -p -a -a o cd co co co E-c CO -H Vi Cm CO B co rl CO CO o e CO Cm r2 '3 > c9 O < 66 INCOME DISTRIBUTION IN THE UNITED STATES Nf r O f- -J- rH tO o O m "A O «0 rj O IS C\i 60 Nf r OOrHOOOCMO OMO»N OOsnvO^l-tOtOOsOsfiCMrHF-asvOrH ooo>-"Mr^>fCMCM <<<<<< 2 2 Z Z Z — ^ — i O f> CO >Ti OtO>OrHIl\00'£)H>fH\O^Pl(M«\ O CM \£> O O vO n OCMOCMrHCOCOOrHCMCOCMnMOmr-- 0<-> rH Nf rH OO'AvCC^rH^l-O QOO>nr>>l-CMCM O C\J CO <<<<<< OHM Z Z Z Z Z Z O tO i-H O M3 ^-~.-~vr-^ — • « • <<<;<<< OtO H Z Z Z Z Z Z O t» CM o r> o in Ovo-Nj-no>fO>rnrH>fo>i-mrH>t O-vf^Om-HvOOOO O to CM O OntO^H»0'0>MJ>0\CtOfflW Or--OCMr-rHnO O CM t» • • « <<<<<< Q C- CM 2? 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'. i s ^ rH O aj -P to CO CQ CO CO CO o c c c c c c E-" O O O O O CQ GQ CO CO CO CQ U fH U ^ U U CO ■ CO CU QJ CO p. o, a p. o, a CM c-\ >t ir> vO t> at : Eh CO CO hhti (U (0 CO I g § CO CO 00 CO CO CO OJ o ZH(MI*1 "cd -5 ■p t3 -a O a) cu co £h CO -H t-i r^!£ I ad p -P -H O fci T3 c a a E a a u CO cu 51 o e cu o r?; < - — 70 INCOME DISTRIBUTION IN THE UNITED STATES to 3 o r- o cn co OCOCMrHCMONrHvO O m rH O >t CM 0>CC\IHifl>t <<<;<<<< O CO m C- OONOONrHOCMOOONOOO'-^vOCMrH O m O C"\ OvO(^C^CUO^nvD>J-intOtO — 'IMOH O 0> O H h H ^ (M H rH rH H OrlHS) OO^NrOJOCVt^rH^rHmCNiO^CV N • Cr-irnr^- o£>totxic--r r >m[>>ANfr^r-Oi-i^— -h GO Or-lr* (M H r-l i-l rH rl • ••• ••••••• OtnOvO OOOOC0l^r r \[>^•C~•OlAOr^• O0> O CM rH Nf CM rH rH J* ft- □ u o « <<<<<< Z Z Z Z 2 Z O i*i >f h m h ff> r-wo^cvO'^CMooNr o' CO 0* ON C- 00 ON* 00* nJ* \0* -J* >£* -2- CN o* o* O rH n H H rH OC--tN-OOC0v0r'\00CMOmCM00C--m CO OrH0NCM\0cri\0r~Nt'*0('rA0NOCMOrH O CM rH HlrlH rH oc-c^^o>tcoT\cn ■ o" o* O nJ- cm cm CM ON C\ ON O CM rH C 1 - OrHvfvOOCMC^-mCMrHrHC*- O rH rH O OCMO^rmCM^tt^vOvOmON O ON O CM rH n H H rH — on — 3 O o 3 Ceo CD 3 OrHC"-t>ONf'rHO OCOONCOONCMrHrH O -Nt rH rH O O C""\ >d t~- m n CM (\ m on f- oo^OONCor-CMm-^-^toc--' CM O ON O CM 00> 8 ON O ON O* CM O* t> O O OrHr r >C0<00>n>0CM00 rn l[>'-^rHrr\rH tSJ — rS" O 2 OCMC^OOvO-NfCM 5>f H H H O O rH t-- (O 0> 0> H vO 8* CM O vO* O ON* CO* CM* r-* CO* CT* ("N* vO* rH t> o" rH O ON O CM rH n rH rH rH 01 V ft "5 ^ *« OCNrHnoNcoONC^ Oi-HO^ n o> CO in cm o oncco o^or-o^Nf'XirHiANj-r-ooN'-^o^-Nr 8 CM rH "A QCO*OC--rHv£>^CMrr 1 f.D n p- co co o (Ji <*> CM rH rH rH O CO vO vO OrH00C"NC0CMCMOC--«N000N —00 CM O 8-j O -J OrHCMCOCMCOiAr^rriC^ONNfiioOrH ON OCIHH CN rH CM rH rH OOOH9>n«\(M o co cm .-h r- -J- cm m § on 1-1 P\ ci c\j cm ° c\1 O oo t~- m 8 CM O O O\tOsf>tCMt0>*CMCM\00^H\t'^0' 8 on cm r-* cm rH >* >o >r co* oo* 01 o'h'2o CM H H -sf rH CM 2 09 53 OCMOOD-UNvOCMrH 8-J- -J- 00 f\ m CM rH *} r-l r* rl O CM CO ^OOiO>JiO O 00 rH O xtOiCOO'O OO H CM H H CM O O UN \0 8rH rH ON OrM(MO*0>HCOneo<^CMOH'flCM\0 o oo rH ^ >••••••• 4) •a % c ;**"'*:! u 01 •• o ^ rH •3 o rH O .e t> u :::::::: § T3 5 :::::::: B a) ....... u .h rH ^ b0 01 Q 01 k K o o . rH C Sh eg 4> • C g C G C at h • ai a) a) ai ai 3 *H rH rH rH rH rH rH Z JSiH-H-H-H-H-H o C £, & g a 000000 o Z H CM r> -J «MO 5§ O £h - ¥• C 01 01 o o 0) - ^ 000 Z Z CO 5^ I a o - a co e c c M3H COMPOSITION OF BROAD INCOME GROUPS 71 this group occurred during the immediate postwar years, 1947 to 1950, when living arrangements were still unsettled because of rapid demobilization of mil- lions of servicemen and also because of the severe housing shortage. These factors, combined with relatively low Social Security payments, caused many widows and elderly couples to live with married children where they were classi- fied as relatives of the head rather than as family heads. As a result, a relatively small proportion (about one-fourth) of the low-income families were headed by persons over 65 years of age. By 1951, when the housing shortage was con- siderably alleviated and Social Security payments to retired workers were in- creased considerably, many aged parents found it possible to live apart from their children. However, since their incomes were quite low, these new families increased as a proportion of the total in the bottom income group. By 1951, families headed by a person 65 years old or over increased from about 26 percent during 1947-1950, to 31 percent of the total and they remained at that level throughout the decade. This tendency for elderly couples to live apart from their children is also reflected in the fact that the proportion of two-person families in the bottom fifth rose from 47 percent during 1947-1950 to about 52 percent in 1951, and it remained at that level for most of this period. A similar process appears to be involved in families with a female head. During 1947— 1949, about 18 percent of all families in the lowest fifth had a female head. The proportion rose to 23 percent in 1950 and it stayed at about that level for the remainder of the period. Other demographic characteristics of the families in the lowest income group, such as color, residence, and number of children under 18 years old, did not change significantly during the entire postwar period. However, there were some changes in economic characteristics, which in some respects appear to be related to the splitting up of families described above. In 1948, only 22 percent of the families in the lowest fifth were headed by a person who was not in the labor force. This proportion rose^to 31 percent in 1949, 36 percent in 1950, and it averaged about 42 percent during 1957-1960. The relatively small proportion of family heads not in the labor force in 1948-1949 could be related to the fact that many elderly persons and widows do not appear in the statistics as family heads during those years. Once these groups established their own homes, the proportion of heads not in the labor force increased because older men and women are less likely to work than are the heads of younger families. Aside from a slight drop in the relative importance of farmers, there were no significant changes in the occupational composition of the lowest fifth of the families during the postwar years. Farmers were the single most important group within the lowest fifth, accounting for 31 percent of the total in 1950 and a somewhat smaller proportion in 1960. Operatives and craftsmen accounted for about one-fourth of the total in 1950 and 1960 and laborers accounted for somewhat less than one-fifth of the total. The stability in the composition of the lowest 20 percent of the families stands in marked contrast to the previously described changes in the composition of families having incomes under $3,000 (in constant dollars) . The latter measure 72 INCOME DISTRIBUTION IN THE UNITED STATES creates the impression that the disadvantaged groups — the aged, broken fam- ilies, and the unskilled — formed a constantly growing proportion of low-income families during the fifties. The classification by fifths leaves the entirely dif- ferent impression that the lower income families had about the same characteris- tics in 1960 as they had had ten years earlier. If low income is defined as less than $3,000, then in 1947, when the average income for all families was about $4,000 (in constant dollars), many families near the middle of the distribution were included in the low-income group. However, in 1960, when the average income was about $5,500, the low-income group was more highly concentrated near the bottom of the distribution. For this reason it is difficult to interpret the meaning of the changes in terms of constant dollars. In contrast, the sig- nificance of the findings with respect to the lowest fifth is much clearer. In all years the families in the lowest fifth have the same relative position in the dis- tribution. The figures suggest that within the lowest fifth of the distribution, disadvantaged groups have not lost ground relative to others. They appear to have received their proportionate share of the increase in real incomes during the past decade. Changes in the characteristics of the top 20 percent and the top 5 percent. Two different measures are used to describe changes in the characteristics of the higher income families — the top 20 percent and the top 5 percent of the income distribution. In 1960, these families had incomes over $9,000 and $14,000, respectively. The dollar limits for other years are shown in appendix B. Focusing first on the highest 20 percent, we find few significant changes in their demographic characteristics (see table II— 6) . Some adjustments in family composition took place immediately after World War II. However, during the fifties, there was no significant change in the distribution by age, sex, or color of head or by size of family or number of children. The proportion of all high-income families has shown a distinct tendency to rise in the Western States during recent years. In 1953, about *1 7 percent lived in this region; by 1958, the proportion rose to 20 percent and in 1960 it was 25 percent. The employment rate for married women increased for all of the quintiles shown. For the top 20 percent, this rate rose from 27 percent in 1949-1950 to 39 percent in 1960. The change in the employment rate for this group was greater than for families lower in the income distribution. The change in the occupational distribution of employed heads of households for the highest 20 percent was striking. In 1948, the self-employed comprised the single largest group among high-income families, accounting for 26 percent of the total. By 1960, this proportion had dropped to 15 percent. In contrast, the proportion of salaried professional and managerial workers had increased. In 1948, these two occupation groups accounted for 20 percent of the total as compared with 37 percent in 1960. Most of the conclusions based on the top 20 percent of the families apply to the top 5 percent as well (see figure 1 1-8) . The number of cases is, of course, much smaller for the top 5 percent and the figures are subject to relatively large COMPOSITION OF BROAD INCOME GROUPS 73 Figure II— 8.— Selected Characteristics of the Top Five Percent: I960 and 1951 Percent Family head 65 years old and over 24.6 23.2 2-person families Percent Wife in paid labor force 3.4 1.9 Female head I . "^^m 1.1 1.2 No earners — 1951 Source: Herman P. Miller, Trends in the Income of Families and Persons in the United Stafes, 1947 to 1960, U.S. Bureau of the Census, Technical Paper No. 8, 1963. variations due to sampling. Nevertheless, the general trends exhibited by the data are consistent with those observed for the top 20 percent. The only major difference between the two sets of data is that there was no significant increase in the employment rates for married women among the top 5 percent. In 1951, about 25 percent of the wives were in the labor force as compared with 28 percent in 1960. These figures suggest that the top 5 percent of the families were able to retain their relative income position without increas- ing the employment of wives, whereas families just below them on the income scale (i.e., those in the 80-95 percentiles) in many cases would have dropped to relatively lower income levels without the additional income provided by a work- ing wife. NOTES 1 Joint Committee on the Economic Report, Low-Income Families and Economic Sta- bility, 81st Cong., 2d sess., 1949, p. 2. 2 Selma F. Goldsmith, "Low-Income Families and Measures of Income Inequality" (Mimeograph). Paper presented at December 1961 meetings of the Catholic Economic Association, p. 9. 3 John K. Galbraith, The Affluent Society, Houghton Mifflin Co., Boston, 1958, p. 323. 4 Dorothy S. Brady, "Research on the Size Distribution of Income," Studies in Income and Wealth, Vol. 13, National Bureau of Economic Research, 1951, p. 30. 6 John K. Galbraith, op. cit., p. 3. 6 Ibid., p. 323. 7 Ibid., pp. 323, 324. Family head not employed 1960 74 INCOME DISTRIBUTION IN THE UNITED STATES NOTES— Continued 8 Leon H. Keyserling, Poverty and Deprivation in the U.S., Conference on Economic Progress, 1962, p. 8. 9 Leon H. Keyserling, Progress or Poverty, Conference on Economic Progress, 1964. 10 Robert J. Lampman, The Low-Income Population and Economic Growth, Joint Eco- nomic Committee, 86th Cong., 1st sess., December 1959, p. 4. n Ibid., p. 34. 13 Ibid., p. 4. 13 Statement of Dorothy S. Brady at Hearings Before Subcomittee on Low-Income Families. Joint Committee on the Economic Report, 81st Cong., 1st sess., December 1949, p. 475. u More detailed levels for both families and individuals are shown in U.S. Bureau of the Census, Herman P. Miller, Trends in the Income of Families and Persons in the United States: 1947 to 1960, Technical Paper No. 8. 15 Leon H. Keyserling, op. cit., pp. 19, 20. 16 Unless otherwise specified, all census data are in terms of total money incomes and not family personal income (including nonmoney income) which is the concept used by the Office of Business Economics. 17 It was not possible to exclude unrelated individuals 14 to 24 years old from the un- published tabulation which underlies the data in figure II— 2. 18 U.S. Bureau of the Census, Current Population Reports — Consumer Income, Series P-60, No. 37, table 15. CHAPTER III WAGE AND SALARY TRENDS FOR MAJOR OCCUPATION GROUPS Introduction In this chapter, trends in income differentials among occupations are con- sidered in relation to overall changes in income distribution. Occupations will therefore be viewed as the fundamental building blocks which, when aggregated, are largely responsible for the shape of the overall income curve ; and changes in the total will be related to changes in the component parts. There is, of course, an auxiliary interest — more or less sociological — in iden- tifying the high-paying and low-paying occupations, and those which have had greater than average gains in income, as well as those which have lagged behind. This type of analysis calls for a somewhat different orientation toward specific occupations, and would involve detailed study of the requirements of specific jobs, the demographic characteristics of persons employed in these jobs, and the relation of the jobs to each other and to the changing needs of the economy. Such a level of detail, while appropriate for an analysis of labor force behavior or occupational trends, goes far beyond the scope of the present study. Between 1939 and 1949, aggregate wages and salaries tripled, increasing from $46 billion to $134 billion; by 1959, the amount nearly doubled again, rising to $259 billion. This very large increase over the 20-year period was accompanied by a marked change in the distribution by income levels. In 1939 the average wage earner received about $800 during the entire year. By 1949 the figure rose to $2,000, and by 1959, to $3,100 (table III— 1) . In 1939, $5,000 represented the top of the scale for the wage earner, and only 1 percent of the workers earned this much or more. By 1949 the proportion of workers earning $5,000 or more rose to 4 percent, and by 1959, to 26 percent. Although some of the rise represented merely inflation of dollar values, even in real terms there was a very substantial increase in the proportion of workers with wages and salaries over $5,000. For men alone — typically the main wage earners in their families and likely to be full-time workers — the changes were even more striking. Changes in the level of wage or salary income and in the frequency distribu- tion of the earners were accompanied by a marked change in the dispersion (or inequality) in the distribution of this type of income. 75 76 INCOME DISTRIBUTION IN THE UNITED STATES Table III— 1. — Wage or Salary Income of Persons, by Sex: 1959, 1949, and 1939 Wage or salary income Both sexes Male Female 1939 1959 1949 1939 i::.: i:c. 100.0 ::: .: 100. 100.0 100. C 100.0 $1 to $999 25.1 27.8 60.0 16.0 19.6 52.8 40.3 44.4 79.0 $1,000 to $1,999 11.7 21.9 29.2 3.6 18.1 33.4 17.0 29.6 18.1 $2,000 to $2,499 6.6 13.2 5.3 4.9 12.9 6.8 9.3 13.9 1.6 $2,500 to $2,999 5.5 11.0 2.0 4.6 13.3 2.6 7.1 6.4 0.5 $3,000 to $4, 999 25.4 22.1 2.4 27.9 30.1 3.1 21.4 5.7 0.6 25.7 4.1 1.0 38.1 6.1 1.4 5.0 0.1 0.1 $3,084 $2,016 $789 $4,209 $2,476 $939 $1,527 $1,208 $555 Source: U.S. Bureau of the Census, Current Population Reports— Consumer Income, Series P-60, Nos. 7, 11, and 35. Table 1 1 1-2, which shows the distribution of aggregate wage or salary income by quintiles during 1939-1959, makes it quite evident that marked changes in the distribution of aggregate wages and salaries took place during the war years. Between 1939 and 1945 the share received by the highest fifth decreased from 49 percent to 44 percent. In contrast, the entire postwar period was marked by stability in the distribution of wages. The greatest difference in the share received by the top fifth between any two years in the entire period 1945 to 1959 does not exceed 2 percentage points. Conclusions regarding the stability of income distribution during the postwar period, based on the data for wages, are identical with those based on total money income shown in table III— 3. There- fore, we can see in the data for persons the same general picture previously discerned in the data for families — a decrease in income concentration during the expansion of economic activity during World War II, and stability during the postwar period. The question that now remains is to what extent the pattern of change can be explained by wage movements within occupation groups. Wage differentials by skill (BLS data) Most analyses of changes in wage levels, particularly those involving trends in differentials for skilled and unskilled workers, are based on the hourly earnings data collected by the Bureau of Labor Statistics. 1 The BLS data, in contrast to the figures on annual earnings collected in the decennial censuses and yearly household surveys have an understandable appeal for several reasons: they define occupations more accurately and more specifically; and the hourly earnings fig- ures separate differences due to wage rate variations from differences due to variations in extent of employment. The Census data, in contrast to the BLS data have the disadvantage of representing employment during a single week, which, of course, often may be quite different from usual or major employment. On the other hand, the Census figures show various demographic factors that might be associated with wage differentials, and the information on annual earn- ings which they provide is a better measure of financial returns associated with different kinds of work. Each set of figures, therefore, has its uses, and each provides a somewhat different picture of the changing relationship between employment and earnings. TRENDS BY MAJOR OCCUPATION 77 Table III— 2.— Percent of Aggregate Wage or Salary Income Received by Each Fifth of Wage or Salary Recipients Ranked by Income, by Sex, for Selected Years, 1939 to I960 Year and sex Total Lowest fifth Second fifth Middle fifth Fourth fifth Highest fifth BOTH SEXES 100.0 1.8 7.8 17 ?ft ft 4ft ft 100.0 1.9 8.1 17.4 26.8 45.9 100.0 1.8 7.7 16.8 25.8 47.9 100 !o 2a 8i3 17!2 25.9 46i5 1956 100.0 2.1 8.4 17.3 25.9 46.3 100.0 2.2 8.7 17.9 26.2 45.0 100.0 2.5 9.2 18.0 25.3 45.0 100.0 2.6 9.7 18.0 25.3 44.3 100.0 3.0 10. 6 18.9 25 9 41.6 100.0 2.3 9.7 18.3 25.7 44.0 100.0 2.6 10.1 18.7 26.2 42.4 J.UU.U 10. 2 ±0,6 25.5 42.8 100.0 2.9 10.3 17.8 24.7 44.3 1945 100.0 2.9 10.1 17.4 25.7 43.9 100.0 3.4 8.4 15.0 23.9 49.3 MA TT? 100.0 2.5 10.9 18.9 25.2 42.5 1959 100.0 2.7 11.4 19.0 25.5 41.5 1958 100.0 2.4 10.6 18.1 24.0 44.8 100.0 2.8 11.5 18.4 24.5 42.8 1956 XUU « U "5 n XX • 7 i ft a AO 1 100.0 3.2 11.9 19.1 25.0 40.9 ^ QKJ 100.0 3.4 12.0 18.7 24.3 41.6 100.0 3.6 12.5 18.8 24.0 41.1 1951 100.0 4.9 13.1 19.3 24.4 38.3 1950 100.0 3.5 12.5 18.7 24.3 41.0 1Q/Q 100.0 3.6 12.3 19.2 24.8 40.1 1 CM Q l nn o J.UU.U -2 Q -J 1 o 7 -C . 1 i q n 17 . u J? , / 1 Q/ n 100.0 4.5 11.9 17.9 26.4 39.3 1945. . 100.0 3.8 12.4 18.5 25.4 39.9 1939 100.0 3.5 9.0 15.5 23.3 48.7 r KM A 1 ,K 1960 100.0 2.4 5.9 16.1 28.2 47.3 1959 100.0 2.5 5.7 16.2 28.0 47.6 1958 100.0 2.6 5.5 16.0 28.2 47.7 1957 100.0 2.7 6.4 16.4 28.2 46.4 1956 100.0 2.8 6.3 15.9 28.5 46.5 1955 100.0 2.9 6.5 16.1 27.8 46.7 1954 100.0 2.9 7.2 17.0 28.0 44.9 1953 100.0 3.0 7.5 17.6 28.2 43.8 1951 100.0 3.3 7.8 18.3 27.7 42.9 1950 100.0 2.0 7.5 17.6 29.5 43.4 1949 100.0 2.2 8.0 18.3 28.6 42.9 1948 100.0 3.0 8.5 18.4 28.6 41.5 1947 100.0 2.8 8.7 18.0 26.7 43.8 1945 100.0 4.5 10.3 18.5 27.0 39.7 1939 100.0 3.0 9.2 16.8 24.5 46.5 Source: Data for 1953-60 from unpublished tabulations used to prepare comparable distribution by occupation and industry groups which appear in Herman P. Miller, Trends in the Income of Families and Persons in the United States, 1947 to 1960, U.S. Bureau of the Census, Technical Paper No. 8, 1963; and for 1939-51 from Herman P. Miller, Income of the American People, Wiley, 1955, p. 104. Table 111-4 shows BLS fi gures which are often cited in analyses of long-term trends in earnings differentials between skilled and unskilled workers. These figures are not generally shown together in a single table because the data for 1907 to 1947 were compiled differently from those shown for later years. How- ever, since there has been some tendency for experts in the field, including BLS officials, to treat the data as if they were roughly comparable, they have been assembled in the form shown in table IH-4. 2 These figures suggest a progressive narrowing of wage differentials between skilled and unskilled workers during 78 INCOME DISTRIBUTION IN THE UNITED STATES Table III -3.— Percent of Aggregate Total Money Income Received by Each Fifth of Income Recipients Ranked by Income, by Sex, for Selected Years, 1944 to I960 Year and sex Total Lowest Second niucLLe r OUT ul Highest 1 11 UQ i li un 1 11 un 1 11 tn fifth BOTH SEXES 1960 100.0 2.0 6.6 15.1 25.9 50.4 100.0 2.1 6.7 15.2 26.0 50.1 1958 100.0 2.1 7.0 15.6 26.1 49.3 1957 100.0 2.5 8.4 16.9 25.8 46.4 1956 100.0 2.2 7.2 15.9 25.6 49.2 1955 100.0 2.3 7.2 15.7 25.4 49.4 1954. JLUU . U 1 ^ St c.j . u / Q 1 1953 100.0 2.4 7.9 16.3 25.3 48.0 1951 100.0 2.5 8.4 16.7 24.7 47.7 1950 100.0 2.3 7.9 16.4 24.3 49.1 1949 i nn n C.J . U 1 • 1 1948 100.0 2.9 8.7 16.6 24.2 47.6 1947 100.0 3.0 8.9 16.2 23.4 48.5 1945 100.0 3.1 9.0 16.0 24.5 47.4 1944 100.0 2.6 8.5 15.6 24.2 49.1 MALE 1960 100.0 2.6 9.5 17.3 24.7 45.9 1 Q'iQ 100.0 2.8 9.8 17.6 24.8 45.0 1953 100.0 2.8 9.8 17.9 25.0 44.5 1957 100.0 2.9 10.0 18.0 24.7 44.5 1956 100.0 2.9 10.2 18.0 24.4 44.4 1955 100.0 3.0 10.1 . 17.7 24.7 44.6 1954 100.0 3.0 10 17. 5 23 7 45 6 1953 ioo!o 3!o 10^6 17!9 23!9 44^3 1951 100.0 3.5 11.3 17.9 23.4 43.9 1950 100.0 3.0 10.7 17.2 23.4 45.7 1949 100 3 ? 10 2 17 8 24 1 44 7 1945 looio 3.5 lo!7 17 '.4 23!l 45.3 1947 100.0 3.7 10.6 16.7 22.7 46.3 1945 100.0 4.1 9.5 17.0 24.1 45.3 1944 100.0 3.4 10.0 17.2 23.8 45.6 FEMALE 1960 100.0 2.6 6.5 13.5 26.5 51.0 100.0 2.7 6.4 13.4 26.1 51.4 1958 100.0 2.8 6.4 13.5 26.3 50.9 1957 100.0 2.7 7.7 14.5 25.7 49.4 1956 100.0 2.9 6.7 13.8 26.5 50.1 1955 100.0 3.0 6.8 13.7 26.2 50.3 1954 100.0 3.1 7.3 14.4 26.6 48.3 1953 100.0 3.1 7.3 14.5 26.5 48.4 1951 100.0 3.5 7.3 14.6 27.5 47.1 1950 100.0 3.7 6.9 14.6 27.3 47.5 1949 100.0 3.8 7.4 15.3 26.7 46.8 1948 100.0 3.9 8.2 15.7 26.5 45.7 1947 100.0 3.8 7.9 15.9 25.3 47.1 1945 100.0 4.7 9.1 16.4 26.1 43.7 1944 100.0 4.3 8.4 15.4 24.3 47.6 Source: Data for 1953-60 from unpublished tabulations used to prepare comparable distribution by occupation and industry groups which appear in Herman P. Miller, Trends in the Income of Families and Persons in the United States, 1947 to 1960, U.S. Bureau of the Census, Technical Paper No. 8, 1963; and for 1944-51 from Herman P. Miller, Income oj the American People, Wiley, 1955, p. 103. the first 50 years of this century. In 1907, the median earnings of skilled workers in manufacturing industries were about twice those of unskilled workers. By the end of World War I, median earnings of skilled workers were only 75 percent greater, and by the end of World War II, only about 55 percent greater. Thus, during a 40-year period, the differential between skilled and unskilled workers was reduced by about 50 percent, or by an average of about 1 percent per year. The narrowing of differentials appears not only to have continued into the early postwar period, but to have accelerated somewhat. Between 1947 and TRENDS BY MAJOR OCCUPATION 79 Table III— 4.— BLS Data Relating to Earnings of Skilled and Unskilled Occupations in Manufacturing Industries, for Selected Periods, 1907 to 1956 Period Earnings ratio f skilled labor ^ Period Earnings ratio { skilled labor ^ \iinskilled labor/ Vyjiskilled labor/ 138 137 155 165 180 175 207 Source: Data for 1952-53 and 1955-56 from BLS Bulletin No. 1188, Wages and Related Benefits, p. 35. Based on a comparison of 12 jobs in manufacturing establishments in 15 areas that were included in the occupational wage surveys conducted in 1953 and 1956. The figures represent the ratio between the hourly earnings of skilled maintenance workers and male janitors in manufacturing establishments. Data for 1907-47 from Harry Ober," Occupational Wage Differentials, 1907-47," Monthly Labor Review, August 1948. For each period, representative unskilled and skilled occupations were selected for each manufacturing industry for which data were available. Average earnings for each unskilled job were used in constructing a relative for the corresponding skilled occupation. These relatives were then arrayed and the medians determined. 1953, the differential dropped from 55 percent to 37 percent, or at the rate of about 3 percent per year; between 1953 and 1956, however, there was no further apparent reduction. On the basis of this evidence, BLS has concluded that: The long-term trend toward narrowing of skill differentials has leveled off temporarily, at least, with skilled manual workers, office workers, and unskilled workers maintaining their relative pay position in the past three years. 3 Some caution should be exercised in interpreting trends during the fifties. Unlike surveys made during the earlier years (when a representative selection of unskilled jobs was used) , the more recent surveys express differentials in terms of the hourly earnings received by janitors. If the basis for comparison had been some other unskilled occupation, or group of occupations, different trends might have been obtained. A somewhat different view of postwar trends in earnings differentials be- tween skilled and unskilled workers is had from a BLS study of hourly earnings of production workers in nonelectrical machinery manufacturing. This industry includes establishments engaged in such diverse activities as the production of ball and roller bearings; construction, mining, and material handling machinery and equipment; metal working machinery and equipment; and electronic com- puting machines. The BLS study presents figures on average straight-time hourly earnings for production workers in specified occupations at various times during the postwar years; the averages for various periods are shown in the pub- lished reports. A summary, representing the percent change for various periods between 1945 and 1961, is presented in table III— 5 and figure III— 1 for all production workers, laborers, and tool and die makers. These data, particularly the data in figure III— 1 , suggest a continued narrowing of wage differentials between skilled and unskilled workers during the postwar period. Between 1945 and 1961 the average hourly earnings of all production workers in machinery manufacturing increased by 142 percent; the earnings of laborers, however, in- creased by 170 percent, whereas those of tool and die makers rose by only 127 percent. 80 INCOME DISTRIBUTION IN THE UNITED STATES Table III— 5 . — Percent Increase in Average Straight -Time Hourly Earnings of All Production Workers in Machinery Manufacturing, by Selected Occupations, for Selected Periods, 1945 to 1961 Period All production workers Laborers , material handling Tool and die makers (other than jobbing) Jan. 1945 to Mar. -May 1961 142.4 169.7 126.7 Jan. 1955 to Jan. 1956 4.8 3.6 4.9 Jan. 1956 to Jan. 1958 10.2 12.6 9.8 Jan. 1958 to Jan. 1959 3.3 4.7 4.1 Jan. 1959 to Jan. 1960 4.1 3.4 3.9 Jan. 1960 to Mar.- -May 1961 3.1 4.0 3.6 Source: BLS Bulletin No. 1309, Industry Wage Survey, Machinery Manufacturing, March-May 1961, table 3. Wage differentials among major occupation groups, 1939 to 1960 Between the years 1939 and 1960, American workers enjoyed an unparalleled period of full employment and rising incomes. There were, to be sure, some years of recession when average earnings did not rise significantly, or even dropped slightly, but for the period as a whole, most occupations experienced continuous growth in earnings. This fact is brought out very clearly in table III— 6, which shows median wages and salaries for each year for males and females by occupation groups. Though all occupations showed substantial gains over the entire period, the increases were by no means uniform. Among men, for whom the figures are most meaningful because they tend to represent the earnings of full-time workers responsible for supporting a family, the medians for all occupations either tripled or quadrupled. Farm laborers had the smallest absolute and relative gains and these were entirely concentrated in the period during or immediately after World War II. Farm labor is the only occupation in which since 1950 incomes have declined, on the average. Among women, the gains between 1939 and 1960 were lower and more vari- able than for men, and also — because of the intermittent employment of most women — somewhat more difficult to interpret. Median wages and salaries of private household workers did not quite double; wages of saleswomen barely doubled; managerial workers and clerical workers tripled their wages, on the average; and the greatest relative gains were attained by professional workers and operatives. On closer examination, table 1 1 1-6 reveals significant patterns with regard to changes in income distribution. Among men, the figures show that between 1939 and 1950, when incomes moved strongly toward equalization, men in the lower paid jobs made the greatest relative gains. For example, median wages and salaries in the lowest paid occupations — farm laborers and foremen — in- creased by over 200 percent; and medians for the three next lowest paid groups of jobs — nonfarm laborers, service workers, and operatives — increased by 175 percent. Craftsmen, whose annual earnings rank closer to the middle range, had increases of 160 percent; and the highest paid workers — those in profes- sional and managerial jobs — had the smallest increases, about 100 percent. In TRENDS BY MAJOR OCCUPATION 81 Figure III— 1 . — Percent Increase in Average Straight-Time Hourly Earnings for All Production Workers and Two Selected Occupations in Machinery Industries, January 1945 to Specified Dates Percent Percent Oct. Nov. Nov. Nov. Jan. Dec. Jan. Jan. Jan. Jan. Jan. Jan. Jan. Apr. 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 Source: BLS Bulletin No. 1309, Industry Wage Survey, Machinery Manufacturing, March-May 1961, p. 6. 82 INCOME DISTRIBUTION IN THE UNITED STATES _ H — H h -3 3 be CO U -P C 0) D, E -r-i (h 0) fi S O o co CO 01 c ►3 3 CO B I a o c b. O as as a u *■ 5 CJ X — '.: ~ r« 3 O a. o 3 a dl T3 co > ■ u •h T3 t< 5) •p c -a x as as c u U nH O X 3 ■a co ai u ■a u v C "O X act. ^ o •X 3 — -a - v fc. C -O X! ii 9 c h rH -H O O X 3 » co 03 rH U CO I CO o u a ■ •»-* t-i O c»h M o P. «* CO —I « • c t_ -a — i o as <~ c u x £ o d a u as » C rH O CO a •a co c -a .* ■ c o CO c ■p c c CO On Nf vD en in £>. n co \0 ^ to UN CO Nf t> vO CO vO Nf O O f"1 m O n} c- un [> n-vfCMHCo vO co m o cn co rH CM CM O CM o o m rH t> n t> rH rH O 0> CO 0> vO t> Nf rH O CM CM CM CM rH 1*1 CO O O CM rH On vO UN Nf On t> <0 0>MMOO> «r> O C-- t> CM vO On CM rH Nf CO CO O toto o> o> n I rH CO rH C~- U3 co vo m t> ua Nf UN, UN. 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I ua ua Ua UN UN UN CM «r> Q ON CO t> vO UN \D UN UN UN UN UN O C7^ C7^ s On CT* Nf rr, CM rH O ON IA UN UN UN m rN O* On 0^ O^ CT* c •r< O O O ua un ua piii COOiov 0) UN fr\ rN CJ Ov o> O dHHH « Oh o o> co t> ua un o^ vO UN UN, UN UN UN. r\ on o^ o^ o^ on o* cy> s 8 c o HOC fa- .o CO o pa pa pa pa co oa m pa pa pa t> pa pa pa pa pa pa st J* _2 c C/l be d c o -a c u a >i X > CO M M CU -H 3 a> o u o CO 3 P. o t> m o rH m >t n to >o in n cm to m st m c> m cm cm o o o St CM CM CM rH rH rltMHOICO>f co rH c\ m o o t> rH st t> cr> m m o st CM O CT> O t> ■P O M (0 JS cu > 01 M U 3 Oh o £1 c\ CM t> o *o CM t> O \0 m to O s^ m st st st m m st c\ t> to ^0 CI vO rH O CT> — - Ct> ci st \D to t> pa rH rH rH Ct> tO Cl TJ CO CO 'J > tH 'O rl HI +-> c -a M as erj C U M .HO cu 3 p. o to t> m O O to D CM io ^ t> ci ci st m oo n h to ClcMOHrlO COOOOvOm t> to o Sf t> O rH C| O *D m rH CM OS CM t> rH -J" rH n CO St O O tS \0 vO st O CM CM CM CM CM CM — CU 3 u u ° O TJ •5 o - c C tu ■~ -a co c — O I "> ^ _ u ~ — ' CU a c So £ 'S 01 C TJ CO E a> ii •< co e -a m cu n c *o ^ cu rH ^5 o st o to st m o £^ st ci n ^ vo n cu h ririOHrio to o ci o o - m cm st c, to o ca st sf n n cm o — - 1> U — > 2 ffl TJ to O (I rl •H TJ !h CU M G TJ r* cu a) e m rH -HO O 3 os m ci cm o o c^ m st- o cy> a-* o oi oi «no in stsi-cMrHoa* to O O t> St *0 CM f- st *0 t> st m St rH rH rH CM vO c\ to t> m m cm to to to st ^0 t> in st Ci CM rH o o CM CM CM CM CM 3 (« o c; C o J2 - co ■> E CO rH I CO M m a) O h a) oi ^h U o Vi ciO o p. +» cd *h cu c t-i -a -H o a) Cm C U X Z O -m OQstOOCOO inmClrHOrH — mt>^30rH CM CM CM CM rH ci st rH o m ^to t> C| £> O CM CD rH rH o o to m ' CM V be c« c B s u -a c «1 V s •- ciS 3 be O a) -o co ■HO Q) rH CO -H T3 m CU - C -O Mt ct) C ■H O CO c CU S Cm O o cu M -P tO m rH >OHO to io n C| C| CI C\ C| CM «r» 5 O cm cn o — O O vO st CM O C| CM CM CM CM rH rH 00 t> CM rH CM st m o o o t> to to st rH m o t> Cl Cl rH to vo m CM 01 X CU Cm CO o -P c C CO cu O O to C- m vo m in >n m m CT^ OS OS (J* C^ Ct* st Cl CM rH O O m in m m m ci OS OS s O OS OS CO u cu X, U o 9J E tH rH rH cu • CO • as - cu • -o ' r o •So' o* O u m 1 -P 1 i M c o ON a) cu m c Cl cu o o r >H rH rH rH rH o O to m o \Q IA 1A IA IA lA n (T» CT» O 0^ O CT» r-t i-i r-i r-i r-i r-i 84 INCOME DISTRIBUTION IN THE UNITED STATES other words, during this period of equalization in the overall income curve, there was also a reduction in the differentials between high-paid and low-paid occupations. There has been marked stability in the distribution of income since 1950, with changes in income gains for the various occupation groups showing a pattern distinctly different from that of the earlier period. Although the higher paid jobs have made slightly greater relative gains than the lower paid, the differences have not been great enough to suggest a change in income distribu- tion. Thus the highest paid workers — those in professional and managerial jobs — had increases of about 65 percent; craftsmen and clerical workers, who rank next in terms of annual wages, had gains of 60 percent ; and salesmen and operatives had gains of somewhat more than 50 percent. Workers in the lowest paid groups of jobs — service workers and nonfarm laborers — had increases of only about 40 percent, and as previously stated, wages of farm laborers declined. This evidence suggests a consistency in the patterns of change in annual wages among occupations and in the overall income curve. An examination of the changes since 1950 in the distribution of wages and salaries within each major occupation group will help determine whether these changes also correspond to those in the overall income curve. It should be noted that corroborative evidence from the 1950 and 1960 Cen- suses suggests that trends in wage differentials among occupation groups for the country as a whole appear in most cases at the State level also. Table III— 7 presents the percent increase in median income between 1939 and 1949 and 1949 and 1959 for males in selected occupation groups, by States. The purpose of this table is to ascertain whether the trends in earnings differentials for the Nation as a whole occurred more or less uniformly throughout the country or whether there were wide variations in the patterns observed for the States, with the overall trend largely representing a weighted average of widely differing trends. Although the same income concept could not be used for each year, it is unlikely that this shortcoming seriously affects most of the comparisons shown — particularly those for craftsmen, operatives, and nonfarm laborers. The medians for 1939 are based on men reporting $100 or more of wage or salary income in that year; the $0 to $99 group was excluded because there was no way to sep- arate those without wages (and who may have had some self-employment income) from those with wages of $1 to $99. The figures for 1949 are based on men reporting $1 or more of total money income. In the three occupation groups for which 1939 to 1949 comparisons are shown, the differences between median wages and salaries and median total money income are quite small, since men in these occupation groups are predominantly wage or salary workers without other major sources of earnings or income. At the national level, in 1949 the difference between median wages and salaries and median total money income for these groups amounted to only a few dollars. 4 TRENDS BY MAJOR OCCUPATION Q 7 ryi < u. - < n (4 L* CQ dec H m 0> - en rH o -p T3 m -H C 0) -H J< CO I* 14 O U TJ 3 - CU C - m co CU C *U S-t e CU C CU co a fl P «) h 14 l< O a) O -a 5 t< =_ c o 3 m s-. -a a) O C fc. .a to co t- ^ as CU Cm T3 M ■H C !) -H >3 B M U u o 1) TJ 3 a c o o CU C T3 (_ £ CU G CU 01 5 H ^< Cm m O CO O 13 S ^ t-, c o 3 9> O n TJ ■h m C et cp t! co S3 Jfi co to to CU en O t> lA O CA t>- Q rH H O "St H d (M CM CM (A CM CM CM rH CA rH c- m to *C t> o rH rH r-( rH CM •A O t> O CM »a >t. \0 ia -tf on to o o cx* o to (A to vO 0* 1A O 00 -st rH rH CM VO rH rH rH rH rH rH n w n rH rH rH n n ^ n d l> ca ct> rH o ca vO m m >}■ v£) ir\ >t >t rH rH rH rH rH rH rH Q\ tM ^00 CM NT Nf (B CM I vO CM rH rH t-l CM rH h r\ O (M^n in >o >o ton >J OJ IA vO n vO IA \C nD la ia \0 vO vfl CX> vD to O 1A -vt vO (A in CA Nt t> O t> O \0 NO lA \D OHO-J CMn^ vO vO C- -\T ^ \0 \D \0 cmti m>t \0 >f *A t> >A o to o no c- o r~ no t> no t> ON CM nO vO C~- nO H O AJ CO O r> o t> Co no to o CM CA -J- IA to \0 NO *A lA nO nO to o \0 \0 1A >0 tO O O CM rH rH fA vO v£> vO *A *A \0 CO c ■h to a o uc C -H O ■H £ CU HOB c CU CO o £ o - - o o •H to CO m Q Q 3 o w O -H O "H TJ Z .C C . . -p to co P «3 m 3 10 i. 3 ^ O *H O O CU ►h 2; z W Z < rH +> =1 o w 86 INCOME DISTRIBUTION IN THE UNITED STATES u u u u TJ V) U w Q C OJ -3 O H 11 ^ as C CD e_ -H 6 3 « § 11 h !0 > T3 U •H C 0) ■P -H X * -X -- rH O 1) TI 3 T3 CD ■> >h 0J C T3 ^ 0) C CD S *H £ m M h u o O -O 3 3 o e ' 4! a) O G Oi b. j3 a ti ed O rH Cw 0) U D Pi CO C o • O D CO X C ►J 01 CO •o to 1, 1) u > -9 •H C CO JC E 0) "O ~ s 8- 9 C ; fci to £ )i e ii 10 E-HAl u o d O x) 5 t. <— c O CO *0 O H ■A rH O CT> (MHHrl O C- *0 rH H H (M N (jiinniPiinntMni ONC"\00>rHt>OvO (\inton v£> vO f> >t c- co c- *£>C^CMmC0r>OC0 in^£)v£)iAI>'sfiA-Nt CMC--*CT*OOOt\l rH vO tM ITi IA >J Nf CM I Nf rt r-n rt o O «*V t> f*> f 0> >0 IT* -vt -nT ^ WfMr\NtOtOtDQ c-i cm rH >rv vo vo ■H Q m \0 vD -O O Q vO >0 *0 -st O 04 rH CM t> ia r> r> c^- r~i m ir\ vO >£> t> ^SJiOHIJi-JiftiO lAmiAto^C^^^O c o a c O CO CO o c c o o U t-, CO CO o o t- 3 o o CO CO •H T3 00 »H o o 0) rH C fa. ft § ■ c a co a e OHO c to .e to cd **h co co 3 rH X H ON • •< Joe c *> ■H C CO o C co jc e o ^ OH T3 >J O H 3 o > -H £4 c? c o •H O Cm CO 41 rH CO rH CO 3 O O .1 S 8 35 a a o |§ I s 5 o 5 -H to £ -3 1 i 2 & fe CC •H co 6r> Q — 1 - £ & 2 »- a p 5 •* §1 a >, a S ^ § cn d be c t. o 08 • a ii a es O o -o * c a 03 i s s a C CO s S ■ s * s I B o o 53 £ H lo m u> bo a a 5 a g 81 fe S. £ CD 2 S i § Pi us § I S 55 ec 03 tsc « 03 8 2 CN g 1 1 -a -5 5 » E g VI *" w JS a b o o ® _ Co m a; « 55 3 ~ w w 03 > s ~* Oi B 03 03 o > a o — 03 3 a o Cm co C O S 2 " 2 d a es o a o 3 a o - 8 ~ o 3 20 TRENDS BY MAJOR OCCUPATION 87 The figures for 1959 represent median total money earnings for men report- ing $1 or more of earnings. In most of the occupation groups for which 1949 to 1959 comparisons are made, the differences between median total money earnings and median total money income are also quite small, amounting to only several dollars. It is only in the professional and managerial group that that difference is at all substantial, and here it has the effect of minimizing the percent increase. Since this group had greater relative gains than most of the others in practically all States, the conceptual problem does not impair the general conclusions. The patterns observed for the country as a whole were found also in the great majority of States. In practically every State, between 1939 and 1949, nonfarm laborers made greater relative gains than operatives, and operatives made greater relative gains than craftsmen. In other words, during this decade the tendency for men in the lower paid jobs to make greater relative gains than those in higher paid jobs was a phenomenon widespread throughout the country. On the other hand, the figures for these same three occupations — laborers, operatives, and craftsmen — showed a reversal of this pattern during the decade 1949 to 1959. Thirty-three of the 49 States for which data were examined — including the District of Columbia but excluding Hawaii and Alaska — showed a consistent pattern in which craftsmen made greater relative gains than opera- tives, who in turn made greater gains than laborers. In 5 of the 16 States which deviated from this pattern, operatives and craftsmen made about the same relative gains, but both made greater gains than laborers; in 10 of the other States, operatives made greater percentage increases than craftsmen, but both made larger relative gains than laborers. It is significant that during 1939-1949, laborers made greater relative gains than operatives or craftsmen in every State, whereas during 1949-1959 they made greater relative gains only in the District of Columbia. These data strongly support the conclusion that during the decade 1939 to 1949 the greatest relative gains were made by the lower paid workers; and that between 1949 and 1959 the greatest relative gains were made by higher paid workers. Further support is given this conclusion by the gains made during 1949-1959 by professional and managerial workers and by farmers and farm laborers. Fig- ures for these groups are not shown for 1939 because the restriction of the 1940 Census data to wages and salaries would not provide very meaningful results for such groups as farmers, businessmen, or independent professionals who depend on self-employment income rather than wages and salaries. However, the figures for 1949 to 1959 show that relative gains for professional and managerial workers, who are among the highest paid, were in most cases about equal to or greater than gains made by craftsmen. In contrast, farm laborers — who are on the average the lowest paid workers — had a decrease in income in 10 States; and where gains were made, in all but 2 States, they were proportionately smaller than gains received by nonfarm laborers. 88 INCOME DISTRIBUTION IN THE UNITED STATES Farmers — also among the lowest paid workers in terms of annual earnings — tended to have smaller relative increases in earnings than nonfarm laborers in most parts of the country. Relative gains for farmers were below those of non- farm laborers in every State in the Northeast and North Central Regions. They were also lower in about half the States in the South and West ; in these regions, however, farmers attained smaller relative gains than the higher paid craftsmen and professional and managerial workers. Inequality of wages within major occupation groups, 1939 to 1960 The preceding section focused on the possible impact on the overall income curve of differential changes in the level of wages among occupation groups. It was found that during the decade ending in 1949, when incomes were becom- ing more equally distributed, lower paid occupations attained greater relative gains than the higher paid; the reverse was true during the decade ending in 1959, which was marked by stability in income distribution. The present section directs attention to the association between overall changes in income distribution and the spread of wages within occupation groups. Table 1 1 1-8 shows the share of wages received by the highest paid fifth of the workers in each occupation during 1939-1960. Although the shares received by each fifth were computed, only the top fifth is shown, since this proportion is a reasonably sensitive measure of the change in dispersion. The figures were computed in the following way. First, the workers within each occupation group were ranked by wage or salary income levels from lowest to highest, and an esti- mate was made of the number of workers at each level. (In preparing this esti- mate it was assumed that persons who did not report on wage or salary income were distributed by income levels in the same proportions as those who did report.) An average income was then selected for each level, and estimates of the aggregates were obtained by multiplying the number of persons at each income level by the average for that level. Sources cited in table 1 1 1-8 give the specific levels used. In the 1939 data, the midpoint of each level under $5,000 was used as the average, and $9,000 was used as the average for the open-end interval ($5,000 and over) . This estimate was made on the basis of an analysis of tax returns for that year and other relevant information. For all other years, the midpoint of $500 or $1,000 intervals was used as the average, and averages for the open-end intervals were generally obtained by fitting Pareto curves to the data. It is important to distinguish between the figures for men and women in table 1 1 1-8. The figures for women are highly influenced by the fact that a great many women are part-time and intermittent workers. In such occupations as sales workers, private household workers, and service workers, where large num- bers of women work only on a part-time basis, and others are employed full time throughout the year, it is difficult to assess the meaning of changes in the dispersion of wages. The fact that the distribution of wages in these occupations was more unequal in the postwar period than in 1939 undoubtedly reflects to a considerable extent the increase of part-time employment in these jobs. TRENDS BY MAJOR OCCUPATION 89 • ASM o ffl CO t m -Nj- < \OCQP3CQCQCQ B3CQCQCQCQCQ Service workers , except private household 0>0> >D * CO m CO m CM CI m CM 01 PI rH rH CM rH m to n n m m m m m -4- -<(• -4 -4- ni- st- >* >t >t >t m Priva te household workers cqcammpacQ ca m t Operatives and kindred workers ^- >j n n n ->t ci cm cm cn t> vOvO^ommvO ia in >j m >j m nnonnn c"\ c\ m fi en m 1^ n n 1^ n d n n n n Craftsmen, foremen, and kindred workers n n n n n n n n n ci cn en en tn ro en en en o> en en en Sales workers nfiiMHOW cm t> >f >f n %t cm n cm en cm cm ->t >t Nf >t >t <*> >J >t >T Nt >t Nf Nf NfSTsJ-NfSfn Clerical and kindred workers m ei m ci cm cm cm cm cm h ^ vo t> i-h to •* — > to cr> m cm %t -*t nj- sj-^t-^j-sf-Nt-o; cn cn sf ^ omenen^ <; z »-» z Professional, technical, and kindred workers t>COt>t>t>\D t> CO to t> O vO\Ot>t>tOt> OvOOmvOCM enmmmcnen m m m ci m <; n ^ n fi mm m. c-\ c~\ ei c> >t z O 00 t> m \f n (M H O w0 lT\ IT\ IA 1A lT\ ITi 1A m IA IT\ o^o^o^o^o^o^ rH rH r-t rH rH rH rH rH rH rH rH rH \0 ia ia ia ia ia mmmmmo^ O^O^OO^O^O^ (T 1 CT* (7 s CT^ (7^ (T* ■- 3 03 03 o 55 co 9 s bo 03 a a be a is o x: o o — a .0 *3 03 - 3 V CD o -a a I hi - a 03 CM I I » CD — O 3 C3 CD i « CD ■—• 03 CQ O V CO .2 S a 8 33 © © IS 1 1 >•«« .© f I £ 1 33 co" a - 03 ff) « o W 3 1 £ 2 3 o i ^ OS t a 03 o> 3 a O 03 GO ... 90 INCOME DISTRIBUTION IN THE UNITED STATES Q uu o cu 3 w o h Z uu U 06 uu Oh >r\ Q. 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1 3 < -1 uu h < O uu o o < u. o H z uu U oi uu CU I ; t coeotoc\ic\jtomiANf^}-c\i^i-r^ivO f-c1t>OrHl>m<'"\OC\lr'-iC->nvO rHvOr-OOCOP^mCMr-tflCNJvOi-im vOr-C-TvOOO^tOCIOJCNJfnF-COm rHC\IOOt>iHrH>ncnrHOJ(^lArHvD r-(C-r>JO>ii-ir r \>tc\jr'-ioh CO" 'fiU 1 CCC'-l«)HOHvI)(M OJ^.rilJ>0>OtOH(f001M«)f>i r-IQarHC\|r^rgrHi-lrH^rHiHi-(r-l rH^-~C->Of r ><*>'^rH>OrHCyJOOJ <~>J(ar-ir\JCNJC\jr>JrH^-(r-| 1 Hi-liHrH oc^O^'O^^'ooh won NBHNOitMHHHHrHiHNH 5">NfinOO»NOOO>ttO(M g r o H c U .0 n a u U CO u P. 0) a £ a Et a o J3 o as Ph I •g X 1 a - o e JS o 3 g PQ CO 05 as 9, and 1939 to 1949 State Percent increase , 1949 to 1959 Percent increase, 1939 to 1949 Laborers Operatives Other workers Laborers Operatives Northeast: 66 72 79 148 142 New York 67 65 83 168 165 69 65 47 147 149 71 64 77 175 163 North Central: 74 73 84 149 146 46 54 70 229 163 60 61 77 202 183 63 61 81 142 139 81 75 78 125 121 (NA) 59 91 157 123 81 53 75 166 157 South : 70 64 73 159 144 89 74 93 204 231 50 77 87 273 176 West: 76 58 68 127 138 63 74 82 158 176 N T A Not available. Source: Appendix table D-l. TRENDS FOR MANUFACTURING INDUSTRIES 115 In 12 of the 16 States for which data are shown in table V-9, laborers made greater relative gains than operatives between 1939 and 1949; and this pattern prevailed in 10 of the States during 1949 to 1959. In this respect, therefore, the pattern of income differences for the transportation equipment manufac- turing industries differs from that for the metal-producing and machinery manufacturing industries. However, when the analysis is extended to the higher paid "other workers," the reduction of differentials between skilled and unskilled workers becomes apparent. In 12 of the 16 States, "other workers" made greater relative gains than either laborers or operatives, providing additional confirmation that higher paid workers tended to receive greater relative income gains during this decade. Food processing Geographically, the food processing industry is much more dispersed than any of the other industries so far examined. This may be seen in table V— 10. Of the 1,500,000 men employed in this industry in 1960, about one-third were in the North Central States, about one-fourth in the South, and an equal proportion in the Northeast. The North and South together accounted for about 85 percent of the total. Although food processing consists of about seven sectors, it is unlike the industries previously described in that it has no dominant sector. The largest sectors, in terms of the number of men employed, include dairy products, bakery products, and meat products, each with about 250,000 workers. Next is the beverages sector, with about 200,000 workers, followed in turn by grain mill products and canning and preserving, with about 130,000 workers each. The pattern of change in wage differentials along regional lines, shown in table V— 11, varied more for the food processing industry than for any of the others previously examined. In the 20 States of the South and the West a familiar pattern is seen — a narrowing of wage differentials between 1939 and 1949, and a widening between 1949 and 1959. In these regions, all States except Mississippi had laborers making greater relative gains than operatives Table V-10.— Males in Food Processing Industries, by Regions: I960 [In thousands] Industry- United States North- east North Central South West Total experienced civilian labor force.... 1,462 356 380 222 254 36 126 66 26 28C 75 102 64 39 138 30 27 35 46 132 15 65 38 14 275 94 76 66 39 40 19 12 6 3 196 53 61 59 23 Misc. food preparations and kindred products.. 129 28 30 42 29 18 6 5 4 3 Source: 1960 Census of Population, Vol. I, Characteristics of the Population, Part 1, U.S. Summary, table 259. 116 INCOME DISTRIBUTION IN THE UNITED STATES between 1939 and 1949. During the next decade they made smaller relative gains than operatives in all but 2 States, and in 13 States they made the smallest relative gains, followed in turn by operatives and "other workers." The pattern in the Northeastern States was similar to that in the South and West but not quite as striking. Four of the States showed a narrow- ing of wage differentials between 1939 and 1949. Between 1949 and 1959, the widening of wage differentials in most of the Northeastern States was similar to that in the South and West. In the North Central States, the pattern of wage movements in both periods was basically different from the patterns for the South and West. Between 1939 and 1949 there was a widening of differentials in 5 of the 11 States for which data are shown ; in 7 States, the relative gains made by laborers between 1949 and 1959 equalled or exceeded the gains made by operatives and "other workers." The tendency toward a widening of wage differentials — so typical of other industries and other regions — does not appear in the food processing industry in the North Central States. Table V-l 1 . — Percent Increase in Median Income for Male Laborers, Oper- atives, and "Other Workers" in Food Processing Industries, for Selected States: 1949 to 1959, and 1939 to 1949 State Percent increase, 1949 to 1959 Percent increase, 1939 to 1949 Laborers Operatives Other workers Laborers Operatives Northeast : 113 90 63 127 131 60 70 67 126 124 65 71 73 165 128 57 77 73 154 144 57 66 69 138 131 North Central: Chio 63 71 66 128 138 67 65 64 183 138 Illinois 75 74 76 141 146 38 62 63 184 149 68 59 67 155 133 67 65 70 128 127 83 81 69 136 137 66 77 71 170 139 85 76 48 132 148 86 83 74 148 148 66 75 73 157 141 South: 60 50 63 146 92 50 55 71 166 116 49 55 61 233 152 West Virginia 31 41 92 166 130 33 43 59 182 148 49 53 61 172 155 51 58 69 210 143 53 64 61 219 175 59 74 68 210 166 66 65 69 175 165 43 48 70 199 143 42 47 68 184 188 36 55 56 218 155 52 64 72 265 181 48 53 80 154 127 53 56 60 174 150 West: a 74 71 187 135 2B 68 65 222 160 18 55 67 225 149 California 195 130 Source : Appendix table D-l. TRENDS FOR MANUFACTURING INDUSTRIES 117 Textile and apparel manufacturing This industry, for which data are given in table V-12, is almost equally divided between the Northeastern and Southern States, and employed nearly 900,000 men in 1960. The two major sectors are the manufacture of yarn, thread, and fabric, largely concentrated in the South and accounting for nearly half of the total employment; and the manufacture of apparel and accessories, centered in the Northeast. Although there was some narrowing of wage differentials in this industry between 1939 and 1949, table V-13 shows that it was not nearly as pronounced as that previously described for the metal, machinery, and transportation equip- ment industries. Seven of the 1 7 States for which data are presented for textile and apparel manufacturing had a widening of differentials between 1939 and 1949, and several of the other States had only small changes. Between 1949 and 1959 the industry followed the general pattern of widening differentials. In only 3 States did the relative gains for laborers exceed those for operatives and "other workers"; in about half the States, laborers made the smallest relative gains, followed in turn by operatives and "other workers." Table V-12.— Males in Textile and Apparel Manufacturing Industries, by Regions: I960 [In thousands] Industry- United States North- east North Central South West Total experienced civilian labor force.... 873 376 60 412 25 558 181 21 349 7 378 95 6 274 3 180 86 15 75 4 Apparel & other fabricated textile products... 315 195 39 63 18 265 173 28 5: 14 Miscellaneous fabricated textile products... 50 22 11 13 4 Source: 1960 Census of Population, Vol. I, Characteristics of the Population, Part 1, U.S. Summary, table 259. Table V-13.— Percent Increase in Median Income for Male Laborers, Oper- atives, and "Other Workers" in Textile and Apparel Manufacturing Industries, for Selected States: 1949 to 1959, and 1939 to 1949 State Percent increase, 1949 to 1959 Percent increase, 1939 to 1949 Laborers Operatives Other workers Laborers Operatives Northeast: 38 44 34 220 215 42 54 45 214 184 41 57 60 188 166 43 56 53 203 168 31 50 58 221 197 45 51 66 190 219 48 67 67 184 22C 36 42 59 191 188 North Central: Ohio 60 56 61 158 216 48 55 65 171 174 South: 45 43 52 216 222 45 47 53 193 194 41 46 46 214 207 44 47 50 210 199 Tennessee 33 36 45 188 185 37 37 42 238 218 Texas 31 50 58 183 188 Source : Appendix table D-l. 118 INCOME DISTRIBUTION IN THE UNITED STATES Furniture and lumber and wood products This industry employed almost 900,000 men in 1960. Its major sectors include sawmills, planing mills, and millwork; miscellaneous wood products; furniture and fixtures. (Logging was included in 1950 and 1960, but since it was not included in 1940, it was omitted in this study for the later years as well, in order to improve the comparability of the data. ) About 40 percent of the employment in furniture, lumber, and wood products is centered in the South; another one-fourth in the West; and the remaining one- third is almost equally divided between the Northeastern and North Central States. Most of the employment in the South and West is in sawmills, planing mills, and millwork, whereas in the North it is concentrated largely in the manu- facture of furniture and fixtures. (See table V-14.) Table V-14.— Males in Furniture and Lumber and Wood Products Industries, by Regions: I960 [In thousands] Industry United States North- east North Central South West Total experienced civilian labor force.... 852 133 165 355 199 Lumber and wood products, exc. 523 54 75 232 162 Sawmills, planing mills, and 432 31 54 197 150 Miscellaneous wood products. 91 23 21 35 12 329 79 90 123 37 Source: 1960 Census of Population, Vol. I. Characteristics of the Population, Part 1, U.S. Summary, table 259. The pattern of wage changes in this industry was quite varied. Table V-15 shows that in the South between 1939 and 1949 there was a narrowing of wage differentials in every one of the 15 States examined; during the following decade the widening of differentials — so typical in the durable goods industries — took place in all but 2 of the States. It was mostly the operatives, rather than the higher paid "other workers," who made the greatest relative gains. This differ- ence may reflect the fact that there are relatively few skilled workers in this industry, and that in the "other workers" groups, owners of small sawmills or of similar establishments may predominate. The West, which is the other major center of employment in this industry, showed very little narrowing of wage differentials between 1939 and 1949. During this decade, in 4 of the 6 States for which data are shown, operatives made greater relative gains than laborers. Between 1949 and 1959 there was a widening of differentials in about half of these States. In the Northern States, more men are employed in the manufacture of furni- ture and fixtures than in lumbering and the manufacture of wood products. This region showed a tendency toward the narrowing of wage differentials be- tween 1939 and 1949. In 1 1 of the 15 States for which data are shown, laborers made greater relative gains than operatives. The Northeastern States exhibited a distinct tendency toward a widening of differentials during 1949 and 1959. In the North Central States, however, the pattern was quite mixed. TRENDS FOR MANUFACTURING INDUSTRIES 119 Table V-l 5. —Percent Increase in Median Income for Male Laborers, Oper- atives, and "Other Workers" in Furniture and Lumber and Wood Products Industries, for Selected States: 1949 to 1959, and 1939 to 1949 State Percent increase, 1949 to 1959 Percent increase, 1939 to 1949 Laborers Operatives Other workers Laborers Operatives Northeast : 34 50 48 196 151 67 65 64 133 147 42 51 53 153 149 47 61 56 154 158 44 46 59 183 163 41 56 68 171 151 51 69 57 161 160 North Central: 68 64 60 77 65 60 X I H m a S s c u I — E C o in c o a 2 < c\ n 3 So u E u u -o o c u -o S J2 "3 -o Ol in 91 4J E 8 c c (« CO eq i-4 -4- C ff +> 5 c U 9 H I in 5 o iS c u ■p (3 0) f-i a. o o t> fn ff I a) rH m > d o co in H ff ff) rH »5 c a) CD I 10 P 9 ? t-i -h cd o i a rH lA 4) o I a) rH in ai -«* >> C o; I CO S -S s Ol m r. ff I a) iH in oi 3 *.S I a) rH m ai in >» c c oi 01 I CO K-5 S Ol Pi >t CO S I a) rH m o> O %f co m n o> l a) iH m o> cm *.g 3 E CM rH I rH rH rH II III cm t> m t> vo en O *0 vD CM t)0 CM pj(fo>mrirl cm cm m m to vD CM TO rH CM vo \2 cn S ff S CM m CM CM o ff _ H en ift vfl vO MOO fT^T IfCvO' ttT rH~ to m m cm cm cn ff ff m C~- TO TO cm cn m vO ff h h o> g cm m CQ ff S ff ic ffi i O O if\ m vim to H ->f to "r» «"> m vo !•> ff rH TO O m cm n >f to m r\ ff B rH C- m m m vO ff m m ff >r to \D o *0 £- m to m o *n to O cn -vt m vo t> N n >i rH ff t> tO cn CM I— ( t r-4 II III t> -tf m cm tr\ ■£> cm ^ n o vo « CM CM >t m TO ff ff vO H O H m ff CM r-i t> r-i ff vo r^i vo >t cm P> >t m vo ff rH rH tO ff C*- rH rH TO H CM O TO S O TO O rH rT-sT irTvo'o^rH' tO 'JD t> Nt vO CM c\ en >t m so ff H to >f O Q * H ri in n Q h O t> CM ff rH S l»> cn -4 >t eo m ^ o >t cm TO m m vo \0 ff TO m o Pi c*^ rH m ff cm >£> ff TO vO >» C5 CM n>t m ^ to H cm ci n n >f >J r< a) I 9 i S CO Oi O Ol o 0> co >»-p >.+j >> 01 ►J 00 rH Nf r-t Nf co cd co CO 01 O 0) O 0) CO >i -P >>4J >> 01 1-5 tO rH rH vf rH rH rH t> ff CM i-i r-{ I I rH CM I I I rH Nt C\ \D -t O C-l TO -vt vO CM m >t O CM -4- vO TO rH CM CM CM CM orioo-Jto 3 cn v} t> o ff * * * rH CM CM CM cn n CM >t >t vO O t> CM CM CM CM CM C^ CM v0 t> cn t> O CM m m rH ff CM rH P> t- r-) CM CMnn^vf vO CMMQ^cnn CM O to t> rH TO m r~ ff CM rH CM CM CM tn -si- ff TO TO O t> C^ n«\Hf NO m tn vo o m to nrc^cn >T >T vtT r- ff >f to ff H to sf >} ff to N to >r vo ff cm tn i-rCM" N CM , CM K cn > ^ O to ff m o ff rH CM ff CM »C m t> cm *o H (M O "*f >l rH CM CM CM CM Cl m a CO 3) CO oi ti O t> O ti CO >>-P >>-P >» 01 1-5 TO rH >T rH vt & 1 •P I d E- A b 8 co cd ^ r I €l cu M - ES, B c -J < 3 1 •J- Net" C\ C/5 H r\ u i P£ < ho; U ON ua f-H < Q uj S3 u J a CO 2 w S l-H z < z l-H uj z < u I l-H 1 > H o st CO vO £> U On I td rH m cd o st 03 m no H on o nO L ON I d H m cd m !>> g O St CO NO m f-, on l as rH m > G •H o st oi m St f-, on I ed H O 01 vD ?H ON cd r-H o st co in I cd rH N OCO O O (M CM rH I I r-H rH II II ■A \0 cn CJ> O CM vO LCN to vO ON CM st O O O st cn CM Nt IA m CO \OvDCM r-H t> st m cn st npiNtunoo* NO St ON CM r-H ON v£)H«\flOO o to CO co O C*n Nf \t n O CO H o o m o no r> m no t> st to on st o no t> to on cn St St ITv vD ON r-H St m to CN, H cm m cn H cm m en o on to to to sT irT in* ■•D to h" i-h cn cn cn st cm CM rH O ON t> O en to CN. to O £> CI Cn St St NO CO rH CM CN. st m o O C- cn, in st On in O rH rH m CN. cm cn st m m co O CM CO CN, CO CN. 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The data represent differences in income associated only with age (that is, experience, seniority, loss of work due to illness, and similar factors) and are independent of changes in the economy over time. In other words, on the basis of the cross-section income data by age for 1949 in the 1950 Census, it could be said that the increase in average income between age 30 (the average for 25 to 34) and age 40 (the average for 35 to 44) was $3,700, representing a gain of 76 percent for the decade, or 7.6 percent per year. The variation of income with age based on cross-section data has been measured annually during the past 15 years and found to be quite stable, and the relation- ship does not appear to be appreciably affected by cyclical changes in the level of economic activity. Therefore, it could be deduced that the relationship between income and age reflected in the cross-section data provides a measure of the extent to which factors associated with age affect individual income. An alternative way of estimating the income change between ages 30 and 40 is to compare the average incomes (measured in constant dollars) of college graduates 25 to 34 years old in 1949 ($4,900) with incomes of college graduates 35 to 44 years old in 1959 ($11,100). This procedure provides a more valid measure of the change in income over time than the one just described because it permits the comparison of average incomes for the same group of men at two different points in time, whereas the cross-section data permit only a comparison of two different groups of men at the same point in time. On the basis of the cohort approach, it could be said that the average income of college graduates increased by $6,200, representing a gain of 127 percent for the decade, or about 12.7 percent per year. This increase consists of two separately identifiable components. One is the increase in income associated with aging. On the basis of the cross-section data previously described, it might be roughly estimated that about 7.6 percentage points of the total increase for college graduates is due to the variation of income with age. This factor, incidentally, is taken into account in the traditional method of estimating lifetime income because it is reflected in the averages used in the formula described at the outset. There is, however, a second component of 5.1 percent per year which is not taken into account in the traditional estimating procedure. This component represents the increase for this cohort in average income over time, due to changes in productivity, in the industrial and occupational mix of the labor force, in the geographic distribution of the labor force, and similar factors associated with changes in the economy as a whole. An alternative view of this problem is presented in figure VI- 1. According to the formulation described at the outset, the values used to estimate lifetime income are based on the cross-section data shown at points A ($8,600) and C ($9,900). The difference between these two points represents the variation due to age (experience, seniority, etc.) which the economy is willing to pay for a given resource (college graduates) at a given point in time (1949) . Alternatively, points A ($8,600) and B ($11,600) show how much the economy pays for the same resource at two different points in time. Assuming that the conditions of supply remained unchanged between 1949 and 1959, it can be 134 INCOME DISTRIBUTION IN THE UNITED STATES concluded that because of the increased experience of this group of college graduates, and because of the change in the entire economy during the decade, the annual average income for the group increased from $8,600 to $1 1,600. The difference between points A and B ($3,000) represents the total change due to both the increase in experience and the growth in the economy, whereas the difference petween points A and C ($1,300) represents the increase due to age alone. Therefore, the difference between points B and C ($1,700) represents the increment associated with economic growth. The age component of the increase is included in the current techniques of estimating lifetime income. The component identified as being associated with economic growth is not included. Figure VI-1.— Average (Mean) Income for Selected Age Cohorts of Male College Graduates: 1959 and 1949 INCOME $12,500 $11,500 $10,500 $9,500 $8,500 AGE Source: Table VI-1. A summary of the components of change in income for various subgroups in the population is shown in table VI-2. The key factor here is that for each color and education group, the greatest gains in income are experienced by the younger age groups. Thus, for example, to continue with the illustration of college graduates previously used, it can be noted that the cohort of men born between 1915 and 1924 (those who were 25 to 34 years old in 1950 and 35 to 44 years old in 1960) had annual income increases of 12.7 percent, whereas, during the same period, men who were 10 years older had annual increases of only 3.5 percent; and those who were 20 years older had annual gains of only 1.2 percent. INCOME AND EDUCATION 135 I cu cm 01 rH g O -PCM r4 OH ■a o -p to o *o a o CD cu I a) to to -o a) to a o C~| oj q a O -P oj rH rH OJ r-l OJ rH •MOtOHOO OJ OJ OJ OJ C-\ OJ m m c~- oo ■<* its cn o. m c-\ c\ oo i> o r- --r m O O O rH rH rH 00 ON m rH n en cn >t ti m fi on ("> t-i t> 00 O r-l ■>* vD vD i— I i— 1 OJ OJ C- vO O rH OJ ON 00 • ••••• OJ OJ C 00 -J ON ON OJ rH rH OJ rH OJ rH 0> 00 O PI o o m >0 00 r-H O O OJ OJ OJ OJ P> OJ oj r-i i> oo -n* m • ••••• pi n n ^ i*\ t> C- ON C- ->t ia O C O rH rH r-H \D m O O UN OJ cn O -f -J- m m o oj oo m in \D vD o OJ a* on o -J" t> o rH rH OJ OJ ^ C- C0 (M >0 n3 M n cn c\ c*n ft c*n m oj -J- -n* MD vO t> OJ OJ OJ OJ oj c*-\ -£ 00 OJ O C- O n n n n n tr\ m c~- t> *o oo o c°t cn. c\ cn on. in rH CN OJ c o c ■sT -vf Nt -vT -vf O O !M * ffi o> n m in m in vo O (M>HHOO O O rH rH OJ -vl" 83 6-i M S3 Pi a) > oo c — vi uj (H n ri <^ to a> o J-P ^-P r-> 4) J OO rH NT rH NT A to UJ UJ ■r dn „n k a) a] a] to UJ O 0) O CJ ■ o — rH rH & o a) J3 cu (0 o ■ -p ■p o lp >i-p >> rH o o - S3 ai -p o c CO 0) OJ a .c rH rH rH -H o Ed o C3 CP SS ® i. -J .2 o CO CO O - c I- o CB " i. s| rS " i. - - CUD O r= OHO 136 INCOME DISTRIBUTION IN THE UNITED STATES Q - _ _ a. S u -1 o o X V c/5 - o ai < p 03 - < O c [2- O bT z ai z < I Pm o C75 H z pa Z 2 O u I H at cm ■ CJ C r — g O -Hoi u co ■a o -p «) X! 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Eh □ £ a rt o - u ep 3 T3 CP a - V tT C CP CP n CP cU C r. ep» O CP - o K /. es a> tc a c3 id 2c INCOME AND EDUCATION 137 cu I co — - cm •h - Q Mnmo Mn CM CM CM CM CO rH CM CM C\J CM CO rH CT> co i-i c- i-i cm cu si cd •w 01 73 -a vO to t> \D t> o HHHHIMO lA CO O \D t> to H H H H(M O o vo cm t> o co 8 cd ■a to -p cu i co CO 01 73 cd co 03 O rH t> rH -\t O co r> cm v\ cH CJ\ C- O O -\f O (ji io h \0 m o> CM CM CM rH CM CI O C- rH vO vO O CM CM CM rH CM -st co i-h co co t> >a cm ri (m n n n CU bD s O -PCM u cd ■a O -p 4) * a) W O *D cd o O co i-h cm o ia c^ n c^ n n ia O CM rH CM O m CM CO CO CO vt IA \D CM t> m o O CM CO CM CM r-H -vf C -P OH - - TJ 0) -p 0) I cd CO CO T3 cd co CO O u o H L> O vO -4" vD O O rH rH rH rH CM m O vD^ m O O rH rH rH rH CM rH rH CO CO >t Cm CM s O vO O vO >t co co co co >t O t> t> rH t> CO co co co co co >t lA CO IA CO CM -\t co co co co co ia co I ia CM CU bo < c -P<\i U cd tJ -P CU C3 MOT) cd t) CO CM CO CO UO C- lA lA lA IA CO O CO -\t vO O lA CO IA 0 CO CO IA H H H « ^ O vC O O Nf rH a* O O rH rH CO CM CU ■P CU I o hi O TJ c co a h cd 3 i o w a E cd I co h cd : >» • P>> CO CO 01 .p fc, CO t* CO M cd cd cd co cu o cu o cu to J>> P >>-p >> CU iJ CO rH -nT rH -vt CO Ig cd CU cu >> • CO • co mo CO • H • r. • S ■ cd c • cu ■ cu a cd • :» • >> .p S-, CO In CO cd cd cd co cu O cu O cu co >j P >> p ^ a tJ CO H H >J rH rH r? o rH & OO cd si cd cd -P o cu -p -p O CU g CO bD o C 01 bD cu E-i cu cu g rH rH 6 f} rH bD rH cu bo rH rH •H O rH •H O w as o w O CO e +j b co (h co h cd cd cd to cu o cu o cu to F»-P >> cu iJtt H Nf H >t a rH & O O cd si ■p o CU C CO bO cu cu 1 rH cu bo rH rH •H O W S3 O 138 INCOME DISTRIBUTION IN THE UNITED STATES If, instead of cohorts, cross-section data had been used, differences associated with age would have accounted for an annual increase of 7.6 percent between the average ages of 30 and 40, 1.5 percent increase between the average ages of 40 and 50, and a decrease of about 0.6 percent between ages 50 and 60. When the age component of the total increase is taken into account, it appears that economic growth accounted for a 5.1 percent annual increase in income between ages 30 and 40, a 2.0 percent increase between ages 40 and 50, and a 1.8 percent increase between ages 50 and 60. Since the growth component is not taken into account in traditional measures of estimating lifetime income, its inclusion would add to the expected income gains of younger men and would therefore have an impor- tant bearing on the estimates of expected lifetime income. Table VI-2 also shows that income gains associated with economic growth appear to be somewhat greater for nonwhites than for whites. Overall, the income gains associated with growth were 5.7 percent per year for nonwhites between the ages of 30 and 40, compared with 5.1 percent for whites of the same age. The corresponding differences between ages 40 and 50 were 4.3 percent for nonwhites and 3.6 percent for whites; and between ages 50 and 60 the gains were 4.0 percent for nonwhites and 3.6 percent for whites. Most of these differences are eliminated, however, when the figures are examined separately for the North and West and for the South, suggesting that the apparently greater gains for nonwhites associated with economic growth are largely due to their migration from the South. Annual income and education The overall picture. Some of the basic statistics pertaining to the relationship between annual earnings and educational attainment are presented in tables VI-3, VI-4, and VI-5. Table VI-3 shows the figures in absolute form for all groups; table VI-4 shows the percentage differences for elementary, high school, and college graduates; and table VI-5 shows the ratio of initial to peak earnings. In order to permit a comparison of differentials for more recent as well as older graduates, each table presents data for whites and nonwhites for each age group, as well as for the total 25 years old and over. As previously noted, women are excluded from the analysis for the reasons that a large proportion never enter the labor market after marriage, and that many of those who do work are employed only part time. This is not to say that schooling is economically unimportant for women; on the contrary, the better educated women tend to have higher living standards than those who have not had much schooling. The difference, however, is not generally or necessarily reflected in the kind of work they do — since most of them do not work — nor is it associated with their age, place of residence, or other personal characteristics discussed in this chapter. Among women, the association between education and financial returns tends to be more indirect than for men, and is attributable, to a large extent, to the fact that better educated men tend to marry better educated women. It is because of the indirect nature of this association that the present study excludes the analysis of the relation between income and education for women. INCOME AND EDUCATION 139 - u o as £ < ►J z > U Q (19 u z H 2 n X - >« C S3 x — « z Cfl < - - < O 3 OS o z Q — H H _1 0. z Q w o >> o - X o ^ o ^ <; w H>< Z 03 pa - < OS - > < I — > 3 H IftHFIOOUrlS) piOn»hh-{«iO ^ooocMincrt,Ht> HCM>OrHIMOCN* CMCMCOvO^fCOOtN ^tminvDC^ocoo in\OrH\D-J-CT>rHO omr>o>j-t--occ CMCMCMCnc-I^JWm S? £ S3 > S o o -* o o m » cMn^tmc^Ocoo cic^crt^-^j-minvo C-CMmmcorHmm ^t-vtmvOOOC^rH CM CM C"l -j- >r m vo r\ n in > n \B \D ' — ■ t- M 1 ! no CM rH C"l m CM C* C"> — . 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CO O O rH a) rH b O O -C 0) 1 OJ i rH •s rH rH •H O ta >H co I CO c ca O CO CO s- ■-- = I, n (. n fj o 11 a s >> >» CI O II O (I CO H < rH ->f O o O 01 co bo 140 INCOME DISTRIBUTION IN THE UNITED STATES w U o [14 s < 2 < > Q n U Z H 2 s u O I CN H ^ Q o c/i z o o a ^ < >- 00 Q •— 1 z a < UL) - -J - < o 2< O ca z o SO < 28 * o a IT >- Z CQ O s > < { > 03 H •a I ■p *> rH ot>rHOm-iOtA (O n o to (M i-H[>l>tOC\iCMrOC> mM-i-norHooo %J-lAvD\DCOOOrH stmcMiOoiOtoiri t>\OvOtOtOCM,-HtO ri n o to o> to OOrH ONftOOOJrHNfvO vOC\J^fH(^rHtOC> r-ir>OC~\t>CMCMCM CMCMCMC\C\ir>^rvO CNJCMrHCMO\r>rHC\ r^i-j-irvvor-OOCM ml>NfSfOt-tO-sf OOtOO^^>J(M(M r\>r~j-u*\t-ootM sfiO (M vO O (J> to t5 t\i co ^ m n to w ir\ to * m « vf-^ITlvOOrHOrH ^tt>ot>>'"\tScMC vONtton^nn-f 8 c\. K 3 ' O H H Nl^lA\DtOHOW m h h t rH \0 t> O 1 O «0 vO U"\ ' tOOOtO*OC"\Ot> vOC^^f^tOCOCT^O^ asoovfi-H-Nrto[> oa\oiAi-ir-\t>c- tOCOsfvOtOtOtOtO Nfir\\Or>tOCMr-Hm vOHst^tOtCO^H rHvOtOCM^fir»ir\>J- CMCMCMcnniA-J-vO n>»if\\Oto >rir»xOvOto-*cMrHto ■sTOt>t>t>Or^tO ^mm>cconiNifi lTsr>>'">t>r^C'\vOrH CMC\fn>r>fvOirit> OOtot>t>ir\c--*a >JKMfHBtOMHK\ f\>jinvOtori a I to 5 £ a) to > R CD O 0) CI u u co co co n f< r\ (, o 11 a) co >> >> O oj o cj >> -P >w m CO rH rH >» to 9 ■ CO CO CO CO CD CD >> >> .c o CO •H gj Eh £ CO W CD O CD O CD CO >>-P >>-P >>-t f\ .-5 tO i-H -4- rH >t C\ O C"l O O O O >t >t NT t> m OO^OCMlTlt^om HOtOlf\H •^IMOOH«0>n •NflAvDOCOrHOCM r>OOr>C1tOtOCM r^OOsftOrHOOC^ CMrHOOO-sfOCNJ rHvOvO-stmtoiriO rHt>Ot><^l^ ^NfvOtOCMOr>>f >r\tO-vftOOt>lACO t>c^-4-Oc*"iinr>o CMfVrH[>irirHt\CNJ to-*Oc^ir>CMt»>o ^oc-mojotOrHt> toOc>T>e"\t>ot> ^ t- to r> to to CT> C"t t> tO f> O CM O to r^CNitOCOCNJtOlATl O^D-4t> nootoootoio ~j->tvOvoto>tc\jm mrimconwirin toot>>fv5c5voto Oi>«)ij>>nNiri >t>fif\\OtonNvt O O riJ 84 3,062 4,791 64 7Z. 700 C. y (\J\J 1 o nn ft? 84 1,714 2,544 67 73 4,878 6,833 71 75 5,101 6,997 73 84 2,828 3,921 72 68 5,946 10,473 57 71 6,142 10,777 57 82 3,310 5,211 64 66 6,316 12,202 52 67 6,502 12,650 51 82 3,273 5,582 59 62 6,523 11,782 55 63 6,708 12,159 55 86 2,894 5,048 57 UNITED STATES 25 to 64 years old... White 18 to 24 years old 25 to 34 years old 35 to 44 years 45 to 54 years old 55 to 64 years NORTH 25 to White 64 years old 18 to 24 years old 25 to White 34 years old 35 to White 44 years 45 to White 54 years 55 to 64 years SOUTH 25 to White 64 years 18 to White 24 years old 25 to White. . . , 34 years 35 to White, 44 years old 45 to 54 years 55 to 64 years Nonwhite. $4,725 4,837 3,318 2,465 2,589 1,745 4,197 4,357 2,994 4,730 4,861 3,474 4,904 5,000 3,457 4,840 4,908 3,324 4,872 4,932 3,794 2,743 2,777 2,355 4,393 4,468 3,562 4,850 4,922 3,874 5,038 5,091 3,885 4,962 5,001 3,772 3,979 4,215 2,569 2,000 2,185 1,440 3,539 3,827 2,384 4,072 4,332 2,724 4,160 4,371 2,668 4,074 4,238 2,476 $6,132 6,250 4,021 3,036 3,105 2,216 5,361 5,480 3,717 6,398 6,507 4,379 6,691 6,793 4,157 6,824 6,940 3,888 6,163 6,245 4,246 3,115 3,144 2,600 5,422 5,498 4,013 6,414 6,492 4,522 6,705 6,779 4,309 6,888 6,984 4,122 5,675 5,889 3,062 2,700 2,852 1,714 4,878 5,101 2,828 5,946 6,142 3,310 6,316 6,502 3,273 6,523 6,708 2,894 142 INCOME DISTRIBUTION IN THE UNITED STATES Table VI-4.— Earnings Differential Between Male Elementary, High School, and College Graduates 18 to 64 Years Old in the Experienced Civilian Labor Force, by Age and Color, by Regions: 1959— Con. Region, age, and color _ -•- ligh school differential High school -college differential Elementary High school Ratio High school College Ratio VEST $5,221 $6,613 79 $6,613 $9,807 67 White 5,300 6,721 79 6,721 9,934 68 4,132 5,002 83 5,002 6,928 72 2,823 3,295 86 3,295 3,660 90 'White 2,888 3,347 86 3,347 3,692 91 2,123 2,597 82 2,597 2,936 88 4,804 5,860 82 5,860 7,109 82 White 4,925 5,971 82 5,971 7,177 83 3,572 4,614 77 4,614 5,867 79 5,368 6,886 78 6,886 10,820 64 5,470 6,988 78 6,988 10,929 64 4,371 5,405 81 5,405 8,049 67 5,361 7,074 76 7,074 12,788 55 5,432 7,163 76 7,163 12,986 55 4,299 5,154 83 5,154 7,934 65 5,180 6,987 74 6,987 11,478 61 5,229 7,092 74 7,092 11,587 61 3,958 4,644 85 4,644 7,666 61 Source: Table VI-3. Looking first at the figures for all age groups combined, we can see the now- familiar tendency for earnings to increase with education. This finding parallels that obtained in virtually all other studies of the relation between income and education, some dating back to the early part of this century. 13 Below the college level, there is roughly a $500 to $1,000 difference (about $10 to $20 per week ) between each of the education groups shown. Thus, among men whose formal schooling ended before the eighth grade, mean income was about $3,700 in 1959. compared with about $4,700 for elementary school graduates. Men with some high school training but no diploma had a mean income of $5,400 compared with $6,100 for graduates. The greatest increase in annual earnings was found at the college level, where men with 1 to 3 years of training averaged $7,400 compared with $10,100 received by graduates. There is a relatively large difference in earnings (29 percent) between men who complete the eighth grade and those who do not : this pattern has been observed in numerous studies conducted under varying economic conditions. It is hard to imagine that the specific skills learned in the eighth grade are so different from those learned in previous grades as to produce so large a differen- tial in earnings or income. It is more likely that the failure to graduate from elementary school serves as a basis for identifying those persons who, for a variety of reasons, will tend to lag far behind the general population in productivity and income. At this level, education may serve as a proxy variable for other factors that prevent successful learning and lead to low productivity. INCOME AND EDUCATION 143 CT> rH C- O CM vD CM tO C\J vO st r> c**i m c- st o m oq is"* to cm CM st st 0> CM i> n t> st vO st n rH £> vO CI O to <*> to <£> CM to o to cm -J- to c~i CM O m to cm m rH VA vO CJ\ <0 0> H rv CM st st st t> t> St St tO rH m st t> O [> St CM O o to n st r> o O H st rH CM CM Q tO st st so m st O O st cm cn m m to st CI CM H o m t> CM \D tp St vD st st CM VO st to st m m CM^vT O CM vO r> o m m m Sst-2- O to st r\ rH m to St m rH O tO C- m rH C> tO ITl cn to St n h no o> rH rH CM 1A \D O O to O m CM St vO O O st n cm n r> vo o rH m rH t> St CM O m so o o o O M3 O rH st \0 st rH O O >fl n O rH St m in cm st ci Q CM to st O CM st CM rH m st m cn CM CM rH O t> CM O vO rH St St St tO VO cn vD Ifllflrl in to vo o o o cn O rH m m to st rH O o c-i m st o m rH t> to m m cm o m m m cm st t> rH m r> Cf> in t> O m o st r> o st \D st I> st rH t> orim o in cm m to o to m \D m CM m o 0010 t> o c-> v£> st to to CM CM O st tc vD O *o m in st oTsT cn to st st n m C- O iO to i£) O rH st m m vo rH o st rH t> moo o (*1 in c- cm cm in m st cm m o CM rH O o -t n O tO rH C- CM CM CM tO in m vo O st m st vO rH oT -te- rn o o st m in I s - st O m rH vo m m to vo to en c- vO o st rH in st c-i st St \D st to st to vo cn H st m to cn CM rH On O rH C"l o m a C9 o rH cn CM n O m rH O CM st O O CM to O m m o CM cm m \D m st v£> to m c^ vo O O st rH t> rH CM O in n vO O n vo vo m in m to rH vD Oi n \0 t> HNtH O to CM CM vO t> O CM m m m as r> m st o \D o m st o O O m St rH sr m r> O rH m r-i o> st O vo 0> st o HOn to ci r> HHCM in n to st rH vO st rH t> to CM CM cn a) H O o X -a o C T3 -O rH rH o o CO CO U U as a! CD CD >> >> c o o -p > co st st u cm m al n CD O O -P titom rH St o ■a -a rH rH o o co co U r. cd at CD CD >> >> •rl O O .. -p -p a) co K ri to m cd rH sr o o CO CO rl ^ cd a) CD CD >> >1 CO St St ri cm m _ a) tH 1) O Of >j-P -P cd IS rH St O -P CO CD rl o o CO CO U f-i al cd CD CD >1 >5 cm m o rl TH O O o +j ■P-P s co cr; ri to m 03 rH st CD CO CO U U a> as •rH CO O O -P fl-p-p « a) PS cd to m >>rH St o o .. co co CD U rl ri a) a) O CD CD E >> rl St St O CM m •H CO O O f h -p -p as as al cd to m >>rH St m O 8 03 es J2 to 3 o — CO 144 INCOME DISTRIBUTION IN THE UNITED STATES A similar differential (although not quite as marked) between persons who attain a given level of schooling and those who graduate from that level, appears also at the higher grades. For example, in 1959, men who had started high school but did not graduate received on the average about $700 more per year than men who completed their schooling in the eighth grade. High school graduates, however, received about $800 more per year than men who started high school but did not graduate. Similarly, men who attended college but did not graduate had, on the average, about $1,300 more per year than high school graduates. The comparable differential for men with 4 years of college was about $1,900 per year. The income differential between men with 1 to 3 years of college, and those who have graduated, reflects, in part, differences in "ability." It is also likely that a diploma leads to better paying jobs, and thereby creates an earnings differential not necessarily related to the specific skills acquired in the final year of schooling. 14 Lack of education limits opportunities for occupational advancement and produces a very narrow range of earnings. Table VI— 5 shows that the average annual earnings of young elementary school graduates was 50 percent of their peak earnings. Among high school graduates the opportunities for advance- ment with age and work experience are somewhat greater, but still quite small. For this group, average earnings at ages 18 to 24 were 45 percent of their peak average at ages 45 to 54. Men with college backgrounds have by far the greatest opportunities for advancement. Initial earnings for men with 4 years of college were less than one-third of peak earnings; and for those with post- graduate work, initial earnings were only one-fifth of peak earnings. In part, the greater relative gains of college men are due to the fact that most of them have not completed their formal studies until they are 22 years old. As a result, the average for the 18-to-24-year age group reflects, to a large extent, receipts from part-time employment in jobs not necessarily related to their college training. In contrast, those men 18 to 24 years old who did not go beyond high school have had an average of 3 years of work experience, and they tend to work at full-time jobs. For the same reason, men in this age group who did not go beyond elementary school are also experienced full-time workers. However, the conclusions presented here regarding the variation of earnings with age for men with different amounts of education are valid even if the full range of ages is used rather than just the ages of initial and peak earnings. This fact can be seen in table VI-6. Among elementary and high school graduates there was a sharp increase in average earnings between the ages of 18 to 24 years (hereafter referred to as age 20 which is roughly the average for the group) and 25 to 34 years (hereafter referred to as age 30) ; and a moderate rise during the following 10 years. By age 40, however, most of these men were close to their peak earnings and most increases thereafter were small, resulting in a slight drop in mean earnings at ages 55 to 64. In contrast, the average earnings of college graduates rose sharply for each age group and did not reach a peak until they were over 45 years old. INCOME AND EDUCATION 145 Table VI-6.— Variation of Average (Mean) Earnings For Male Elementary, High School, and College Graduates 18 to 64 Years Old: 1959 - Age Average (mean) earnings Percent increase over preceding age Elementary- school graduates High school graduates College graduates Elementary school graduates High school graduates College graduates $2,465 $3,036 $3,538 (X) (X) (X) 4,197 5,361 7,053 70 77 99 4,730 6,398 10,863 13 19 54 4,904 6,691 13,313 4 5 23 4,840 6,824 13,089 -1 2 -2 X Not applicable. Source: Table VI-3. Variations by color and region. When the tendencies described for the total population are examined separately for whites and nonwhites, it can be seen that the earnings of whites are much more responsive to increases in educational attainment, reflecting perhaps their greater opportunity to use the skills acquired in school. The relationship between earnings and education for whites is very similar to that previously described for the total population: Below the college level, earnings increased by $500 to $1,000 for each of the education groups shown in table VI-3. Among college men the gains were much greater, ranging from $1,000 to $2,000. Gains in earnings for nonwhites were much smaller at all education levels. Below the college level, greatest gains appear to be associated with graduation from elementary school. The average earnings of nonwhite elementary school graduates were $800 greater than earnings of men who did not reach the eighth grade. An average of 2 years of high school added only $200 to annual earnings; and high school graduates made only $500 more than men with an average of 2 years of high school. The economic value of college training was particularly less significant for nonwhites than for whites. The nonwhite male with 1 to 3 years of college averaged only $300 more per year than the high school graduates. Among whites the differential was 4 times as great ($1,300). Similarly, the nonwhite with 4 years of college earned only $500 more than the men with only 1 to 3 years of college. Among whites this differential was about 4 times as great ($1,900). These patterns did not vary appreciably by region. Earnings for whites and nonwhites were lower in the South than in the other regions; but the relationship between earnings and education was much the same as in the other regions. The variation of earnings with age for whites and nonwhites is summarized in table VI-7. Among elementary school graduates, whites and nonwhites had about the same pattern of earnings. In both cases there were sharp increases in average earnings between ages 20 and 30, and moderate increases 146 INCOME DISTRIBUTION IN THE UNITED STATES -p 3 •a a co bp co a e m — q •H 0J C do C a as u co bp C-c ao P. a) C CD u a cu ^ & o a, CD p bO C co bp as a CD fH Pi -a u bo P. a) fl) co i| CU p bo U as a u ■ V ^- O Sf rH 0> X vO I ^CM CO t> o X IA C^l rH ^Sf Sf t> O X fN rH O C- CM d X O m | I »■> rH -J- cn. CM X O ia cm I ^CM KWOri X o m cm X O >A rH ^ O n h sf ■■D t> \D ON co > n to O O O rH n IA rH st CO QN hskjooi rr\ sf \0 t> vO Sf rH rH CM CO Sf CM rH CO St "A On CM IA O cm m m ia in nO t> On sf nO O nO -J- r-\ no o no O >o ^ oj n o ia rH o u"\ c-i o n to co to \OOtomn ■A CM rH O CM C\ t> rH sf st On t> t> O 0> St 0> t> nO rH en vO O CM CM n>ooiH CO CO IA vO X rH I I ^-~Sf PI VA sf X 'A rH II CO f> IA O X t> rH I rH ^--nO On st CM X t> rH rsinoo^n X C- CM nO C- On t> CO *H rH tS ^A CO CM [S. fr, rH CO \0 O st st On rH O IA st VA vO St rH NO CM st IA IA sf St CO CM On St Sf On On O CO rH St St t> On V\ *A \D \0 nO CM rH CM CM CO m o st O O CO rH rH IA C- CM ^ \D nO O O rH CO en CM St t> CO NO On CM ON O* rH O O. 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Earnings for both groups dropped as the age for retirement was approached. The earnings pattern for high school graduates is similar to that just described but there are important differences. Among whites, there appeared to be no tendency for earnings to decrease with advancing age. Here again, the gains in average earnings were very sharp between ages 20 and 30, moderate between ages 30 and 40, and slight thereafter. Only in the West was there a tendency for the average to fall beyond age 50, and here the drop was slight. The pattern of earnings for nonwhite high school graduates is significantly different from that for whites. In all regions, nonwhite high school graduates have their peak earnings at age 40, and lower incomes as they get older. In some regions, the decreases are significant. In the West, for example, the average for nonwhite high school graduates dropped by one-seventh — from $5,400 for those aged 35 to 44. to $4,600 for those 55 to 64. The pattern of differences between the earnings of white and nonwhite high school graduates is much sharper than the pattern described for elementary school graduates. Many factors are undoubtedly involved; for instance, the kinds of jobs open to high school graduates are more restricted for nonwhites than for whites. When a middle-aged nonwhite high school graduate loses his job, he probably has much more difficulty in finding another job at the same rate of pay than would a white high school graduate. Also, whites may be given preference for positions with increasing responsibility and pay; thus, their earnings tend to increase with age. The greatest difference in the variation of earnings with age between whites and nonwhites is at the college level. Among whites, average earnings doubled between the ages of 20 and 30, increased by more than half between the ages of 30 and 40, and by about 25 percent between the ages of 40 and 50. As the retirement age approached, there was only a slight drop in the average. Nonwhite college graduates also had a substantial increase in average earnings between ages 20 and 40, although their gains were considerably less than those received by whites. In contrast to the pattern for whites, however, the average earnings of nonwhites increased slightly between ages 40 and 50 and fell appreciably during the next 10 years, reflecting the difficulty of nonwhites to maintain their employment and earnings with advancing age. Variation by occupation. Occupations vary greatly in the amount of formal schooling required. Most professional work can be done only by those who have completed 4 years of college and, for many jobs, several years of highly specialized postgraduate work are also required. Although clerical workers need far less education, completion of high school is today generally a minimum requirement for most white-collar jobs. Laborers and operatives, on the other hand, need little schooling or specialized training of any type. Many of the crafts require some high school training plus several years of apprenticeship which are not reflected in the census reports on years of school completed. In view of these 148 INCOME DISTRIBUTION IN THE UNITED STATES considerations, the relationship between education and earnings is quite different in the various occupations. The basic figures bearing on this relationship are shown in table VI-8. In order to remove the effects of age from the data, the figures are shown for men aged 25 to 64, and for those aged 35 to 44. Relatively few occupations in the professional field had appreciable numbers of persons who were not college graduates. In these occupations, however, the earnings of college graduates exceeded those of elementary and high school graduates by a wide margin. Accountants and auditors are a case in point. Those who were elementary or high school graduates averaged about $7,200; college graduates averaged $8,500. Those without college training probably worked at the more routine jobs in which they carried out the functions pre- scribed by men with formal training in accounting. It is undoubtedly true that in this, as in other professions, most of the top jobs require college training. Similar differences were found among engineers and scientists. In these occupations the differential between college graduates and men with less school- ing was considerably greater than in accounting. As for engineers, a relatively small number worked in the profession even though they had never gone beyond the eighth grade, and no doubt some who claimed the title were not actually- doing engineering work. Others may have been bona fide engineers on the basis of experience rather than education. At any rate, in 1959 their average earnings were $7,400; high school graduates earned $8,100 on the average; and college graduates, $9,700. Differences of similar scale prevailed among natural scientists. Farming is an occupation in which earnings are not often thought to be highly associated with education. This impression is incorrect. In 1959, farmers who did not go beyond elementary school earned only $3,200 on the average; high school graduates, about $4,200; and college graduates averaged $6,800. The age distribution of farmers is quite different from that of other occupations. However, as shown in table VI-8, the relationships described above are as valid for the 35-to-44-year age group as for all men in the prime working ages. Although earnings of clerical workers are somewhat less responsive to educa- tion than earnings of most other workers, for the occupation group as a whole they varied appreciably with education, average earnings ranging from $4,800 for elementary school graduates, to $6,400 for those with 4 years or more of college. Within this major group, however, the pattern of earnings was much different for some specific occupations. For example, mail carriers who were elementary school graduates averaged $5,000, and only $400 more if they had completed high school. College men who delivered the mail earned only $5,300. Mail delivery was one of the few occupations in which college graduates earned less than high school graduates. It is possible, of course, that some of the college men in this occupation were part-time workers, and that others had less seniority than men who entered the postal service immediately upon graduation from high INCOME AND EDUCATION 149 school. Even so, however, it is apparent that the limited range of earnings does not permit much of a payment for education. The earnings pattern of postal clerks and shipping clerks was about the same as that of mail carriers. The earnings of craftsmen were most responsive to increases in education — more so than might be expected on the basis of a priori judgment. A question hard to answer is, what, specifically, do bricklayers, plumbers, mechanics, and other craftsmen learn in 4 years of high school that would make their annual earnings considerably higher than those of men in the same trade who never went beyond grammer school? Part of the answer may be that education is associated with general intelligence, and that "years of schooling" is in some measure a proxy variable for aptitude to learn. Another possibility is that even within a given trade, employers or unions give preference to high school graduates in consideration for apprenticeships. Whatever the explanation may be, in every craft for which data are shown, high school graduates earned considerably more than men with only 8 years of schooling. In some occupations — such as line- men, electricians, plumbers, and mechanics — college training also seemed to pay off, while in others, there seemed to be no added reward for higher education. Considering the occupation group as a whole, craftsmen who did not go beyond the eighth grade averaged $5,200 in 1959; high school graduates, $6,100; and college graduates, $8,100. The fact that the overall average for college grad- uates is higher than that shown for any specific craft within the group indicates that most craftsmen with college training work at jobs other than those shown in table VI-8. A large proportion are foremen. The highest paid workers in the building trades are electricians. Their earn- ings ranged from $6,100 for elementary school graduates, to $6,800 for college graduates. Overall, plumbers earned somewhat less than electricians, a differ- ence due partly to the fact that plumbers on the average have considerably less education; those who were elementary school graduates earned about $500 less than electricians with the same years of schooling. However, plumbers who were high school graduates earned as much as electricians with equal education, and college graduates earned considerably more. Plasterers without much edu- cation earned considerably less than plumbers; however, those who were high school graduates had average earnings only about $100 less than plumbers. Painters and carpenters earned far less than other men in the building trades regardless of the years of schooling they had completed. Even among semiskilled and unskilled workers there was a close association between earnings and education. Among operatives, for example, elementary school graduates averaged $4,700; high school graduates, $5,300; and college graduates, $5,800. Bus drivers with 4 years of high school averaged $700 a year more than elementary school graduates; for truck drivers the differential was $600; and for miners, $1,000. 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E « C ^1 OS O rH -H 03 O O W ►J •H C -H TH 5 Cm vOnOVAnOnOnO nOVAVAnOnCC^ VAVAIAVAVA VAIAnOVA nOVAVAnOnOnO VAVA>J1AnOC- VA^f^J-VAVA >J->JVAVA e 3 On rH Cm vO VA vO VAVA^nOnOnO VAVA>JVAnOO -vf-vf-vf-vt^f n» n| lf\ »> ■ a cn C •f o a c s 8.3 §03 a - 3 — ■ « s 8 a s - ~ c/3 o — cn a M a 3 a 33 - ■s s s o Oh CO .2 E I 1 I I a; VU I 2 ? •s? 8 3 o 00 INCOME AND EDUCATION 153 The patterns described for all workers applied to whites and nonwhites alike, with this major difference: nonwhites in every occupation earned far less than whites with the same amount of schooling. The fact is that in every major occupation except farming, nonwhite high school graduates on the average earned less than whites who did not go beyond the eighth grade. This pattern prevailed not only in the South, where discriminatory patterns are deeply en- trenched and openly admitted, but also in the North where discrimination has been far more muted. The relationship between earnings and age varies considerably by occupation. In most professional and managerial jobs — which tend to offer the greatest security and the best opportunities for advancement to positions of increasing responsibility — incomes tend to rise regularly until about age 50, when a plateau is reached and maintained until retirement. Workers in these jobs are generally paid annual salaries rather than weekly or hourly wages; thus their earnings are not diminished because of the periodic illnesses which frequently afflict older people. Clerical workers, for many of the same reasons that apply to professionals, also tend to maintain their incomes as they approach retirement. Their peak, however, comes earlier — around age 40. The main reason that their earnings do not continue to increase between ages 40 and 50 (as in the case of profes- sionals) is that opportunities for advancement are more limited. For craftsmen, operatives, and lower paid workers, earnings rise rapidly in the early years, reaching a peak when the men are around age 40, and showing a distinct tendency to decline in the older age groups. The relationships just described are shown graphically in figures VI-2 to VI-5. Figures for engineers who are college graduates show that their earnings rose by 70 percent (from $4,800 to $8,200) between the ages of 20 and 30, with an increase of 28 percent (to $10,400) between ages 30 and 40, and a further rise of 10 percent (to $11,500) by age 50. This peak was maintained until about age 60. The same general pattern was found for accountants, college professors and instructors, lawyers, natural and social scientists, and physicians. For dentists the earnings pattern differs significantly from that for other professions. Dentists had their peak earnings at age 40; during the next 10 years their average dropped by about 12 percent, and by age 60 their earnings were no higher than during the early years of practice. The decline in earnings with age in this occupation may be partly due to physical factors which cause an earlier reduction in work schedules than in most other professions. The pattern of earnings for managerial workers in public administration is about the same as that for other professional workers, although the earnings of managers and officials in private industry continued to increase to age 60. 154 INCOME DISTRIBUTION IN THE UNITED STATES Figure VI-2.— Earnings of Engineers, by Education and Age: 1959 Average (mean) earnings $10,000 $8,000 $6,000 $4,000 $2,000 ' | | 15 25 1 1 35 45 AGE 55 65 Source. 1960 Census of Population, Subject Reports, Occupation by Earnings and Education, Series PC(2)-7B, tables 1 and 4. Figure VI-3.— Earnings of Clerical Workers, by Education and Age: 1959 Average (mean) earnings $10,000 $8,000 $6,000 $4,000 $2,000 Co llege graduate s High school graduates \ : Elementary school graduates i I I 15 25 35 45 55 65 AGE Source: i960 Census of Population, Subject Reports, Occupation by Earnings and Education, Series PC(2)-7B, tables 1 and 4. INCOME AND EDUCATION 155 Figure VI-4.— Earnings of Salesmen and Sales Clerks (n.e.o, by Education and Age: 1959 Average """"" ™— — — — — — — (mean) $8,000 $6,000 $4,000 $2,000 1 ■ ' 1 1 I I I 15 25 35 45 55 65 AGE Source: 1960 Census of Population, Subject Reports, Occupation by Earnings and Education, Series PC(2)-7B, tables 1 and 4. Figure VI-5.— Earnings of Carpenters, by Education and Age: 1959 Average (mean) earnings $8,000 $6,000 $4,000 $2,000 / / ■ 1 15 High school graduates Elementary school graduates 25 35 45 AGE 55 65 Source: 1960 Census of Population, Subject Reports, Occupation by Earnings and Education, Series PC(2)-7B, tables 1 and 4. 156 INCOME DISTRIBUTION IN THE UNITED STATES Among clerical workers who were high school graduates, earnings rose sharply (from $3,000 to $5,000) between ages 20 and 30, with a further rise of about $700 between ages 30 and 40. The peak of $5,700 reached at age 40 was maintained until retirement. This same general pattern applied to bank tell- ers, bookkeepers, mail carriers, and office machine operators. The earnings of postal clerks showed a slight tendency to rise in the older age groups. The earnings of shipping clerks, on the other hand, showed a distinct tendency to decline in the older age groups, reflecting the insecurity of employment among older people and their greater difficulty in finding reemployment. The earnings of sales workers show only a slight tendency to decline as they grow older. Earnings of salesmen who were elementary school graduates rose progressively from $2,600 at age 20, to $4,600 at age 30. At age 40 their earn- ings averaged $5,200, and at age 50, about $5,600. This peak was maintained through age 60. Salesmen who were college graduates had about the same pattern, but their earnings were, of course, much higher. High school graduates also had a similar pattern, but their earnings fell off slightly about the age of 60. The earnings of foremen behave very much like those of professional workers, but on a much lower level. Earnings rise until about age 50, when they reach a plateau which is maintained until retirement. Craftsmen, however — almost without exception — tended to experience declines in earnings once they had passed their fortieth birthday. For example, the mean earnings of car- penters who were high school graduates rose from $5,400 at age 30, to $5,700 at age 40; but those aged 50 earned only $4,900 on the average; and those aged 60, only $4,500. This pattern was more or less typical of most other occupations. The reasons for the declines in earnings among craftsmen (and other blue- collar workers) are not hard to find. Payment in these occupations is typically on an hourly basis; not to work is not to earn. Furthermore, as men reach their fifties and sixties they tend to have more frequent illnesses, and as a result their earnings suffer. And in many of these occupations there is no tenure. Work on a construction project, for instance, lasts until the project is com- pleted, after which a new job must be found. Where employers have a choice, they are often likely to select younger workers for the job. The variation of earnings with age for operatives, service workers, and laborers was very similar to that for craftsmen. Changes since 1939. The educational attainment of the population has increased considerably during the past 20 years. The proportion of college graduates has nearly doubled, and the proportion of high school graduates has also risen dramatically. Census data suggest that the increase in the relative supply of more highly educated workers has not had any marked effect on income differentials. The incomes of college graduates, in particular, do not appear to have gone down relative to other groups in the population, because INCOME AND EDUCATION 157 of the greater increase in their number, suggesting that the demand for their services has kept pace with the increased supply. In 1949, Seymour Harris — noting the rapid rise in the extension of higher education— expressed concern lest the persistent increase in the supply of college-trained workers would so flood the market that college students within the next 20 years are doomed to disappointment after graduation, as the number of coveted openings will be substantially less than the numbers seeking them. 15 This concern, expressed by several other noted educators, including James B. Conant, 16 has not been borne out by the experience of the fifties and sixties. Nonwhites in particular have experienced dramatic changes since World War II. Migration and technological change have altered the dominant role of the nonwhite from that of a southern farm wageworker or sharecropper to that of a low-paid industrial worker. In 1940, about three-fourths of all nonwhite males 14 years old and over lived in the South, where they were largely engaged in agricultural pursuits. 17 By 1950, the proportion residing in the South dropped to about two-thirds, 18 and in 1960 the proportion was slightly more than half. 19 Even in the South, nonwhites are now more con- centrated in urban areas than ever before. The figures on the occupational distribution of nonwhite males tell the story even more dramatically. In 1940, 4 out of every 10 employed nonwhite males in the United States worked either as laborers or sharecroppers on southern farms. 20 In 1960, fewer than 2 out of every 10 nonwhites were employed in agriculture, about half working as either unskilled or semiskilled workers at nonfarm jobs. 21 The change in the occupational status of non- whites has been accompanied by a marked rise in educational attainment — proportionately far greater than for whites. Among men in the 25-to-29-year age group — and these are the ones most likely to have benefited from recent advances in education — the median years of school completed for nonwhites increased by about two-thirds, from 6.5 years in 1940, to 10.9 years in 1960. The increase for whites in the same age group was only about one-fifth, from 10.5 years in 1940 to 12.5 years. In 1940, the average young nonwhite male was about 4 years behind the average white in his schooling. This gap was narrowed to only \y 2 years by 1960. The most dramatic advances in schooling among nonwhites have come at the lower elementary grades. In 1940, one-third of the young nonwhite males had completed less than 5 years of school. This proportion has been reduced to only 8 percent and is largely responsible for the striking reduction in illiteracy among nonwhites. 22 Gains in education among nonwhites were by no means restricted to the lower grades. Since 1940, the proportion of high school graduates among young nonwhite men has risen fourfold, from 10 percent to 40 percent; and the proportion of college graduates has more than tripled. 158 INCOME DISTRIBUTION IN THE UNITED STATES In view of these very substantial increases in educational attainment, it is interesting to note the changes which have taken place in the association between education and income. In order to bring more light to bear on the subject, data from three decennial censuses and four Current Population Surveys covering the period 1939 to 1961 have been assembled as a time series. The basic results are shown in table VI-9, with derived measures presented in table VI-10. Since neither the income concept nor the population is directly comparable for all the years shown, the figures in table VI-9 represent only rough measures of change. Except for 1939, however, most of the differences are relatively small and are not likely to distort relationships seriously. For example, the figures for 1956, 1958, and 1961 are entirely comparable, since they are based on the Current Population Survey and represent the total money income of the civilian noninstitutional male population 25 years old and over. The 1959 figures are based on the 1960 Census, and represent total money earnings, and are restricted to males 25 to 64 years old. The 1949 figures are based on the 1 950 Census and also represent the total money income of all males 25 years old and over, including a relatively small number of insti- tutional inmates. The 1946 figures are based on the Current Population Survey and represent the total money earnings (not total income) of the civilian noninstitutional male population 25 years old and over. Although the con- ceptual differences between income and earnings are substantial, the actual differences in the averages are usually quite small. The figures for 1939 are based on the 1940 Census and are restricted to males 25 to 64 years of age with $1 or more of wage or salary income and less than $50 of nonwage income. For this group, of course, the averages represent total money income; however, the universe has been restricted, because of the way in which the data were collected, to those persons who received only wage or salary income. Only about three-fifths of all men 25 to 64 years old in 1940 were in this category. The effects of this restriction cannot be measured, but it is undoubt- edly more important than restrictions cited for other years. It is also possible that the restriction affects college graduates more than persons with less school- ing, since college graduates are more likely to have income other than earnings. 23 The figures in table VI-10 suggest that elementary school graduates, despite the reduction in their relative numbers, had smaller relative income gains than high school graduates. In contrast, the income differential between high school and college graduates has remained fairly constant over time. In the absence of 1939 income data for elementary school graduates, com- parisons between the incomes of elementary and high school graduates must be restricted to the period since 1946 If attention is focused on these years, it is evident that the incomes of high school graduates have risen more rapidly than those of elementary school graduates. In 1946, the incomes of elementary school graduates were 79 percent of those received by high school graduates. This ratio dropped to 70 percent in 1956 and has remained at about the same INCOME AND EDUCATION 159 Table VI-9.— Average (Mean) Income (or Earnings) For Males 25 Years Old and Over, by Years of School Completed and Age, for Selected Years, 1939 to 1961 Years of school completed and age 1961 1 1959 2 1958 1 1956 1 1949 1 1946 2 1939 3 25 YEARS OLD AND OVER Elementary: Total $J, 544 (NA) $3 , 043 $3 , 041 $2,394 $2,041 $1,036 O QQ(J (NA) 2; 530 2, 574 2,062 1 ,738 (NA) J nnt 4 , ^UD /ma \ (NA) jfbtf 3,631 2, 829 2,327 (NA) High school : 1 to 3 years. 5, 161 (NA) 4,452 4,367 3,226 2,449 (NA) 4 years . 5,946 (NA) 5, 257 5,183 3,784 2,939 (NA) College: 1 to 3 years, . . 7,348 (NA) 6,272 5,997 4,423 3,654 (NA) 4 years or more . . 9,817 (NA) 8,643 7,877 6,179 4,527 (NA) 25 TO 34 YEARS OLD Elementary: Total J, PU4 /via \ ■"3 1 Of? 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It appears therefore that the major discrepancy between the Census and OBE self-employment estimates centers in income from nonfarm self-employment. Both the CPS and the Census estimates show some improvement relative to the OEE totals between 1949 and 1959. One possible reason for this improve- ment is the increased importance of wages and salaries as a part of total income. This type of income rose from 67 percent of the total in 1949 to 71 percent in 1959. Since wages and salaries are much more completely reported in the censuses than is unearned income, this change alone — other things being equal — would result in a reduction in the underreporting of income in the census. In table A-4 an attempt is made to ascertain whether there is any relationship between the improvement shown for each State and the change in the relative Table A-4.— Wage or Salary Income in 1959 and 1949 as a Percent of Total Money Income, by Regions, Divisions, and States Region, division, and State 1959 1949 Region, division, and State 1959 United States... REGIONS: Northeast North Central South West NORTHEAST: New England Middle Atlantic... NORTH CENTRAL: East North Central West North Central SOUTH: South Atlantic . . . . East South Central West South Central WEST: Mountain Pacific NEW ENGLAND: Maine New Hampshire Vermont Massachusetts Rhode Island Connecticut MIDDLE ATLANTIC: New York New Jersey Pennsylvania EAST NORTH CENTRAL: Ohio Indiana Illinois Michigan Wisconsin 71 67 73 71 69 69 72 73 74 63 70 69 67 67 70 67 71 67 73 71 74 72 75 73 75 75 74 75 70 72 67 64 64 71 72 72 56 68 63 60 60 65 65 68 64 72 70 72 71 75 73 72 71 71 75 67 WEST NORTH CENTRAL: Minnesota Iowa Missouri North Dakota South Dakota Nebraska Kansas SOUTH ATLANTIC: Delaware Maryland District of Columbia Virginia West Virginia North Carolina South Carolina Georgia Florida EAST SOUTH CENTRAL: Kentucky Tennessee Alabama Mississippi WEST SOUTH CENTRAL: Arkansas Louisiana Oklahoma Texas MOUNTAIN: Montana Idaho : . . Wyoming Colorado New Mexico Arizona Utah Nevada PACIFIC: Washington Oregon California 67 59 68 52 49 58 61 68 76 67 75 73 69 71 72 62 67 71 71 62 59 69 64 68 58 62 63 66 70 69 73 72 70 66 70 Source: Derived from tables A-3 and A-5. EVALUATION OF CENSUS INCOME DATA 181 importance of wages and salaries in that State. It is quite clear that although such a relationship does exist in most cases, there are many important excep- tions. For example, each of the Middle Atlantic States shows a reduction in the underreporting of income between the 1950 and 1960 Censuses, but no appreciable change in the ratio of wages and salaries to total income. The same was true for Massachusetts and Michigan. In these cases, at least, it appears that the improvement resulted from other factors than the reweighting of the components of income. A check was made to see if the substitution procedure used in the 1960 Census was in any way responsible for the improve- ment in each of the above States. The check was made by estimating an aggregate for persons reporting on income, before substitution for nonresponse, using the data shown in 1960 Census of Population, Detailed Characteristics, Final Report, PC ( 1 ) , table D-l for each State. In each case it was found that the substitution procedure had no major impact on the results. In Connecticut, for example, the aggregate based on the published figures (i.e., after allocation for nonresponse using computer tech- niques) was $6.0 billion, whereas the estimate based on cases reporting on income, using a substitution procedure similar to the one employed in 1950, was somewhat higher, $6.2 billion. In other words the more refined substitu- tion procedure introduced in the 1960 Census tended to lower the aggregate, implying that income nonrespondents in the census had characteristics asso- ciated with lower-than-average income recipients. Similar results were obtained for New York, New Jersey, Pennsylvania, Massachusetts, and Michigan. Table A— 5 was prepared primarily to show for each State the difference be- tween the estimates of aggregate total money income obtained in the 1950 Cen- sus from the data for families and unrelated individuals and from the data for persons. The only figures previously shown were national totals. In every State the aggregate based on the data for persons exceeds that based on the family figures. Most of the differences were in the neighborhood of 10 per- centage points. For 38 of the States, the aggregates for persons exceeded the family figures by 8 to 11 percentage points. In only 1 State, Vermont, was the difference less than 5 percentage points. Comparability of Census and OBE income distributions. Although the trends exhibited by the Census and OBE income distributions are very similar (see chapter I), the level of the Census data is far below that of OBE. Some of this difference is more apparent than real and is due to the use of different income concepts in the two series. But, even when rough allowance is made for this fact, the difference in level remains substantial. Table A-6 shows 1959 income distributions for families and unrelated indi- viduals based on three sources: OBE, the 1960 Census, and the March 1960 CPS. These fi gures clearly show that the greatest differences between the OBE and the Census data occur at the extremes of the distribution. The 1960 Census data show 13.6 million families and individuals with total money income under $2,000, compared with 12.1 million in the March 1960 CPS, and 7.5 million 182 APPENDIX A Table A-5.— OBE Estimates of Total Money Income in 1949 by Type, and 1950 Census Estimates of Total Money Income in 1949 Based on Figures for Families and Unrelated Individuals and Persons 14 Years Old and Over, by Regions, Divisions, and States [Millions of dollars] Region, division, a tlu o 0a l/c OBE Census Total income Wage or salary income Self- employ- ment income Inc ome other than earnings Income of families and unrelated individuals Income of persons 14 years old and over Total Percent of OBE Total Percent of OBE $190,737 $128,561 $31,254 $30,922 $156,094 82 $173,261 91 58,34-3 41,963 6,549 9,831 45,719 78 51,320 88 60,047 40,223 11,068 8,756 49,099 82 54,341 90 «?+. Smith flpnt.Tfll 14,856 8,878 3,388 2,590 12,646 85 13,844 93 WEST: 6,031 3,600 1,466 965 5,266 87 5,740 95 Pacific 22,271 14,450 3,924 3,897 18,512 83 20,512 92 NEW ENGLAND: 962 623 157 182 755 78 860 89 Mpu Wq rrrn T T"P 608 411 74 123 505 83 543 89 380 242 61 77 321 84 325 86 6,561 4,741 641 1,179 5,212 79 5,824 89 1,091 761 101 229 804 74 890 82 3,229 2,321 343 565 2,455 76 2,781 86 MIDDLE ATLANTIC: 24,379 17,330 2,773 4,276 18,892 77 21 , 206 87 7,418 5,528 864 1,026 6,094 82 6,849 92 Ppnri qv 1 \roni a 13,715 10,006 1,535 2,174 10,681 78 12,042 88 EAST NORTH CENTRAL: Ohio 10,986 7,862 1,444 1,680 8,886 81 9,891 90 5,052 3,568 858 626 4,140 82 4,545 90 13,820 9,814 1,998 2,008 11,139 81 12,319 89 8,955 6,706 1,076 1,173 7,335 82 8,136 91 Wisconsin 4,243 2,836 790 617 3,562 84 3,959 93 WEST NORTH CENTRAL: 3,567 2,159 870 538 3,087 87 3,416 96 3,304 1,555 1,215 534 2,742 83 2,980 90 4,862 3,107 955 800 3,784 78 4,253 87 North Dakota 678 294 282 102 586 86 636 94 South Dakota 730 302 338 90 612 84 666 91 1,623 810 565 248 1,305 80 1,444 89 2,227 1,210 677 340 1,921 86 2,096 94 SOUTH ATLANTIC: Delaware 550 355 68 127 340 62 397 72 3,132 2,237 391 504 2,545 81 2,837 91 District of Columbia.... 1,567 1,138 132 297 1,290 82 1,401 89 3,197 2,303 418 476 2,915 91 3,173 99 1,876 1,417 191 268 1,550 83 1,718 92 North Carolina 3,188 2,052 645 491 2,771 87 3,089 97 South Carolina 1,492 1,014 233 245 1,279 86 1,447 97 2,757 1,839 465 453 2,306 84 2,577 93 Florida 2,943 1,772 590 581 2,626 89 2,868 97 EAST SOUTH CENTRAL: Kentucky 2,324 1,458 485 381 2,028 87 2,229 96 2,694 1,755 473 466 2,305 86 2,535 94 2,181 1,442 377 362 1,869 86 2,078 95 Mississippi 1,288 665 391 232 1,028 80 1,155 90 1 Excludes Alaska and Hawaii. EVALUATION OF CENSUS INCOME DATA 183 Table A-5.-OBE Estimates of Total Money Income in 1949 by Type, and 1950 Census Estimates of Total Money Income in 1949 Based on Figures for Families and Unrelated Individuals and Persons 14 Years Old and Over, by Regions, Divisions, and States— Con. [Millions of dollars] OBE Census Region, division, and State Total income Wage or salary income Self- employ- ment income Income other than earnings Income of families and unrelated individuals Income of persons 14 years old and over Total Percent of OBE Total Percent of OBE WEST SOUTH CENTRAL: $1,316 2,566 $682 $410 $224 $1,096 83 $1,236 94 1,590 463 513 2,053 80 2,272 89 2,216 1,259 535 422 1,954 88 2,171 98 8,758 5,347 1,980 261 1,431 7,543 86 8,165 93 MOUNTAIN: 812 434 117 677 83 726 89 647 370 188 89 588 91 655 101 406 257 91 58 358 88 387 95 1,656 965 382 309 1,448 605 87 1,561 94 661 385 169 107 92 664 100 828 499 189 140 702 85 773 93 Utah 763 524 136 103 670 88 728 95 258 166 50 42 218 84 246 95 PACIFIC: 3,360 2,207 596 557 2,900 86 3,169 94 2,098 1,332 458 308 1,803 86 1,978 94 16,813 10,911 2,870 3,032 13,809 82 15,365 91 Source: OBE data prepared by the Office of Business Economics. Census data based on unpublished tabu- lations of the Bureau of the Census. Table A-6.— Comparison of Census, CPS, and OBE Numbers of Families and Unrelated Individuals, by Income Levels in 1959 [In millions] Income level Family personal income OBE Total money Income Census CPS FAMILIES AND INDIVIDUALS Total 55.3 58.3 55.8 Under $2,000 7.5 11.4 12.5 15.5 8.4 44.8 13.6 10.9 12.1 14.7 7.0 45.1 12.1 11.1 12.6 14.3 5.7 45.1 $2,000 to $3,999 $4,000 to $5,999 $6,000 to $9,999 $10,000 and over FAMILIES Total Under $2,000 3.5 7.6 10.7 14.8 8.2 5.9 8.0 10.5 13.9 6.8 6.0 8.8 11.2 13.6 5.5 $2,000 to $3,999 $4,000 to $5,999 $6,000 to $9,999 $10,000 and over Source: OBE data from Maurice Liebenberg and Jeannette M. Fitzwilliams, "Size Distribution of Income in 1961," Survey of Current Business, April 1962; 1960 Census data from 1960 Census of Population, Vol. I, Charac- teristics of the Population, Part I, U.S. Summary, table 95; and CPS data from U.S. Bureau of the Census, Current Population Reports— Consumer Income, Series P-60, No. 35, table 5. 184 APPENDIX A in the OBE distribution for family personal income. A part of this difference is attributable to the larger number of unrelated individuals who were counted as separate units in the decennial census, but counted either as part of family groups, or entirely excluded, in the March 1960 CPS and in OBE. The 1960 Census includes 2.7 million more unrelated individuals than the OBE estimates and many of these were undoubtedly included in the lower income levels. All three series agree very closely with respect to the total number of families. The 1960 Census and CPS distributions show about the same number of families with total money incomes under $2,000 (about 6 million), but a considerably smaller number is shown in OBE — 3.5 million. Because of differences in the definition of income, these numbers are not, of course, directly comparable. Adjustments which were made to increase the comparability between the two series are described in table A-7. At the upper end of the distribution there were large differences among the three sources of information. The March 1960 CPS shows 5.5 million families with total money incomes over $10,000, compared with 6.8 million in the 1960 Census, and 8.2 million in OBE. These figures suggest at least two separate problems: Why are the CPS and 1960 Census estimates of the number of high- income families so far below the OBE estimates? And why are the CPS esti- mates so different from the 1960 Census figures? The first question is discussed below; and the second in a later section of this appendix, where CPS and Census income distributions are compared. The OBE figures are prepared quite independently of the Census data. The rather complicated procedure used to prepare the OBE estimates, explained in detail elsewhere, 4 basically involves combining Federal individual income tax Table A-7.— Adjustments to Family Money Income in 1959 to Obtain Family Personal Income [Millions of dollars] Family personal income $365,432 Family money income 351,398 Difference $14,034 Deductions from family money income Wages and salaries: Employee contributions to Social Security.... $7,322 Nonfarm business: Contributions to Social Security 433 Inventory valuation adjustment 139 Farm income: Contributions to Social Security 158 Rent: Roomer and boarder income 780 Miscellaneous: Periodic payments from life insurance 1,552 A: liticr.s tc fa.-rJ.ly rr.cr.ev i~zz~e Nonmoney wages: Farm $09 Nonfarm 1,434 Nonfarm business: Imputed profits 457 Farm business: Inventory change 92 Nonmoney food 971 Nonmoney housing 1,971 Interest: Imputed 10,066 Accrued interest on U.S. Bonds 238 Rent: Imputed rent on nonfarm owner-occupied homes 6,153 Miscellaneous: Lump sum payments from Social Security and National Service Life Insurance 741 Busir.ess transfer payments to individuals 1,441 Nonmoney workmen's compensation 415 $24,418 Source: Unpublished data of the Office of Business Economics. EVALUATION OF CENSUS INCOME DATA 185 returns into family units; and adjusting the income distributions based on these units to include (a) families that did not file tax returns, and (b) types of income not required to be reported on tax returns. Finally, the amounts of income that are reported are adjusted to agree with control totals used in the personal income series. Since both census and survey data are subject to some underreporting of income, it is to be expected that the OBE distributions, which are based on aggregates adjusted to equal the totals shown in the national income accounts, will have fewer families at the bottom of the distribution and more at the top. So long as the difference between CPS and OBE aggregate money income is in the neighborhood of 15 percent, fairly large differences in the distributions by income levels can be expected. The 1960 Census aggregates, however, are within 5 percent of the comparable OBE money income total; yet the difference in the distribution by income levels remains quite striking. This suggests the possibility that the results pro- duced by the OBE adjustment procedure may be in error, especially since a major part of the operation is based on relationships established about 15 years ago. The thought is not a new one; and it has caused concern for some time to those who are most familiar with the details of the adjustment procedure. According to Selma F. Goldsmith, who worked on both series, Since the OBE procedure for the entire postwar period has been linked to the 1946 findings, it is possible that when relationships from the newly available CPS data for 1959 are incorporated by the OBE, the number of nonfarm families in the lower income range may be larger than is now the case. 5 An attempt was made in table A-8 to place the 1960 Census and the OBE income distributions on a roughly comparable basis by adding to the Census distribution the estimated amount of money income missed in the census, as well as the income included in OBE family personal income data but not in the v census data. The procedure involved numerous assumptions and the following steps: First, an estimate was made of the aggregate money income included in the census. This amounted to $331.7 billion ($317.1 nonfarm and $14.6 farm) compared with an OBE estimate of $353.1 billion. Thus it was estimated that $20.3 billion in money income would have to be added to the Census distribution to account for missing money income. In addition, the OBE data contain $14.0 billion other income (largely nonmoney income), included in the family personal income concept but not in family money income. This amount also had to be added to the Census distribution, making a net addition of $34.3 billion. The next question was how to distribute the missing income by income levels. To find the answer, the items that must be adjusted in making the transition from family money income to family personal income were examined; this was done for the purpose of finding out whether any differential pattern of adjust- ment by income level was warranted. Table A-7 summarizes the items in- volved in this adjustment for 1959. Note that $10.4 billion, consisting largely of employee contributions to Social Security, must be deleted from the Census 186 APPENDIX A Table A-8.— Comparison of Census and OBE Estimates of Families and Unrelated Individuals, by Family Personal Income in 1959 [In millions] Family personal incomes- Families and unrelated individuals OBZ Census OBE Census Total Under $2,000 $2,000 to $3,999 $4,000 to $5,999 $6,000 to $9,999 $10,000 and over 55.3 58.3 — .? 45.1 7.5 11.4 12.5 15.5 8.4 12.0 10.0 10.8 16.5 9.0 3.5 7.6 10.7 14.9 8.3 4.8 7.1 9.0 15.5 8.7 1 See text for explanation of family personal income. Source: OBE data from Liebenberg and Fitzwilliams, op. cit.; census data based on unpublished data of the 1960 Census. data to cover items included in money income but not in family personal income. On the other hand, $24.4 billion must be added to the Census data to include items consisting largely of nonmoney or imputed income that are excluded from the money income concept. About $16 billion, or two-thirds of the total, consists of imputed interest or imputed rent on nonfarm owner-occupied homes. A relatively small part of the total ($3.4 billion) represents the value of food produced and consumed on farms or the rental value of farm housing. Examination of these data led to the preparation of separate adjustments for farm and nonfarm families and individuals. An estimate of the aggregate money income of farm families and unrelated individuals in the Census dis- tribution was found to be about $14.8 billion. Imputed farm income is esti- mated by OBE at $3.3 billion (see table A-7). The Census distribution of money income was inflated to include this $3.3 billion of imputed income by assuming a 100-percent increase in the dollar limit of the two lowest income levels (under $1,000, and $1,000 to $1,999), a 50-percent increase in the next two levels ($2,000 to $2,999, and $3,000 to $3,999) , a 25-percent increase in the $4,000 to $4,999 level, and a 10-percent increase in the $5,000 to $5,999 level. No imputed income was added to income levels above $6,000. These assumptions are undoubtedly incorrect because some imputed income, particularly the value of farm housing, accrues to the higher income groups. It is also unlikely that half the farm families and unrelated individuals with money income under $2,000 are in fact moved to a higher income level by the addition of imputed income. These assumptions were deliberately made extreme to see whether the adjustment for imputed income could possibly reduce the great difference between the Census and OBE estimates of the number of low- income families. For this reason, assumptions were used that favored the allocation of income to the lower income groups. On the basis of the available data, no logical basis could be found for dis- tributing the nonfarm imputed income or the missing money income. It seems reasonable that much of the nonfarm imputed income accrues disproportionately to the upper income groups rather than to those with incomes under $2,000. EVALUATION OF CENSUS INCOME DATA 187 Imputed interest largely goes to the holders of checking accounts. This $10 billion item of imputed income must surely be disproportionately allocated to higher income families. Since homeowners have higher average incomes than renters, it is also likely that a very small share of another major item of imputed nonfarm income — $6 billion of imputed rental to nonfarm homeowners — goes to families with incomes under $2,000. In balance it appeared that the most reasonable distribution of nonfarm imputed income would be a disproportionate allocation in favor of the upper income groups. However, in order to inflate the estimate for the lower income groups as much as possible, the nonfarm imputed income and the missing money income were allocated proportionately by income level. Table A-8 shows that when rough allowance is made for conceptual differ- ences between the two series, the OBE figures tend to understate the number in the low-income groups. The 1960 Census estimates of families and unre- lated individuals with incomes under $2,000 is 12.0 million, compared with 7.5 million for OBE. Even if it is assumed that all 2.7 million unrelated individuals included in the Census but not in OBE had incomes under $2,000 — which is unlikely since most of them were Armed Forces members whose annual pay, including income in kind, typically exceeds $2,000 — the difference between the two series is 1.5 million. If the comparison is restricted to families alone, the Census estimate of the number with incomes under $2,000 exceeds OBE by 1.3 million, or about one-third. In order to obtain an income distribution for the CPS that is consistent with the OBE estimate of aggregate family personal income, an adjustment procedure was also applied to that survey. In the March 1960 CPS each person 14 years old and over was asked to report the amount of cash income received during 1959 from each of the following sources: wages and salaries; net income from nonfarm self-employment; net income from farm self-employment; rents, roy- alties, estates, and trusts; Social Security; private pensions, and veterans' pay- ments; and all other sources including unemployment compensation, public and private assistance, workmen's compensation, etc. The answers were sum- marized on a family basis and a tabulation was made showing the estimated amount of each type of income obtained in the CPS. A summary comparison of CPS and OBE aggregates of each type of money income is shown in table A-9. Using these figures, the amount of income reported by each family in the CPS was adjusted by a factor intended to yield in the aggregate the OBE esti- mate of each type of money income. (Actually, the adjusted CPS aggregate was somewhat greater than the OBE control. See footnote to table A-9 for explanation.) Thus, each reported amount of wage and salary income was multiplied by 109, each nonfarm self-employment amount was multiplied by 122, etc. The new amounts for each type of income were then summed for each family and a new estimate of family money income was obtained. The data were then retabulated by income level to obtain the figures shown in table A-10. 188 APPENDIX A Table A-9. -Estimated Amount of Aggregate Money Income in 1959, by Type, Based on Data from the CPS and the OBE [In billions] # Type of income OBE CPS Ratio of OBE to CPS Total $351.4 1 $294.5 119 Wages or salary Income 249.1 228.9 109 Nonfarm self -employment income 34.1 28.0 122 8.2 5.6 147 25.5 7.2 353 6.5 4.3 149 Social Security, veterans' payments, 16.0 15.1 106 12.1 5.4 226 ' Table A-l shows a CPS aggregate total money income of $306.7 billion for 1959, as compared with $294.5 billion shown here. The aggregate in table A-l was obtained from the published distributions by total money income levels, whereas the source pattern aggregate shown here was obtained from a special tabulation. The difference of $12 billion was due to the fact that somewhat different methods were used to obtain the two estimates. One complication that stems from this fact is that when CPS data were adjusted to OBE control totals as described in the text, the money income distribution totaled to more than $351 billion which was used as the control. As a result, families and unrelated individuals in the adjusted CPS income distribution are classified at somewhat higher levels than they should be. Thus the number of low-income families in the adjusted CPS distribution is somewhat understated. Note: See text for explanation of aggregate money income. Source: Unpublished data of the Bureau of the Census and the Office of Business Economics. Table A-10.— Comparison of Census and CPS Estimates of Families and Unrelated Individuals, by Adjusted Money Income in 1959 [In millions. Income levels adjusted to include estimated amount of money missed in the 1960 Census and CPS results] Adjusted money income 1 Families and unrelated individuals Families Census CPS Census CPS Total Under $2,000 $4,000 to $5,999 $6,000 to $9,999 58.3 55.8 45.1 45.1 13.0 10.4 11.4 15.4 8.2 8.0 10.0 12.0 16.5 9.1 5.5 7.5 9.7 14.5 7.9 3.9 6.8 10.2 15.5 8.6 1 See text for explanation of adjusted money income. Note: OBE data not shown; available only by family personal income level, not by money income level. Source: Unpublished data of the 1960 Census and the March 1960 CPS. In order to understand the significance of table A-10, it is important to recall that the 1960 Census data failed to include only $20 billion in money income, and that this income was added to the distribution in a very crude way (i.e., proportionately at each income level) . On the other hand, the CPS data did not include much more money income — $45 billion to be exact — but this income was added to the distribution by a much more sophisticated pro- cedure. It is clear from table A-10 that the two distributions are quite dif- ferent even though both now add to about the same aggregate income. The 1960 Census data have many more families and unrelated individuals at the lower income levels. The question is: Which of these distributions is more correct — the Census data with the larger initial aggregate and crude adjust- ment procedure, or the CPS data with the far smaller initial aggregate and a EVALUATION OF CENSUS INCOME DATA 189 more sophisticated adjustment procedure? Although there is no objective answer, a better case can be made for the 1960 Census data because they required much less adjustment. In order to compare the CPS and OBE data it was necessary to inflate the adjusted CPS money income figures in table A-10 to family personal income. This adjustment was made in much the same way as that used to obtain total money income, which has been described in the discussion pertaining to table A-9. The adjusted money income figures were processed using the factors shown in table A— 11. These factors were obtained by adding to and subtract- ing from each type of income the appropriate item from table A— 7. One ex- ception, however, should be noted: imputed rent from nonfarm owner- occupied housing was added to wages and salaries rather than to rental income, on the assumption that income from this source is widely distributed through- out the population, and, unlike rent, is not highly concentrated. Table A-l 1 .—Adjustment Factors to Inflate Family Money Income to Family Personal Income [In billions] Family Family Type of income money personal Ratio income 1 income $249.1 $249.9 1.0003 34.1 34.1 1.0000 8.2 10.9 1 . 3293 25.5 35.8 1.4039 6.5 5.7 .8769 Social Security, veterans' payments, and 16.0 16.0 1.0000 12.1 13.0 1.0744 1 See text for explanation of family money income. Source: Unpublished data of the Bureau of the Census. Table A-l 2 shows CPS and OBE figures for families and unrelated individ- uals distributed by family personal income. There is reasonably close agree- ment between these two sets of numbers — particularly at the extremes of the distribution — although the CPS data show a somewhat larger number of low- income families. The difference, however, does not appear to be striking. Table A- 12.— Comparison of CPS and OBE Estimates of Families and Unrelated Individuals, by Family Personal Income in 1959 [In millions] Family personal income 1 Families and unrelated individuals Families CPS OBE CPS OBE Total 55.8 55.3 45.1 44.8 Under $2,000 7.9 10.0 11.9 16.5 9.4 7.5 11.4 12.5 15.5 8.4 3.9 6.8 10.1 15.4 8.9 3.5 7.6 10.7 14.9 8.3 $2,000 to $3,999 $4,000 to $5,999 $6,000 to $9,999 $10,000 and over 1 See text for explanation of family personal income. Source: OBE data from Liebenberg and Fitzwilliams, op. cit.; CPS estimates based on unpublished data from the March 1960 CPS. 190 APPENDIX A The 1960 Census data are not shown in table A- 12 because they were not inflated to family personal income. To some extent, the similarity of the CPS and OBE results is due to the fact that there is some relationship between the procedures used to prepare both sets of figures. The major difference be- tween the two series is that the OBE figures start with tax returns which are adjusted to a family basis, whereas CPS starts with family income obtained in household reports. According to the available evidence, the completeness of income reporting is not much better on tax returns than in household surveys. Aside from this difference, both sources use essentially the same method for distributing the missing income; i.e., each type of income is distributed pro- portionately by income level and adjusted total income is then obtained. The OBE adjusts the income levels rather than the income of the individual family: but this difference does not necessarily have a major impact on the results. On the basis of this limited evidence, there is reason to believe that the OBE figures tend to understate the number of low-income families and individuals. This judgment, however, must be very tentative until the OBE does further work on a reexamination of the procedures used to prepare adjusted income distributions. Comparison of Census and Sales Management estimates of aggregate income by counties: 1959 In contrast to the State data, there are no official figures that can be used to evaluate the 1960 Census results for counties. The Office of Business Econom- ics regularly publishes income figures for States but not for smaller geographic areas. 6 Many State and local government agencies, university bureaus of busi- ness research, chambers of commerce, and commercial banks prepare county income estimates. In a mail canvass made of all such agencies listed in the Department of Commerce report, Personal Income: A Key to Small-Area Market Analysis, published in 1 96 1 , T it was found that none of these agencies had made comparisons of the 1960 Census figures with their own estimates using the same income concept. There are three well-known commercial sources of county income estimates for the United States: Standard Rate and Data Sen-ice (published in Spot Television Rates and Data, Newspaper Rates and Data, and Spot Radio Rates and Data) : Editor and Publisher Company (published in Editor and Publisher Market Guide) ; and Sales Management (published in Survey of Buying Power) . Of these three sources of information, the cash income figures published by- Sales Management were most nearly in conceptual agreement with the 1960 Census data. This series measures the money income received by households less personal tax and nontax payments which are primarily Federal, State, and local income taxes plus several other types of taxes and fees. The figures shown by Editor and Publisher and Standard Rate and Data Service are based on the personal income concept used by OBE. This concept includes several types of nonmoney income that are excluded from the census data. Editor and Publisher uses the personal income concept directly, whereas Standard Rate and Data Service uses disposable income, which is personal income less personal tax and nontax payments. EVALUATION OF CENSUS INCOME DATA 191 The comparison of the Census and Sales Management figures by county is not an evaluation in the same sense as the Census-OBE comparison. Never- theless, the ability to compare the independently prepared Census and Sales Management county income figures with each other should provide useful insights into the quality of both series. The absence of independent estimates has evidently been disturbing to some users of the Sales Management figures. In 1961, the Director of Research of Life magazine, in testimony before a con- gressional committee, stated: . . . for intercensal years wc fall back on Sales Management in their survey of cur- rent buying power. . . . While we are satisfied that the households and popula- tion data are good, we don't know how good the income data are. 8 The comparison attempted here provides at least a useful beginning in the evaluation of both sets of county income aggregates. There are several important conceptual differences between the Sales Man- agement income figures and those derived from the 1960 Census. For this reason, various adjustments had to be made in the Census results before they could be compared with Sales Management estimates. Sales Management publishes the number of households and cash income per household for each county. 9 Using these figures, an estimate was prepared of the aggregate cash income received by households for each county. Sales Management uses the Census definition of a household. Excluded from the Sales Management figures are the incomes of all persons living in hotels, room- ing houses, college dormitories, military barracks, or institutions, since the res- idents of such places are not members of the population residing in households. Cash income includes money income received by residents of households. It excludes the income of persons not living in households as well as nonmoney income received by the population living in households. The benchmarks used to prepare the Sales Management figures for each State are estimates of per- sonal income for the preceding year as published in the August issue of the Survey of Current Business. For example, State estimates for 1958 were taken from this source, adjusted to conform to the Sales Management definition of Net Effective Buying Income, and then projected for each State to 1959. 10 One important part of this adjustment was the deduction of personal tax and non- tax payments to arrive at a disposable income concept. Figures for 1958 were used in the adjustment procedure in order to obtain by January 1960 an esti- mate of the aggregate income in 1959 for each State. Ordinarily these figures would not have been published until August 1960. The State totals derived in the manner described above were distributed by county, using a variety of statistical procedures. One of these procedures is described as follows: . . . segregate the state total into the income derived from farming, manufacturing, trade, property, etc. Then the farm income would be distributed among all counties in accordance with the number of farm operators and laborers, the manufacturing income would be allocated according to the number of manufacturing workers in each county, and so on until the sum of the income earned by the components of the county labor force would be the county income total. 11 192 APPENDIX A It is further pointed out that the figures are . . . refined by correlation analyses based on the median and mean rent figures collected for both counties and cities and reported in the 1940 and 1950 Censuses of Housing. 12 The 1960 Census income aggregates for each county appear in the County and City Data Book for 1962. These figures were derived from 1960 Census of Population, General Social and Economic Characteristics, Final Report, PC ( 1 ) , chapter C, table 86. They represent the total money income of the entire population, before taxes are deducted. For comparability with the Sales Management figures, estimates had to be made for each county of the income received by the population living in hotels, rooming houses, and other group quarters, as well as personal tax and nontax payments. The census data also had to be adjusted for consistency with the personal income totals used as benchmarks in preparing the Sales Management figures. The number of persons living in group quarters in each county is shown in 1960 Census of Population, General Population Characteristics, Final Report, PC( 1 ) , chapter B, table 28. The average income used to estimate the aggregate received by the population in group quarters depended on the type of group quarters that was most important in each county. A listing was made of all special population concentrations, by county, for each State, including the estimated number of occupants in each place. In counties without any large special dwelling places, the median income for unrelated individuals was used as the average for the occupants of group quarters. Where most of the popula- tion in group quarters lived in military barracks, an average income of $1,600 was used; $700 was used for college dormitories; $900 for homes for the aged; $1,100 for migratory workers' camps; and $200 for all institutions except homes for the aged. Estimates of personal tax and nontax payments for each State were obtained from the August 1960 Survey of Current Business, pp. 13 and 17. It was assumed that these tax payments were distributed by county in the same pro- portion as the aggregate money income reported in the 1960 Census. The final adjustment made in the Census figures was the adjustment for underreporting. Table A-2 shows that in most States, the census figures were several percentage points below the independent estimates prepared by OBE. Since Sales Management essentially uses the OBE State totals as benchmarks, the Census results also had to be inflated to the OBE estimates before the two series could be compared. This adjustment was made by assuming that the underreporting of income in each county was the same as for the State as a whole. The estimate of disposable income received by households in each county was therefore inflated by the percent of underrporting shown in table A-2 for the State in which the county is located. Table A- 13 shows the specific adjustments that were made in the 1960 Census income figures for Connecticut to make them comparable with the Sales Manage- ment estimates. EVALUATION OF CENSUS INCOME DATA 193 Table A-13.— Adjustment of I960 Census Figures for Comparability with Sales Management Estimates, for Connecticut [In millions] County Aggregate money income in 1960 Census HJ Estimated aggregate income of group quarters residents Estimated taxes Census estimate excluding group quarters and taxes Census estimate comparable with Sales Management (Col. 4 adjusted for under- reporting of income) Sales Manage- ment estimates $5,963.3 $62.4 $874.2 $5,026.7 $5,464.0 $5,609 1,825.7 1,610.5 267.3 185.3 l l,448.9 373.4. 126.8 125.4 9.6 11.3 2.7 1.1 11.9 19.7 5.2 0.9 267.6 236.1 39.2 27.2 54.7 18.6 18.4 1,548.5 1,363.1 225.4 157.0 1,224.6 299.0 103.0 106.1 1,683.2 1,481.6 245.0 170.8 1,331.1 325.0 112.0 115.3 1,682 1,530 235 167 1,385 355 120 135 • This figure appears incorrectly in the County and City Data Book for 1962 as 1,499. Source: Column 1 from U.S. Bureau of the Census, County and City Data Book, 1962; columns 2-5 based on un- published estimates of the Bureau of the Census; and column 6 from Sales Management, Survey of Buying Power, July 10, 1960. See also, Herman P. Miller, Comparison of 1960 Census Aggregates with Independent Estimates by Slate and County, Advertising Research Foundation, 1964. Column 1 shows the aggregate money income figures that underlie the rounded figures published in the County and City Data Book for 1962. Column 2 shows the estimated amount of income received by residents of group quarters in each county. This amount must be subtracted from the Census total because group quarters are not included in the Sales Management figures. The estimate for Fairfield County, for example, was obtained by as- signing an average income of $700 to each of the 13,696 residents of group quarters. This average was used because most of these residents appeared to be college students living in dormitories. Column 3 shows the estimated personal tax and nontax payments (largely Federal, State, and local income taxes) included in the 1960 Census figures. This amount also must be subtracted from the Census total because it is not included in the Sales Management figures. The estimate was obtained in the following way. The August 1960 Survey of Current Business (pp. 13 and 17) shows that $874 million in personal tax and nontax payments (largely Federal, State, and local income taxes) were paid in Connecticut in 1959. This amount represents 14.66 percent of the estimated aggregate money income for Connecti- cut reported in the 1960 Census ($5,963.3 billion). It was therefore estimated that 14.66 percent of the aggregate income in each county represented Federal, State, and local income tax payments. Column 4 shows the 1960 Census totals excluding income of group quarters and taxes. Column 5 shows column 4 adjusted for underreporting of income in the 1960 Census. Table A-2 shows that only 92 percent of the OBE estimated income 194 APPENDIX A for Connecticut was reported in the census. Therefore the Census totals were divided by 0.92 to obtain the amount that would be consistent with the OBE estimate. Column 6 shows the Sales Management figures for each county. A summary of the differences between Census and Sales Management esti- mates by county is shown in table A- 14, and an additional summary for standard metropolitan statistical areas (SMSA ; s) is shown in table A-15. The two sets of figures are generally in very close agreement with respect to the percent distribution of aggregate income among counties within a State. For the country as a whole, 80 percent of the counties were either in exact agreement, or they differed by one-tenth of a percentage point with respect to the proportion of the State total shown for a given county. Less than 3 percent of the counties differed by as much as 1 percentage point (see table A-14). The absolute amounts of aggregate income by county were generally in much wider disagreement than were the percentage figures. As might be expected, the differences were most pronounced in the counties with the smallest aggre- gate incomes. For example, the estimated aggregate for Sumter County, Ala- bama, was $10 million in the Census data and $12 million in Sales Management. In both series, Sumter County received 0.3 percent of the State total; yet, there is a difference of $2 million, or 20 percent, between the two figures. For the country as a whole, the estimated aggregate incomes differed by less than 5 percent for 28 percent of all counties; differences of 5 to 10 percent were found in 20 percent of the counties. Thus, in about one-half of the counties the dif- ferences in aggregate income between the two series were less than 10 percent. Relatively large differences — 15 percent or more — were found in about one-third of all counties; but, as noted above, the amounts involved in most of these counties were relatively small and subject to large errors of estimation. A more significant comparison of the Census and Sales Management income aggregates is shown in table A-15, where both sets of data are presented for standard metropolitan statistical areas. Since the underlying data were com- puted for counties, it was necessary to restrict the comparison to 188 SMSA's comprised of whole counties. These areas, however, represent a very large proportion of the total aggregate income in the United States, and they also contain the places with the most rapid change and development. Most users of income statistics for local areas undoubtedly attach greatest significance to the figures for SMSA's. Table A-15 shows that in 79 SMSA's, or 42 percent of the total, the difference between the Census and Sales Management estimates was less than 5 percent; in an additional 62 SMSA's, or 33 percent of the total, the difference was 5 to 10 percent. Thus, in about three-fourths of the SMSA's the difference between the two sets of figures was less than 10 percent. EVALUATION OF CENSUS INCOME DATA 195 Table A-14.— Summary of Differences Between I960 Census and Sales Management Estimates of Aggregate Income in 1959, by Regions, Divisions and States Region, division, and State Total number of counties Counties in which Census and Sales Management estimates of percent of total income in each State vary by: 0.1 percent or less 0.2 to 0.9 percent 1.0 percent or more Counties in which Census and Sales Management estimates of aggregate income vary by: 4.9 percent or less 5.0 to 9.9 percent 10.0 to 14.9 percent United States.. Northeast New England Maine New Hampshire. . . . Vermont Massachusetts. . . . Rhode Island Connecticut Middle Atlantic New York New Jersey Pennsylvania North Central East North Central. Ohio Indiana. . .„ Illinois Michigan Wisconsin West North Central. Minnesota Iowa Missouri North Dakota South Dakota Nebraska Kansas South South Atlantic Delaware Maryland Dist. of Columbia Virginia West Virginia. . . . North Carolina... South Carolina... Georgia Florida East South Central. Kentucky Tennessee Alabama Mississippi West South Central. Arkansas Louisiana Oklahoma Texas West Mountain Montana Idaho Wyoming Colorado New Mexico Arizona Utah Nevada Pacific Washington Oregon California 3,072 2,464 528 80 852 623 504 217 67 16 10 14 14 5 8 150 62 21 67 1,054 436 88 92 102 83 71 618 87 99 114 53 67 93 105 1,387 553 3 23 1 99 55 100 46 159 67 364 120 95 67 82 470 75 64 77 254 414 281 57 45 24 63 32 14 29 17 133 39 36 58 144 22 7 2 4 6 122 52 10 60 884 393 81 30 97 74 61 491 71 81 104 30 37 74 94 1,157 441 1 17 1 84 29 79 27 149 54 306 105 39 53 59 410 56 45 69 240 279 177 39 34 7 49 19 2 20 7 102 29 26 47 53 35 7 7 9 6 3 3 18 6 151 39 7 12 4 7 9 112 14 16 9 18 28 17 10 212 102 2 4 13 25 21 18 8 11 52 14 5 12 21 58 19 19 8 12 112 84 17 8 13 11 10 8 9 8 28 8 9 11 20 10 2 1 1 2 2 2 10 4 3 3 19 4 1 2 1 15 2 2 1 5 2 2 1 18 10 23 20 1 3 4 3 3 4 76 28 8 5 6 4 48 19 7 22 285 137 35 33 10 33 26 148 12 18 35 15 25 20 23 363 144 25 10 20 16 46 21 101 37 26 15 23 118 17 9 30 62 121 72 17 14 8 12 6 2 49 15 16 18 63 17 3 4 3 4 1 2 46 14 5 27 203 109 25 28 15 21 20 94 14 20 17 8 6 8 21 259 95 2 10 1 19 7 24 12 7 13 77 21 2: 19 17 87 9 16 19 43 98 53 11 10 4 8 9 3 6 2 45 13 12 20 39 13 4 2 4 2 1 26 11 4 11 156 72 11 16 15 17 13 84 10 15 19 8 8 11 13 254 94 1 3 16 13 13 5 34 9 69 25 14 14 16 91 17 8 12 54 55 37 6 6 5 1 3 18 3 4 11 — Represents zero. Source: Herman P. Miller, Comparison of 1960 Census Aggregates with Independent Estimates by State and County, Advertising Research Foundation, 1964, table 3, pp. 11-13. 196 APPENDIX A Table A-l 5. —Census and Sales Management Estimates of Aggregate Income in 1959, by Standard Metropolitan Statistical Areas [In millions. Excludes SMSA's in New England that do not consist of whole counties] Census Sales Manage- ment Ratio of Sales Manage- ment to Census £. QQ .yj 265 290 1.09 1,303 1,328 1.02 296 360 1.22 2,097 1,827 .87 509 532 1.05 1,333 1,337 1.00 215 227 1.06 1 ,796 1,707 .95 522 493 .94 7,392 7,968 1.08 118 120 1.02 j i j 452 1.09 167 158 .95 424 473 1.12 408 419 1.03 271 254 .94 305 347 1.14 171 209 1.22 656 784 1.20 594 486 .82 95 82 .86 434 432 1.00 975 989 1.01 594 625 1.05 Standard metropolitan statistical area Standard metropolitan statistical area Census Sales Manage- ment Total Abilene, Texas Akron, Ohio Albany, Ga Albany -Schenectady-Troy , N.Y Albuquerque, N. Mex Allentown-Bethlehem-Easton , Pa. -N.J Altoona, Pa Amarillo, Texas Ann Arbor, Mich Asheville, N.C Atlanta, Ga Atlantic City, N.J Augusta, Ga.-S.C Austin, Texas Bakersfield, Calif Baltimore, Md Baton Rouge, La Bay City, Mich Beaumont-Port Arthur, Texas Billings, Mont Binghamton, N.Y Birmingham, Ala Browns ville-Harlingen-San Benito, Texas Buffalo, N.Y Canton, Ohio Cedar Rapids, Iowa Champaign-Urbana , 111 Charleston, S.C Charleston, W.Va Charlotte, N.C Chattanooga, Tenn.-Ga Chicago, 111 Cincinnati, Chio-Ky Cleveland, Chio Colorado Springs , Colo. . . . Columbia, S.C Columbus, Ga.-Ala Columbus, Chio Corpus Christ i, Texas Dallas, Texas Davenport -Rock Island- Moline, Iowa-Ill Dayton, Ohio Decatur, 111 Denver, Colo Des Moines, Iowa Detroit, Mich Dubuque , Iowa Duluth-Superior , Minn. -Wis Durham, N.C El Paso, Texas Erie, Pa Eugene, Oreg Evansville, Ind.-Ky Fargo-Moorhead , N. Dak.- Minn Flint, Mich Fort Lauderdale-Hollywood, Fla Fort Smith, Ark Fort Wayne, Ind Fort Worth, Texas Fresno, Calif Gadsden, Ala Galveston-Texas City, Texas Gary -Hammond -East Chicago, Ind Grand Rapids, Mich Great Falls, Mont Green Bay, Wis Greensboro-High Point, N.C Greenville, S.C Hamilton-Middletown, Chio. Harrisburg, Pa Houston, Texas , Huntington -Ashland, W. Va. - Ky.-Chio Huntsville, Ala Indianapolis , Ind Jackson, Mich Jackson, Miss Jac ks onvi lie , Fla Jersey City, N.J Johnstown, Pa , Kalamazoo, Mich Kansas City, Mo.-Kans Kenosha, Wis Knoxville, Tenn Lake Charles, La Lancaster, Pa Lansing, Mich Laredo, Texas Las Vegas, Nev Lawton, Okla , Lexington, Ky Lima, Ohio Lincoln, Nebr Little Rock-North Little Rock, Ark , Lorain-Elyria , Ohio Los Angeles -Long Beach, Calif Louisville, Ky.-Ind , Lubbock, Texas lynchburg, Va Macon, Ga Madison, Wis Memphis, Tenn Miami, Fla Midland, Texas Milwaukee, Wis Minneapolis -St. Paul, Minn Mobile, Ala Monroe, La Montgomery, Ala Muncie, Ind Muskegon-Muskegon Heights, Mich Nashville, Tenn Newark, N.J New Orleans, La Newport News -Hampton, Va... New York, N.Y Norfolk -Portsmouth , Va Odessa, Texas Ogden, Utah Oklahoma City, Okla Omaha, Nebr. -Iowa Orlando, Fla $117 218 1,017 660 132 195 411 294 357 613 2,307 374 173 1,384 235 278 683 1,110 357 305 2,104 194 514 203 476 518 54 269 106 210 166 274 388 364 15,168 1,191 260 146 256 401 1,686 148 2,418 2,862 421 130 235 184 243 647 3,798 1,371 326 23,498 742 153 173 846 867 505 $131 199 1,016 645 129 187 341 273 326 601 2,103 368 109 1,366 221 220 702 1,268 386 291 2,101 180 504 218 497 543 59 252 90 174 177 257 380 385 14,322 1,118 286 133 238 370 884 1,732 133 2,277 2,621 384 127 234 187 236 567 3,396 1,325 309 24,200 908 175 175 829 757 484 EVALUATION OF CENSUS INCOME DATA 197 Table A-l 5. —Census and Sales Management Estimates of Aggregate Income in 1959, by Standard Metropolitan Statistical Areas— Con. [In millions. Excludes SMSA's in New England that do not consist of whole counties] Standard metropolitan statistical area Census Sales Manage- ment Ratio of Sales Manage- ment to Census Paterson-Clifton-Passaic , N.J $2,660 $2,806 1.05 269 269 1.00 538 592 1.10 Philadelphia, Pa. -N.J 8,307 7,969 .96 Phoenix, Ariz. . . . 1,079 990 .92 "4,336 4,235 .98 1,537 1,519 .99 132 138 1.05 167 182 1.09 265 258 .97 2-49 212 .85 495 501 1.01 197 184 .93 713 673 .94 240 250 1.04 1,230 1,231 1.00 406 413 1.02 1,006 991 .99 312 324 1.04 157 172 1.10 St. Louis, Mo. -Ill 4,018 4,069 1.01 638 653 1.02 94 111 1.18 903 838 .93 San Bernardino-Riverside- 1,335 1,322 .99 1,911 1,788 .94 San Francisco-Oakland, Calif 6,294 6,278 1.00 1,343 1,209 .90 Santa Barbara, Calif 360 293 .81 253 258 1.02 343 367 1.07 2,252 2,083 .92 419 379 .90 Standard metropolitan statistical area Ratio of Sales Sales Census Manage- Manage- ment ment to Census $179 $180 1.01 147 138 .94 443 483 1.09 462 524 1.13 278 283 1.02 200 202 1.01 217 231 1.06 287 284 .99 410 444 1.08 1,032 1,006 .97 494 502 1.02 1,214 1,178 .97 172 178 1.03 107 115 1.07 888 1,002 1.13 251 241 .96 519 542 1.04 423 444 1.05 738 715 .97 123 109 .89 127 109 .86 552 551 1.00 212 196 .92 4,302 4,190 .97 217 216 1.00 387 385 .99 298 299 1.00 619 608 .98 199 196 .98 493 541 1.10 804 846 1.05 315 261 .83 408 397 .97 892 898 1.01 Sioux City, Iowa Sioux Falls, S. Dak South Bend, Ind Spokane, Wash Springfield, 111 Springfield, Mo Springfield, Ohio Steubenville-Weirton, Qhio-W.Va Stockton, Calif Syracuse, N.Y Tacoma, Wash Tampa -St. Petersburg, Fla. Terre Haute, Ind Texarkana, Texas -Ark Toledo, Ohio Topeka, Kans Trenton, N.J Tucson, Ariz Tulsa, Okla Tuscaloosa, Ala Tyler, Texas Utica-Rome, N.Y Waco, Texas Washington, D.C.-Md.-Va. . . Waterloo, Iowa West Palm Beach, Fla, Wheeling, W.Va.-Ohio Wichita, Kans Wichita Falls, Texas Wilkes-Barre — Hazleton, Pa Wilmington, Del. -N.J Winston-Salem, N.C York, Pa Youngstown-Warren, Ohio... Source: Herman P. Miller, Comparison of 1960 Census Aggregates with Independent Estimates by State and County, Advertising Research Foundation, 1964, table 4, pp. 14-19. Comparison of CPS and Census Essentially two types of comparisons can be made between the income data collected in the CPS and in the census: (a) distributions or averages can be compared for many different characteristics, such as age, sex, color, education, etc.; and (b) tabulations can be made for an identical sample of persons who provided information in both surveys. Overall comparisons of distributions and averages reveal net differences between the two surveys but provide little insight into the reasons for these differences. Moreover, comparisons of this type do not provide a validation of either set of statistics since neither one can be regarded as a suitable bench- mark. Despite these limitations, there is understandable interest in comparing the results of these two surveys, since both attempt to measure the same thing. In addition, the CPS income surveys have provided useful income statistics for nearly 20 years; to this extent, at least, they provide a reasonable base against which the census results can be compared. Although agreement between the 198 APPENDIX A two series does not necessarily validate either one. disagreement could provide useful clues regarding possible errors. The second type of comparison noted above, generally referred to as a CPS- Census match, involves the analysis of reports obtained for an identical sample of persons in 1950 and 1960 who were included in both the CPS and the census. By comparing the answers given for this sample in the CPS and in the census, it is possible to obtain a measure of the extent of response variation and its likely impact on selected cross-classifications of income and other variables. As might be expected, a large proportion of the respondents did not report the same figures in both surveys. This type of comparison provides a basis, therefore, for getting behind the net errors detected by comparing overall distributions and averages and discovering some of the reasons for the differences. To the extent that nonrespondents in one survey were interviewed in the other, the CPS-Census match also sheds light on possible biases introduced into each set of data due to nonresponse. CPS and Census estimates for selected characteristics: 1949 and 1959. Tables A-16 and A-17 present CPS and Census median incomes in 1949 and 1959 by selected characteristics. The figures for persons in table A-16 show- that in both years the Census estimates tended to exceed the CPS figures. For Table A-16. — Comparison of Census and CPS Median Income in 1959 and 1949 of Persons 14 Years Oi d and Over, by Residence, Color, and Sex Residence, color, and sex 1959 1949 1 CPS Census Differ- ence CPS Census Differ- ence MALE United States $3,996 $4,103 $107 $2,346 $2,434 $88 White 4,208 4,319 111 2,471 2,572 101 1,977 2,273 296 1,196 1,341 145 4,230 4,254 24 2,563 2,613 50 White 4,425 4,474 49 2,669 2,741 72 2,347 2,409 62 1,476 1,571 95 1,696 2,098 402 1,054 1,339 285 White 2,003 2,283 280 1,194 1,489 295 664 778 114 488 577 89 FEMALE United States 1,222 1,357 135 960 1,029 69 White 1,313 1,441 128 1,070 1,137 67 809 909 100 495 584 89 1,290 1,397 107 1,049 1,104 55 White 1,361 1,478 117 1,158 1,200 42 928 948 20 614 672 58 480 731 251 392 458 66 White 665 826 161 433 533 100 311 367 56 290 311 21 1 Excludes Alaska and Hawaii. Source: 1960 Census data from 1960 Census of Population, Vol. I, Characteristics of the Population, Part 1, U.S. Summary, table 97; 1950 Census data from 1950 Census of Population, Vol. II, Characteristics of the Population , Part 1, U.S. Summary, table 138; and CPS data from U.S. Bureau of the Census, Current Population Reports- Consumer Income, Series P-60, Xos. 7 and 35, tables 16 and 22, and underlying tabulations. EVALUATION OF CENSUS INCOME DATA 199 all males and for white males the differences amounted to about $100 in each year; for nonwhites the absolute and relative differences were considerably greater, amounting to about $150 in 1949, and $300 in 1959. For females, both white and nonwhite. the Census estimates tended to exceed the CPS by about $100 both in 1949 and 1959. The estimates cited above are for the country as a whole. For male and female nonfarm residents the differences in both years were so small as to be insignificant. In contrast, the Census medians for male farm residents in both years were about one-fourth higher than CPS medians, and for females the 1959 Census medians were also substantially higher than for CPS. The family data in table A-17 show somewhat different patterns from those described above for persons. In 1949, the Census estimates for families tended to be somewhat lower than the CPS for the country as a whole and for nonfarm residents; only farm residents in 1949 reported slightly higher incomes on the average in CPS than in the census. In 1959, the Census estimates for families were uniformly higher than CPS. For the country as a whole, among both white and nonwhite families, the difference was about $250 in that year, rep- resenting a differential of about 5 percent for whites and nearly twice that amount for nonwhites. Among white families, the Census estimates exceed the Table A-17.— Comparisons of Census and CPS Median Income in 1959 and 1949 of Families and Unrelated Individuals, by Residence and Color [Minus sign ( — ) denotes decrease] 1949 1 Residence and color CPS Census Differ- CPS Census Differ- ence ence FAMILIES $5, 417 $5, 660 $243 $3 ,107 $3,073 -$34 5, 643 5, 893 250 3 ,232 (NA) (NA) 2, 917 3, 161 244 1 ,650 (NA) (NA) 5, 620 5, 822 202 3 ,324 3,249 -75 5, 825 6, 060 235 3 ,428 (NA) (NA) 3, 225 3, 336 111 1 ,973 (NA) (NA) 2, 800 3, 228 428 1 ,587 1,729 142 White 3, 151 3, 472 321 1 ,757 (MA) (NA) 1, 136 If 263 127 691 (NA) (NA) UNRELATED INDIVIDUALS 1, 556 1, 596 40 1 ,050 997 -53 If 663 I, 654 -9 1 ,134 (NA) (NA) I, 075 h 217 142 819 (NA) (NA) If 655 1, 618 -37 1 ,116 1,043 -73 White If 763 1, 675 -88 1 ,208 (NA) (NA) 1, 161 I, 248 87 843 (NA) (NA) 628 926 298 500 591 91 641 975 334 559 (NA) (NA) (B) 648 (NA) (B) (NA) (NA) B Fewer than 100 sample cases. NA Not available. 1 Excludes Alaska and Hawaii. Source: 1960 Census data from 1960 Census of Population, Vol. I, Characteristics of the Population, Part 1, U.S. Summary, table 95; 1950 Census data from 1950 Census of Population, Vol. II, Characteristics of the Population, Part 1, U.S. Summary, table57; and CPS data from U.S. Bureau of the Census, Current Population Reports- Consumer Income, Series P-60, Nos. 7 and 35, table 2, and underlying tabulations. 200 APPENDIX A CPS figures by about $250 in nonfarm areas and by about $300 in farm areas, whereas nonwhite family incomes in the Census averaged about $100 higher than in the CPS in both farm and nonfarm areas. As previously noted in the discussion of the aggregates, the family income figures obtained in the 1960 Census are less affected by underreporting of income than was the case in 1950, due primarily to the change in the method of collecting family income data. In view of some major conceptual differences in the definition of unrelated individuals in the CPS and the Census, it is difficult to make direct comparisons between the two series. Moreover, the CPS estimates for nonwhite unrelated individuals are in several instances based on small samples and are therefore subject to relatively large sampling errors. With these considerations in mind, there appears to be close agreement between the CPS and Census estimates for 1949; however, in 1959, the relation between these two series was rather erratic. For the country as a whole and for nonfarm residents there was no significant difference between the two series. For farm residents Census es- timates appear to be about $300, or 50 percent, higher than CPS. Estimates of aggregate income for 1949 and 1959 are available from the Cur- rent Population Surveys and from the decennial censuses. For 1959, the de- cennial census obtained 95 percent of the OBE estimates whereas CPS reached only 87 percent (see table A-l). The comparison is somewhat more difficult to make for 1949 because two different estimates are available from the decennial census. The aggregate income based on the family income statistics was only 81 percent of the OBE estimate; but family income was badly understated in the 1950 Census because income information was obtained for the family head and for all other persons as a group, not individually. The aggregate based on the income reports for persons in the 1950 Census was 91 percent of the OBE total, whereas the comparable CPS aggregate was only 84 percent of the OBE figure. Two questions arise at this point: (a) why are the income aggregates based on the decennial census higher than those based on CPS; and (b) why are the 1960 Census results more complete in relation to the OBE total than those obtained in the 1950 Census? Although the same income definitions were used in the CPS and in the decen- nial census, the results are not exactly comparable because of differences in the definition of the income-receiving unit. The census figures contain more un- related individuals because (a) members of the Armed Forces living on military installations are counted as unrelated individuals in the census but are excluded in the CPS; and (b) unmarried college students living away from home are counted as unrelated individuals in the census but as members of their parents' families in the CPS. Although the difference in the number of unrelated indi- viduals is relatively large, it accounts for only a minor part of the discrepancy in aggregate income in the two series. The reason for the higher Census aggregate can be clearly seen in table A-l 8, which shows the distribution of families and unrelated individuals by total money income in 1959 based on the March 1960 CPS and the 1960 Census. There is EVALUATION OF CENSUS INCOME DATA 201 Table A-18.— Comparison of CPS and Census Estimates of Families and Unrelated Individuals, by Total Money Income in 1959 [In millions] Total money income Families and unrelated individuals Families Census CPS Census CPS 58.3 55.8 45.1 45.1 13.6 12.1 5.9 6.0 10.9 11.1 8.0 8.8 12.1 12.6 10.5 11.2 L4.7 U.3 13.9 13.6 4.9 4.3 4.7 4.1 1.5 1.1 1.5 1.1 0.6 0.3 0.6 0.3 Source: 1960 Census data from 1960 Census of Population, Vol. I, Characteristics of the Population, Part 1, U.S. Summary, table 95; and CPS data from U.S. Bureau of the Census, Current Population Reports— Consumer Income, Series P-60, No. 35, table 5. a difference of nearly $30 billion between these two series. The CPS estimates total $303 billion whereas the 1960 Census figures add to $332 billion. Nearly all of the difference is accounted for by the fact that the 1960 Census obtained an appreciably larger number of high-income families. An examination of the two distributions shows rather close agreement near the bottom of the distribu- tion, but wide differences at the top. The 1960 Census reported more families and unrelated individuals at the lowest income level primarily because, as pre- viously noted, the decennial census counts members of the Armed Forces living on military posts and unmarried college students living away from home as unrelated individuals. The CPS excludes the former and counts unmarried college students as part of their parents' families. These groups add very little to the 1960 Census aggregate income, several billion dollars at most. If the comparison is restricted to families, there is almost exact agreement in the numbers at the bottom income level. The 1960 Census, however, contains about 1.3 million more families with incomes above $10,000, and these families account for practically all of the aggregate difference between the two series. In other words, most of the income missing from the annual CPS income surveys is not distributed throughout the income range, but is highly concentrated in the top income levels. Why does the CPS indicate fewer high-income families than the census? Two possible answers come to mind, relating to sampling variability and bias. Conceivably the CPS estimates of high-income families are subject to very large sampling errors; or perhaps there is a bias in the CPS which tends to make that survey produce a chronic shortage in the number of high-income families. There is no evidence to support either of these theories. If sampling error were a factor, then some of the CPS samples should have produced overestimates of the number of high-income families during the past 15 years. In a sample as large as the CPS an estimate with a large sampling error should be overstated about as often as it is understated. This has not taken place in CPS because the number of high-income families is consistent from year to year and is not subject to wide unexplained fluctuations. 202 APPENDIX A It is most unlikely that the CPS sample has a bias that causes a chronic short- age in the number of high-income families. To militate against the intrusion of bias, the most rigorous controls are used in the selection of the sample, the listing procedures, and all other phases of the design and selection of the sample. Several other explanations are possible but none are conclusive. One hy- pothesis is that CPS income estimates are understated primarily because respond- ents are unable or unwilling to provide accurate answers, or because they tend to forget minor or irregular sources of income. The very first income report based on the CPS, published by the Bureau of the Census (in May 1947), stated : In addition to sampling variations, the figures are subject to biases due to errors of response and nonreporting. In most cases the schedule entries for income are based on memory rather than on records, and in the majority of instances on the memory or knowledge of some person, usually the wife of the household head, who is not the principal income recipient. . . . Memory bias in income estimates derived from field surveys probably produces underestimates, because the tendency is to forget irregular sources of income. Other biases of reporting are due to misrepresentation or to misunderstandings as to the scope of the income concept. 18 Since the missing CPS income is caused by a shortage of high-income families, it seems very unlikely that the deficiency is due to faulty memory, poor choice of respondent, nonresponse, and willful misstatements. Evidence to support this view is available from the intensive studies that were made after the 1950 Census to find out why the income estimates produced by the Census Bureau surveys were too low. All these tests started with the assumption that income reports obtained by standard procedures used in Census Bureau surveys are defective for the reasons stated above. None of these surveys turned up the missing income. After the 1950 Census an intensive reinterview survey was made, using a more detailed questionnaire and better qualified and better trained interviewers than had been used in the census; but the reinterview survey pro- duced little, if any, additional income. A comparison of 1950 Census reports with tax returns; Bureau of Old-Age, Survivors, and Disability Insurance wage records; and income reports obtained by the Survey Research Center of the University of Michigan, turned up no substantial amounts of missing income. Matching studies of Census reports for identical families interviewed in the census and in the annual Current Population Surveys in 1950 and in 1960 offered no clues regarding the missing income. In short, this hypothesis is not sup- ported by the results of field tests. Another hypothesis attempts to relate the shortage of high-income families in the CPS to nonresponse rather than to reporting error. There is some evidence to support this view. There are two types of nonresponse in the income surveys conducted by the Bureau of the Census. The first is called "Type A" and refers to households for which no information whatever is obtained regarding labor force status, income, or any other subject because EVALUATION OF CENSUS INCOME DATA 203 no one was at home during repeated visits, the occupants were temporarily absent, refused to be interviewed, or did not provide information for other reasons. These households, amounting to about 5 percent of the total, are implicitly represented in the CPS tabulations because the sample weights for interviewed households are increased as a means of substituting for them. An unpublished analysis made by the Census Bureau of households that were Type A noninterviews in either April or July 1959 (but not in both months) suggests that these households have about the same income distribution as households that are interviewed. The second type of noninterview in the CPS income surveys comes from households that provide labor force information but do not respond to the income questions. No substitutions were made for these households, and there were no adjustments of sample weights in the March 1960 CPS. They were excluded from the income tabulations. According to the 1960 CPS-Census matching study, about nine-tenths of the people who did not report on income in the CPS in March 1960, did provide such information in the census. This study shows that nonrespondents in the CPS have somewhat higher than average incomes. The median income in the 1960 Census of men who did not report on income in the CPS was $4,900, compared with a median of $4,300 for men who did report in the CPS. More significant is the fact that nonrespondents in the CPS appear to contain a larger proportion of men with incomes over $10,000. About 6 percent of the male respondents in the CPS had incomes over $10,000, whereas about 13 percent of the male nonrespondents in CPS reported incomes over $10,000 in the census. Female nonrespondents in CPS also have considerably higher average incomes than those who responded. This factor would also tend to reduce the number of high-income families in the CPS. A third hypothesis attempts to explain the larger 1960 Census estimates of high-income families in terms of a possible bias in the 25-percent sample. This view does not stand up under close examination. Several preliminary analyses conducted by the Census Bureau staff do suggest that there may be biases in the 25-percent sample because there are significant differences between some estimates for which complete count and sample data are available. For example, the sample contains an undercount of older persons. Males 65 years old and over are understated by about 2.7 percent and females, by 1.8 percent. Similarly, a shortage of nonrelatives and primary individuals has been noted. None of the evidence uncovered to date, however, points specifically to an overcount of high-income families in the 25-percent sample. Even less likely is the possibility that the overcount is as much as one-third, which is the difference between the CPS and Census estimates of the number of families with incomes over $15,000. A fourth hypothesis attributes the larger number of high-income families in the 1960 Census primarily to better reporting induced by the self -enumeration procedure used to collect sample information in the 1960 Census. It seems 204 APPENDIX A reasonable to many people that higher income respondents might have provided more accurate reports in the 1960 Census because they were asked to complete their own returns and to sign them. Here again the evidence from the GPS- Census matching studies is most revealing. A comparison of CPS and Census income reports for a sample of persons shows no tendency toward overreporting or underreporting at any income level in either 1950 or 1960. It appears, therefore, that the accuracy of reporting was about the same in the CPS and the census, and that the higher income families are missing from the CPS figures, rather than that they are in the distribution but classified at too low a level. It has been argued that the results of the CPS-Census matching study may not be valid because the answers of respondents might have been conditioned as a result of having been interviewed in two successive months; that is, people who gave one answer in the March CPS may tend to repeat that answer in April in the census. There is no evidence to support this view. Indeed, the CPS- Census matching study shows considerable variability of response, since about half the families were classified in different $500-income levels in the two surveys. Thus, there were fairly large gross errors in reports, suggesting little conditioning. These errors, however, tended to offset one another, producing little change in the income distribution. Since the 1960 Census had more high-income families than the CPS, one might well ask why the same thing did not happen in 1950. To some extent it did, but the tendency was hidden by other factors which tended to lower the aggregate. As previously explained, income data were collected in the 1950 Census by asking three income questions for the family head and for all other relatives as a group. This differed from the procedure used in the CPS where income questions are asked for each member of the family individually. More- over, where income was reported only for the family head, that amount was used as the total income for the family even where no information was obtained for other family members. There is no question that this procedure produced an underestimate of family income in the 1950 Census because aggregates based on the 1950 Census family statistics accounted for only 81 percent of the OBE total whereas, aggregates based on statistics for persons, which were collected in the same way as in the CPS, accounted for 91 percent of this total. In the 1960 Census, where income was reported for each person individually, as in the CPS, both the family ag- gregate and the persons' aggregate represent about 95 percent of the OBE total. Therefore, the procedure used to collect family income statistics in the 1950 Census produced a downward bias in the results. Nevertheless, the 1950 Census obtained 20 percent more families with incomes over $10,000 than did the CPS in the same year. Thus the tendency for CPS to be deficient in high- income families was present even in 1950, but it could not be seen as clearly as in 1960. EVALUATION OF CENSUS INCOME DATA 205 Why did the proportion of aggregate money income covered in the decennial census increase from 91 percent to 94 percent between 1949 and 1959, and why did the GPS coverage also increase from 84 percent to 87 percent during the same period? Although the answer is at best conjectural, one factor must be the increase in the relative importance of wages and salaries as a component of the total. In 1949, wages and salaries represented 67 percent of the total as compared with 71 percent in 1959. Since this type ot income is much more completely reported in household surveys than are other types, it follows that aggregate income coverage in household surveys will tend to improve as wages and salaries gain in importance. There may also be other contributing factors. Perhaps the public has become more receptive to income surveys over the years, and as a result the quality of response has improved. Or it may be that respond- ents are providing more accurate reports than they did 10 years ago because of increases in educational attainment. Also, more people are now required to file tax returns and therefore keep better records or are better able to remember their income. An improvement in population coverage in the census or the annual surveys could also account for some reduction in the underreporting of income. CPS-Census matching study About one-fourth of the persons who were in the March 1960 income supple- ment to the CPS were also asked to report income information in the 1960 Census. Similarly, about one-fifth of the persons in the March 1950 income supplement were asked to report on income in the 1950 Census. Upon com- pletion of each census, an attempt was made to match the reports obtained for identical persons in the CPS and the census, using name, address, age, sex, color, and other means of identification. In 1960, Census records were found for about 93 percent of the persons who were in the CPS income sample. After the records were matched a comparison was made of the amount of income reported in each survey. A summary of the results of such a comparison with respect to total money income is shown in table A-19. The income concept and period covered by both surveys were the same. Therefore, variations in the responses are not due to conceptual differences between the two surveys but rather to a variety of other factors including, in 1950, differences in the quality of the enumerators, and variability of response due to such things as the memory factor and change in respondents. In addition to the factors noted above, variations between the CPS and the Census for 1960 could be due to the use of self-enumeration in the census as compared with direct enumeration in the CPS. Table A-19 shows considerable variations in the reports received for identical persons in each survey; however, these variations tended to cancel each other, leaving the overall distributions unchanged. This was true for both males and females in both censuses. This table shows no significant differences in the medians (which agree nearly to the dollar) , the distributions by income levels, or the proportions of income recipients. One of the hallmarks of an improved 206 APPENDIX A Table A-19.— Consistency of Total Money Income Reporting in the CPS and the Census, for Persons 14 Years Old and Over, by Sex: I960 and 1950 Comparison of CPS and Census Male Female 1960 1950 1960 1950 Total reporting on income in CPS and Census 100 100 100 100 Percent in same interval in both 56 62 73 77 20 21 14 13 24 18 13 11 Income recipients in CPS and Census 100 100 100 100 56 65 69 77 PpTPPTit. in hichPT' intpnvnl in ("IPS 19 20 15 13 Percent in higher interval in Census 24 16 16 10 Persons reporting no income in CPS 100 100 100 100 Porn PTi t vi th i nrnrnp i n f!pn bh 26 43 12 12 100 1 (VI JJUU 10C 34 38 14 14 Median income: CPS $4,327 $2,514 $1,508 $1,152 4,406 2,444 1,524 1,163 N on respondents in CPS: Percent reporting in Census 90 75 92 85 $4,862 $3,095 $2,491 $1,000 Nonrespondents in Census: Percent reporting in CPS 88 88 94 92 $3,216 $2,373 $1,093 $1,000 Source: Unpublished data of the Bureau of the Census. survey technique in the collection of income data from households is the ability to identify persons with small amounts of income, often not reported. In the case of women there was a striking consistency in the results obtained in both 1950 and 1960. Each survey reported income for about 12 to 14 percent of the women who were classified as not having income in the other survey. The results were somewhat different for men. In 1960, about one-fourth of the men without income in the CPS were found to have some income in the census. On the other hand, about one-third of the men without income in the census were found to have some income in the CPS. In 1950, about 40 percent of the men without income in each survey were found to have income in the other survey. Perhaps the major conclusion suggested by table A-19 is that the two-stage self-enumeration procedure used in the 1960 Census did not produce results appreciably different from those obtained by the conventional direct enumera- tion methods used in the CPS. It could be argued, in view of the difficulty of recruiting enumerators of comparable ability with those used in the CPS, that the 1960 Census results might have been worse than the CPS results if direct enumeration had been attempted. This argument, however, is not supported by the facts, since the 1950 CPS and Census medians and distributions are also identical, and the same interview methods were used to collect both sets of data. Since income information for persons in the census was first obtained in the CPS, the Census report might be regarded as a conditioned response rather than as an independent estimate. It is undoubtedly true that some of the Census reports were conditioned by the CPS response. In view, however, of the vast differences in the reports for identical persons in both surveys, it is hard to EVALUATION OF CENSUS INCOME DATA 207 imagine that this was a major factor. In 1960, only 56 percent of the males reported incomes that were in the same class interval in both surveys; about 20 percent reported higher incomes in the CPS and about 24 percent reported higher incomes in the census. For women, the consistency of response in 1960 was greater than for men, with about three-fourths reporting incomes in the same class interval. It must be remembered, however, that a very large propor- tion of women do not receive any income; and it is much easier for them to recall whether or not they had any income than to estimate the specific amount. There is some evidence that consistency of response between the CPS and the census was somewhat greater in 1950 than in 1960. The differences how- ever, are not very striking. Among men, about 62 percent were in the same class interval in the CPS and the census in 1950, compared with 56 percent in 1960. Among women, 77 percent were in the same class interval in 1950, compared with 73 percent in 1960. Where differences were found, the census data in 1960 show a tendency to be higher, whereas the reverse was true in 1950. Thus, for example, among male income recipients in 1950, 20 percent were in a higher CPS class interval and 16 percent were in a higher census class interval. In 1960, the CPS was higher in 19 percent of the cases and the census was higher in 24 percent. The corresponding differences for females were not significant. In both 1950 and 1960, the great majority of persons who did not report on income in one survey did report in the other. The matching study therefore provides a fairly good indication of the income of nonrespondents in both the census and the CPS. In 1960, 90 percent of the males who did not report on income in the CPS did report in the census. The median for this group ($4,900) was above the average for persons who did report in the CPS ($4,300) . Conversely about nine-tenths (88 percent) of the males who did not report on income in the census did report in the CPS. The median for this group ($3,200) was considerably below the median obtained for men who did report in the census ($4,400). In the 1950 Census there was also some tendency for male nonrespondents in the CPS to have somewhat higher incomes than those who reported ($3,100 for nonrespondents as compared with $2,500 for respondents), whereas nonrespondents in the census had about the same average income ($2,400) as respondents. Among women, nine-tenths of nonrespondents in the March 1960 CPS reported on income in the census ; and the average, as for men, was considerably higher ($2,500) than the average for respondents ($1,500). Similarly, nine- tenths of the women who did not report on income in the 1960 Census did report in CPS. The average for this group ($1,100), again as for men, was lower than the average for respondents ($1,500) . In 1950, women nonrespond- ents in the CPS and the census had about the same average income as respondents ($1,000). 208 APPENDIX A The figures set forth show differences between the CPS and the census in terms of total income for 1950 and 1960. Similar comparisons by type of income were not made in 1950. They are available, however, for 1960, and are summarized in table A-20. Table A-20. -Consistency of Reporting by Type of Income in 1959 in the CPS and the Census, for Persons 14 Years Old and Over, by Sex: I960 Male Female Comparison of CPS and Census Wage or salary income Self- employ- ment income Income other than earnings Wage or salary income Self- employ- ment income Income other than earnings Recipients of specified type of income in CPS and Census.... 100 64 16 20 100 42 27 31 100 60 21 19 100 74 12 14 100 52 32 16 100 67 17 16 Percent in same interval in both Percent in higher interval in CPS Percent in higher interval in Census .... Persons without specified type of income in CPS 100 20 100 5 100 13 100 5 100 1 100 8 Percent with specified type in Census... Persons without specified type of income in 100 100 6 100 13 100 6 100 1 100 7 Percent with specified type in CPS 19 Median income: CPS $4,552 4,630 $2,959 2,855 $746 732 $1,926 1,938 $1,056 961 $739 715 Census Source : Unpublished data of the Bureau of the Census. The consistency of reporting in the CPS and the census for wages and salaries and income other than earnings is very similar to that described above for total income. For both men and women the medians reported for each type of income were virtually identical in the CPS and the census, as were the proportions of income recipients and the distributions by income levels. Simi- larly, the variability of response was about the same as for total income. About three-fifths of recipients were in the same income levels; 16 percent were in a higher class interval in the CPS than in the census, and 20 percent were in a higher interval in census than in the CPS. Although the median self-employment income was about the same in the CPS as in the census, the variability of response was much greater for this item than for wages or salaries or for income other than earnings. Only 42 percent of the men reporting this type of income were in the same class interval in both surveys; 27 percent were in a higher CPS class interval, and 31 percent were in a higher Census class interval. This pattern is very similar to that obtained in the 1950 C PS-Census matching study for persons classified as self- employed at the time of the census. In that study it was found that only 31 percent of the income recipients were in the same class interval in the CPS and the Census, 38 percent were in a higher CPS class interval, and 31 percent were in a higher Census class interval. In 1950, the median income for self- employed workers in the CPS was $1,800 compared with $1,500 in the census. 14 At first glance the similarity of the CPS and the Census medians for self- employment income seems inconsistent with the earlier finding that the 1960 EVALUATION OF CENSUS INCOME DATA 209 Census had a considerably higher aggregate self-employment income than the CPS. As previously noted (see table A-l) the Census aggregate for self- employment income was 112 percent of the OBE total compared with only 91 percent for the CPS. The larger Census aggregate, despite the similarity of the median self -employment income, is attributable to the considerably larger number of persons with self-employment income reported in the census. In the 1960 Census there were 11.4 million persons with self -employment in- come, compared with only 10.4 million in the CPS. The Census had fewer farm residents with self -employment income (2.8 million, compared with 3.3 million in the CPS) , but considerably more nonfarm residents with self -employment income (8.6 million in the Census, compared with 7.2 million in the CPS). The larger Census aggregate therefore appears to be due primarily to the considerably larger number of persons with nonfarm self -employment income reported in the census. It is hard to tell which estimate of the number of nonfarm residents with self-employment income is more reasonable. There is some possibility that the Census estimate is too high because of the misclassification of wages and salaries as self-employment income. Results of reinterview surveys On completing the field work in the 1950 and 1960 Censuses, intensive rein- terview surveys were conducted with relatively small samples of households for the purpose of detecting possible biases in the census results. About 25,000 households were reinterviewed in 1950, but income information was obtained for only about 5,000 households that were in the 20-percent sample. In 1960, the sample consisted of about 3,400 households previously included in the 25- percent Census sample. Reinterview surveys are intended to serve as benchmarks against which the census results can be compared. For this reason, the special measures described below were employed to help assure that more accurate results would be obtained. 15 Partly because of these measures, the field cost per person in the 1 950 reinterview survey was about 20 times that in the census. 1. In the reinterview survey, the income information was obtained whenever possible from the person himself; whereas in the census, information for all household members was obtained from any responsible member of the household. 2. In contrast to the more global questions used in the census, detailed "prob- ing" questions were asked in the reinterview survey. In 1950, questions were asked for all three types of income that were included in the census — wages and salaries, self -employment, and income other than earnings. The reinterview survey, in 1960, was restricted to income from self-employment and to income other than earnings. 3. For the reinterview survey, superior interviewers were selected and given more intensive training and closer supervision than was possible in the census. 4. The information obtained in the original census interview and in the reinterview was compared, case by case, and attempts were made to reconcile 210 APPENDIX A discrepancies in the field. In 1950, the reinterview survey enumerator had the census reports with him, and he tried to account for differences during the interview. In 1960, the results were compared in the office, and a special visit was made to reconcile discrepancies. Despite these efforts to obtain more accurate answers, the reinterview survey results have several shortcomings. In the first place, the accuracy of the infor- mation depends on how well the interviewers do their job, on the adequacy of the information provided by the respondents, and on their willingness to coop- erate. In addition, the effectiveness of the reinterview survey is reduced by the length of the interval between the two surveys. In 1950, most of the field work was not done until August or September, or about 4 to 5 months after the completion of the census, and 8 to 9 months after the end of the calendar year to which the income data pertained. In 1960, 1,400 households were inter- viewed in July, and the remaining 2,000 were not interviewed until October. In general, the reinterview surveys in 1950 and 1960 found a relatively large number of persons with small amounts of income who had reported no income in the census. For persons who reported $1 or more of income in both surveys, the overall results were very- similar despite considerable variability of individual response. Table A-21 shows that in 1960 about 9 percent of the women who reported no income in the reinterview survey were found to have reported $1 or more of income in the census, whereas proportionately twice as many women without income in the census were found to have reported $1 or more of income in the reinterview survey. These results are almost identical with those shown for 1950. The net effect of this difference was the addition of several million women with relatively small amounts of income to the reinterview survey dis- tributions. The average income for women, however, was about the same in the census and the reinterview survey, and the distributions by income level were also very similar. In the aggregate, therefore, the reinterview survey results do not differ substantially from those obtained in the census. The figures for men show essentially the same pattern for 1950 and 1960 as those described for women. Here again the averages and the distributions by income levels were very similar for both surveys; there was also a tendency for the reinterview survey to find a somewhat larger number of income recipients. Table A-21 also shows that the variability of response in the reinterview surveys is very similar to that obtained in the CPS-Census matching study. In 1950 and 1960 about three-fifths of the men were in the same income interval in both surveys; the remaining two-fifths were more or less equally divided between those who were in a higher interval in the census, and those who were in a higher interval in the reinterview survey. In each year there was a tend- ency for a slightly larger proportion to report higher incomes in the reinterview survey. The figures for women were very similar to those for men, except that a somewhat larger proportion of women were in the same income interval in both surveys. EVALUATION OF CENSUS INCOME DATA 211 Table A-21.— Consistency of Total Money Income Reporting in the Census and the reinterview survey, for persons 14 years old and over, by sex: 1960 and 1950 Comparison of Reinterview Survey (RES) and Census Male Female 1960 1950 1960 1950 Total reporting on income in RES and Census 100 100 100 100 60 61 71 76 24 24 20 16 16 16 10 8 100 100 100 100 63 62 66 74 22 22 21 15 16 16 13 11 Persons reporting no income in RES 100 100 100 100 i ft £} O 100 100 100 100 41 39 20 17 Median income: RES $4,501 $2,511 $1,578 $1,146 4,507 2,575 1,501 1,083 Nonrespondents in RES: 91 73 75 76 Median income in Census $4,182 $1,756 $887 $1,065 Nonrespondents in Census: 91 67 80 74 Median income in RES $4,833 $2,710 $2,283 $1,602 Source : Unpublished data of the Bureau of the Census. 212 APPENDIX A NOTES 1 The results of these studies are summarized in An Appraisal of the 1950 Census Income Data, Studies in Income and Wealth, Princeton University Press, Vol. 23, 1958. See reports by Herman P. Miller and Leon R. Paley, "Income Reported in the 1950 Census and on Income Tax Returns"; and B. J. Mandel, Irwin Wolkstein, and Marie M. Delaney, "Coordination of Old-Age and Survivors Insurance Wage Records and the Post- Enumeration Survey." 2 Ibid. Article by Marius Farioletti, "Some Income Adjustment Results from the 1949 Audit Control Program." 3 Ibid. Article by Selma F. Goldsmith, "The Relation of Census Income Distribution Statistics to Other Income Data." 4 Selma F. Goldsmith, "Size Distribution of Personal Income," Survey of Current Business, April 1958, p. 14. 5 Selma F. Goldsmith, "Low-Income Families and Measures of Income Inequality" (Mimeograph). Paper prepared for December 1961 meetings of the Catholic Economic Association, p. 8. 8 The following are three exceptions to the general rule: Income of Hawaii, published in 1953, contains personal income estimates for four counties; Income in Alaska contains 1957 personal income estimates for the southeastern, central, and western parts of that State; and "Measuring Regional Market Growth — A Case Study of the Delaware River Area," Survey of Current Business, January 1959, contains personal income estimates for 8 subregions in this 53-county area. 7 This report contains an excellent summary of the sources of income data for small areas including the names and addresses of all agencies that were engaged in the prep- aration of such estimates in the spring of 1960. 8 Statement of Richard S. Ostheimer, Director of Research, Life magazine at Hearings on Mid-Decade Census, Subcommitte on Census and Government Statistics, 87th Cong., 1 st sess., November 29 and 30, 1 96 1 , p. 474. 9 See Sales Management, Survey of Buying Power, July 10, 1960. 10 Ibid., p. 56. 11 Ibid., p. 60. M Ibid., p. 60. 13 U.S. Bureau of the Census. Family and Individual Money Income in the United States: 1945 and 1944, Series P-S, No. 22, May 1947, p. 5. u Herman P. Miller, "An Appraisal of the 1950 Census Income Data," Journal of the American Statistical Association, March 1953, p. 35. 15 For a more detailed description of these procedures see, Bureau of the Census, The Post-Enumeration Survey: 1950; Technical Paper No. 4, 1960. APPENDIX B COMPUTATION OF CONSTANT DOLLARS, QUINTILES, AGGREGATES, AND ■ GINI RATIOS Constant dollar computations Each year since 1947 the Bureau of the Census has published a report (Series P-60) showing the distribution of families and unrelated individuals by income levels, cross-classified by such characteristics as urban-rural residence; age, sex, color; employment status, occupation and industry of head; size of family, and number of children. Similar tabulations were made for males and females classified by the amount of their own income and by various personal charac- teristics. The income distributions shown in these reports are in current dollars, and the classes used have generally been $500 levels up to $4,999; $1,000 levels from $5,000 to $7,999; $8,000 to $9,999; $10,000 to $14,999; $15,000 to $24,999; and $25,000 and over. For purposes of this study, the published current-dollar distributions were converted into distributions of constant dollars in terms of 1959 purchasing power, and also into distributions based on the income limits for each fifth of all families for each year. A brief description of the procedures used to make these conversions follows. A punchcard was prepared for each column of each table, showing the number of families at each income level. For example, a single punchcard might rep- resent 2-person families in 1950. The first field in this card would represent the total number of 2-person families; the second field, the number with income under $500; the third field, the number with incomes from $500 to $999; etc., until each income level was accounted for. The second step required the subdivision of broad income intervals (such as $7,000 to $9,999, and $10,000 to $14,999) into smaller intervals to provide a more refined basis for interpolation to convert to constant dollars, and also to compute aggregate income. This subdivision was accomplished from generalized tables prepared from Pareto curves that were fitted to frequency distributions having varying degrees of concentration in the open-end limits. 1 The specific factors used for each year and for each interval are shown below. 213 214 1947-48 APPENDIX B 1949-58 F 10 f 6-10 f 6-7 f 7-8 f 8-9 f 9-10 Under 2.0 100 35 27 21 17 2.0-2.9 100 40 27 19 14 3.0-3.9 100 44 27 17 12 4.0* 100 45 27 17 11 6 _ ratio of cumulative frequencies above $6,000 F. n ~ to cumulative frequencies above $10,000. m-n Z frequencies between $m000 and $n000 as a per- cent of the frequencies between $6,000 and $10,000. F 7 F 10 f 7-10 f 7-8 f 8-9 f 9-10 Under 1.9 100 43 32 25 2.0-2.4 100 47 31 22 2.5+ 100 50 30 20 _ ratio of cumulative frequencies above $7,000 F, n — to cumulative frequencies above $10,000. m-n - frequencies between $m000 and $n000 as a per- cent of the frequencies between $7,000 and $10,000. 1959-60 1951-60 F 8 F 10 f 8-10 f 8-9 f 9-10 ■5 f 10-15 f 10-ll f ll-12 f 12-13 f 13-14 f 14-15 Under 2.0 100 42 Under 2.9.. 100 32 24 18 14 12 2.0-2.4 100 62 38 3.0-3.9 100 35 24 18 13 10 2.5+ 100 65 35 4.0+ 100 37 25 17 12 9 I ratio of cumulative frequencies above $8,000 to cumulative frequencies above $10,000. ? 15 ratio of cumulative frequencies above $10,000 to cumulative frequencies above $15,000. "m-n s frequencies between $m000 and $n000 as a per- cent of the frequencies between $8,000 and $10,000. m-n r frequencies between $ra000 and $n000 as a per- cent of the frequencies between $10,000 and $15,000. After the detailed frequency distributions were prepared, the income limit for each interval was adjusted by a factor representing the change in the Con- sumer Price Index, using 1959 as the base. The following factors were used for each year: 1947 . 76.6 1954 92. 1 1948 . ___ 82. 5 1955 _ _ 91.9 1949 _ 81. 7 1956 _ . 93. 3 1950 82.5 1957 96.5 1951 _ _ 89. 1 1958_ _ 99. 1 1952 91. 1 1959 100.0 1953 91.8 1960 101.5 The Consumer Price Index is basically a measure of changes in prices of the goods and services bought by urban "wage earner and clerical worker families" representing about two-thirds of all persons living in urban places, and about two-fifths of the total United States population. The same index was used for all groups because separate price indexes have not been developed for various income levels. Nor did the available data permit adjustment for the fact that the price index is strictly applicable to consumer expenditures for goods and services, whereas the family income data also cover family savings and income tax payments. For these and other reasons, the estimates, partic- ularly in the income range over $10,000, are to be regarded as approximations. COMPUTATION OF INCOME MEASURES 215 Computation of distributions by quintiles The first step in preparing the distributions of income by quintiles was the calculation for each year of the dollar value representing the income limit for each fifth of families ranked from lowest to highest according to income. These dollar values are shown in table B-l. Thus, for example, in 1950, the poorest 20 percent of the families had incomes under $1,665, the wealthiest 20 percent had incomes over $5,357, and the wealthiest 5 percent had incomes over $9,070. The punchcards prepared for each column of each table, showing the number of families by income level, were then put through a computer program which provided by straight-line interpolation the number of families within the income limits designated by the quintile values. In effect, therefore, the CPS data were retabulated for each year, using the income limits of the quintiles rather than the dollar values shown in the published reports. Table B-l.— Dollar Values Used to Compute Characteristics of Families, by Quintiles, and for Top 5 Percent: 1947 to I960 Year Lowest quintile Second quintile Middle quintile Fourth quintile Highest quintile Top 5 percent 1960 Under $2,798 $2,799-$4,8l2 $4,813-$6,472 $6,473-$8,992 $8,993 and over $14,385 and over 1959 Under $2,713 $2, 714- $4, 612 $4, 613- $6, 209 $6,210-$8,548 $8,549 and over $14,010 and over 1958 Under $2,564 $2, 565- $4, 341 $4,342-$5,825 $5,826-$8,233 $8,234 and over $13,355 and over 1957 Under $2,491 $2,492-$4,254 $4,255-$5,662 $5, 663- $7, 882 $7,883 and over $12,690 and over 1956 Under $2,451 $2,452-$4,119 $4,120-$5,511 $5,512-$7,672 $7,673 and over $12,460 and over 1955 Under $2,228 $2,229-$3,785 $3, 786- $5, 110 $5,111-$6,916 $6,917 and over ,$11,355 and over 1954 Under $2,018 $2,019-$3,551 $3,562-$4,813 $4,8l4-$6,635 $6,636 and over $10,910 and over 1953 ' Under $2,132 $2,133-$3,634 $3, 635- $4, 870 $4, 671- $6, 605 $6,606 and over $10,245 and over 1952 Under $2,052 $2,053-$3,340 $3, 341- $4, 494 $4,495-$6,107 $6,108 and over $9,736 and over 1951 Under $1,959 $l,960-$3,207 $3, 208- $4, 239 $4, 240- $5, 815 $5,816 and over $9,481 and over 1950 Under $1,665 $l,666-$2,860 $2,861-$3,822 $3,823-$5,356 $5,357 and over $9,070 and over 1949 Under $1,540 $l,541-$2,635 $2,636-$3,568 $3, 569- $5, 051 $5,052 and over $8,680 and over 1948 Under $1,656 $1,657-$2,721 $2,722-$3,649 •$3,650-$5,086 $5,087 and over $9,104 and over 1947 Under $1,580 $1,581-$2,561 $2,562-$3,469 $3, 470- $4, 926 $4,927 and over $8,968 and over Source: Derived from U.S. Bureau of the Census, Current Population Reports— Consumer Income, Series P-60, annual reports. Computation of aggregates Aggregates were obtained by multiplying the estimated number of families at each income level by the average income for that level. Since $500 or $1,000 levels were used below $10,000 for 1947 to 1949, and below $15,000 thereafter, the midpoint of each interval below the open end was assumed to be the average. A value of $19,000 was used for the $15,000 to $24,999 interval. In general, the average for the open-end interval ($10,000 and over for 1947 to 1949, $15,000 and over for 1950, and $25,000 and over thereafter) was obtained by fitting a Pareto curve to the data. This average was obtained by substituting in the formula shown below. Where the shape of the curve sug- gested that the Pareto fit did not apply (i.e., where the frequencies in the open-end interval exceeded those in the adjacent interval), $20,000 was used as the average for $10,000 and over, $24,000 for $15,000 and over, and $44,000 for $25,000 and over. 216 APPENDIX B V x= c—d b—a X— lower limit of open-end interval. a = Logarithm of lower limit of interval preceding open end. b = Logarithm of lower limit of open-end interval. c — Logarithm of the sum of the frequencies in the open-end interval and the one preceding it. d = Logarithm of the frequencies in the open-end interval. This method of estimating the mean for the upper ranges of an income dis- tribution is based largely on the empirical observations of Vilfredo Pareto during the closing years of the last century. While studying income tax data for various European countries, this investigator found that the upper ranges of the income distribution could be described by a curve of the general type, Y = AX~ V , where X is the income size and Y is the number of persons having that income or larger. The logarithmic form of this curve (Log Y= Log A—V Log X) is, of course, a straight line. That is, if the logarithms of the income sizes are charted on a horizontal scale and the logarithms of the number of persons having an income of a particular size or larger are charted on a vertical scale, the resulting points will fall on a straight line. Graphically, the curve would appear as shown in figure B-l. 2 A mathematical procedure can be devised for estimating the mean for the upper ranges of a curve of this type. The general expression for the mean of the interval from $10,000 to infinity is shown below. In this expression, X is the lower limit of the open-end interval and Y is the number of families and individuals having an income of that amount or greater. f* 00 XYdx TP J 10.000 ^ — — /Too Ydx J 10. 000 An expression for Y in this formula can be obtained by reducing the cumula- tive form of the Pareto curve (Y--=AX- V ) to its noncumulative form; i.e., the first derivative: V x v+i J Substituting this expression in the formula for the mean yields the expression: J 10.000 \ / X ! f- AV — T y T7 _L 1 dX J 10, 1 000 which when reduced gives : X=X COMPUTATION OF INCOME MEASURES 217 In the above expression, X is the lower limit of the open-end interval ($10,000 in this case) and V is the slope of the income curve, which is a straight line Figure B-l.— Pareto Curve Showing Distribution of Families and Unrelated Individuals, by Income Levels: 1959 \ A V=Slo thr (Se pe of 3Ugh | e text line Doint • for pas s A exp sin an Ian g d atic B )n ) ^ B" 5 10 Income size (thousands of dollars) 50 100 Source : Herman P. Miller, Trends in the Income of Families and Persons in the United States, 1947 to 1960, U.S. Bureau of the Census, Technical Paper No. 8, 1963. 218 APPENDIX B Table B-2.— Actual and Computed Estimates of Adjusted Gross Incomes for 100 Standard Metropolitan Statistical Areas Based on Income Tax Re- turns for 1959 [Numbers in thousands. Minus sign ( — ) denotes decrease] Standard metropolitan statistical area Actual Computed Difference Difference as a of actual $1 117 $1,115 -$2 0.2 1. 197 1,213 16 1.3 Allentovn-Bethlehem-Easton, Pa. -N.J 861 870 9 1.0 1. 737 1,725 -12 0.7 520 547 27 5.2 3, 308 3,380 72 2.2 474 511 37 7.8 959 1,042 83 8.7 5, 114 5^362 248 4.8 825 837 12 1.5 2, 610 2,671 61 2.3 579 585 6 1.0 429 431 2 0.5 468 474 6 1.3 419 425 6 1.4 615 14,746 131 0.9 2, 161 2,155 -6 0.3 Cleveland Ohio. 3, 904 3 970 66 1 7 1, 266 1*295 29 2.3 2, 037 2,050 13 0.6 512 512 - - 1 346 1,372 26 1.9 1) 838 1,900 62 3.4 533 543 10 1.9 7, 694 7,751 57 0.7 433 438 5 1.2 413 434 21 5.1 Flint, Mich 630 594 -36 5.7 991 988 -3 0.3 470 528 58 12.3 947 974 27 2.9 661 661 - - 637 672 35 5.5 i, 209 1,226 17 1.4 784 804 20 2.6 2, 220 2,265 45 2.0 344 309 -35 10.2 Indianapolis Xnd*. 1, 453 1 474 21 1.4 758 761 3 0.4 1, 238 1,242 4 0.3 326 321 -5 1.5 2, 038 1,998 -40 2.0 538 539 1 0.2 433 443 10 2.3 491 495 4 0.8 385 400 15 3.9 15, 098 15,218 120 0.8 T.mi t ^vi lip Kv — TnH 1, 215 1 222 7 0.6 871 '870 -1 0.1 1, 653 1,820 167 10.1 2, 589 2,595 6 0.2 2, 947 2,996 49 1.7 445 463 18 4.0 630 647 17 2.7 4$ 004 4,060 56 1.4 686 696 10 1.5 If 377 1,389 12 0.9 25, 918 26,348 430 1.7 719 736 17 2.4 805 753 -52 6.5 811 834 23 2.8 2, 601 2,607 6 0.2 632 751 119 18.8 8, 216 8,244 28 0.3 1, 018 1,057 39 3.8 4, 635 4, 662 27 0.6 If 536 1,553 17 1.1 If 394 1, 396 2 0.1 486 606 120 24.7 776 812 36 4.6 — Represents zero. COMPUTATION OF INCOME MEASURES 219 Table B-2.— Actual and Computed Estimates of Adjusted Gross Incomes for 100 Standard Metropolitan Statistical Areas Based on Income Tax Re- turns for 1959— Con. [Numbers in thousands. Minus sign ( — ) denotes decrease] Standard metropolitan statistical area Actual Computed Difference Difference as a percent of actual $1,352 $1,419 $67 5.0 1,020 1,029 9 0.9 n ■ t * _ xa — -n i 3,791 3,761 -30 0.8 64-9 656 7 1.1 896 896 — 1, 298 1, 314 16 1.2 1,938 1,993 55 2.8 6,385 6, 394 9 0.4 1,410 1,414 4 0.3 317 303 -14 4.4 2,295 2, 300 5 0.2 409 451 42 10.3 469 494 25 5.3 469 460 -9 1.9 812 822 10 1.2 378 (ma) (NA) (NA) 1,072 1, 079 7 0.7 564 574 10 1.8 1,085 1,129 44 4.1 887 893 6 0.7 574 575 1 0.2 778 784- 6 0.8 516 529 13 2.5 4, 315 4,251 -64 1.5 598 598 477 471 -6 1.3 855 783 -72 8.4 521 500 -21 4.0 436 (NA) (NA) (NA) 909 904 -5 0.6 — Represents zero. NA Could not be estimated from the published data. Source: Internal Revenue Service, Statistics of Income 1959, 1960, and 1961, Income Tax Returns, State and Metropolitan Areas. when plotted logarithmically. The method for determining the value of V has been described above. In view of the many different types of income distributions to which Pareto curves were fitted using the procedures described above, a rough test was made of the validity of this method using income tax data for 1959. The Internal Revenue Service has published figures on adjusted gross income, by detailed income classes, for the 100 largest standard metropolitan statistical areas (SMSA's) . 3 These figures are based directly on the amounts of income reported on tax returns. Independent estimates were made for each city by consolidating the income classes at the upper end of the distribution into two groups — "$15,000 to $25,000" and "$25,000 and over" — and fitting a Pareto curve to the open-end interval using the procedures previously described. The actual and computed estimates of aggregate income are shown for each SMS A in table B-2. In 69 SMSA's the computed estimates differ from the actual by less than 3 percent; in 19 cases the difference was 3 to 5 percent; in 6 cases it was 6 to 9 percent; and in only 6 cases was it 10 percent or more. These data provide some support for the view that the Pareto curve produces fairly reliable estimates of aggregate income in a wide variety of situations. 220 APPENDIX B Further evidence in support of this position comes from consistency checks that were applied to aggregates obtained from overall distributions and from distributions by major occupation groups. Annual estimates of aggregate in- come were prepared, using Pare to curves, for 1948 to 1960 for all males, based on overall distributions by income level. Corresponding estimates were pre- pared by major occupation groups which were summed to obtain an overall aggregate. In only 4 years did the difference between the global estimate and the estimate obtained by summing the occupations differ by as much as 3 per- centage points; the more typical difference was 1 or 2 percentage points sug- gesting that the use of Pareto averages for specific occupations did not produce major changes in the overall aggregate. Computation of Gini Index of Concentration The Gini Index of Concentration is a measure of income concentration that is derived from the Lorenz curve which is obtained by plotting the cumulative percent of units (families or persons) on the X axis against the cumulative per- cent of the aggregate income accounted for by these units on the Y axis, as shown below. If all units had exactly the same incomes, the Lorenz curve would be represented by the diagonal shown in the diagram. Curves drawn to actual data invariably fall below this line and the greater the inequality in the distribution of income, the greater the area between the diagonal line and the Lorenz curve. Figure B-2. — Illustrative Example Showing Computation of Gini Index of Concentration f, f 100 Percent of units Source : Herman P. Miller. Trends in the Income of Families and Persons in the United States, 1947 to 1960, U.S. Bureau of the Census, Technical Paper No. 8, 1963. COMPUTATION OF INCOME MEASURES 221 The Gini Index of Concentration is defined as the proportion of the total area under the diagonal that is between the diagonal and the Lorenz curve. 4 This relationship can be expressed as follows, using the notation in figure B-2 above: T A area between curve and diagonal A -\-B area under diagonal Since the cumulative percents on each axis add to 100, the area in the entire square is 1 and the area under the diagonal is 1/2. Therefore, the' expression above can be rewritten as follows : T 1/2 — Area under curve n . , N L=— =1—2 (area under curve) If we assume that the curve between any two points is approximated by a straight line, the area for any segment of the curve can be expressed as follows : \Ji+l~Ji) 2 When summed over all intervals, the area under the curve is s (/<+.-/,) (y<+ /' +l) j=i ^ Substituting in the expression for L above yields the formula that was used in computing the Gini Index : £=1-2 S (/«+.-/«) {y '\ y,+,} £=1-S (/< + .-/ i )(2/ i + 2/ ( +.) t'=l NOTES 1 These tables were prepared by Hyman Kaitz of the U.S. Bureau of Labor Statistics. 2 Pareto's observations have been subjected to repeated study and although his in- ferences, which came to be known as "Pareto's Law," have been largely refuted, his statistical observations regarding the upper ranges of the income distribution appear to be generally sound even today, and his mathematical formulation is widely used as the basis for estimating the average for the open-end of an income distribution. 3 Internal Revenue Service, Statistics of Income 1959, I960, and 1961 , Income Tax Returns, State and Metropolitan Areas. 4 This presentation is based on James Morgan, "The Anatomy of Income Distribution," The Review of Economics and Statistics, August 1962, p. 281. APPENDIX C OCCUPATIONAL CLASSIFICATION AND STATISTICAL TABLES USED TO MEASURE WAGE TRENDS FOR DETAILED OCCUPATIONS See chapter IV for a discussion of the source and limitations of the data. The list below shows the detailed occupations included in each of the inter- mediate occupation groups for which data are shown in the tables that follow. Detailed occupations are not shown where the intermediate occupation group consists of only one detailed occupation. The abbreviation "n.e.c." means "not elsewhere classified." The figure "1960" appearing in parentheses after a detailed occupation indicates that the occupation was added to the intermediate group in 1960, but was not included in that group in 1940 or 1950. Occupational Classification Professional, Technical, Kindred Workers 1. Artists and art teachers 2. Authors, editors, and reporters Authors Editors and reporters Public relations men and publicity writers (1960) 3. Chemists 4. Clergymen 5. College presidents, professors, in- structors (n.e.c.) 6. Designers and draftsmen Designers Draftsmen 7. Engineers, civil 8. Engineers, electrical 9. Engineers, mechanical Aeronautical engineers Mechanical engineers Technical engineers (n.e.c.) Sales engineers (1960) 10. Musicians and music teachers 11. Pharmacists 12. Social, welfare, and recreation workers Recreation and group workers Social and welfare workers, ex- cept group 13. Sports instructors, athletes, enter- tainers Athletes Dancers and dancing teachers Entertainers (n.e.c.) Sports instructors and officials 14. Teachers Farm and home management ad- visors Teachers (n.e.c.) Teachers, elementary schools (1960) Teachers, secondary schools (1960) 223 224 APPENDIX C Salaried Managers and Officials 15. Conductors, railroad 16. Postmasters, and miscellaneous gov- ernment officials Inspectors, public administration Federal public administration and postal service State public administration Local public administration Officials and administrators (n.e.c), public administra- tion Federal public administration and postal service (n.e.c.) State public administration (n.e.c.) Local public administration (n.e.c.) Postmasters Managers and officials 17. Manufacturing 18. Transportation, communication, and other public utilities Transportation Telecommunications, and utili- ties and sanitary services 19. Wholesale trade 20. Eating and drinking places 21. Retail trade, except eating and drinking Food and dairy products stores, and milk retailing General merchandise and five and ten cent stores Apparel and accessories stores Furniture, home furnishings, and equipment stores Motor vehicles and accessories retailing Gasoline service stations Hardware, farm implement, and building material retail- ing Other retail trade 22. Finance, insurance, and real estate Banking and other finance Insurance and real estate 23. Business and repair services Business services Automobile repair services and garages Miscellaneous repair services 24. Personal services Clerical, Sales, and Kindred Workers 25. Baggagemen, express messengers, railway mail clerks Baggagemen, transportation Express messengers and railway mail clerks 26. Bookkeepers, accountants, cashiers, ticket agents Accountants Bookkeepers Cashiers Ticket, station, and express agents 27. Mail carriers 28. Messengers, except express Messengers and office boys Telegraph messengers 29. Shipping and receiving clerks 30. Stenographers, typists, and secre- taries 31. Telegraph operators 32. Newsboys 33. Insurance agents and brokers Insurance adjusters, examiners, and investigators (1960) 34. Real estate agents and brokers 35. Salesmen and sales clerks (n.e.c.) Manufacturing Wholesale trade Retail trade Other industries (including "not reported" ) Craftsmen, Foremen, and Kindred Workers 36. Bakers 37. Blacksmiths, forgemen, and hammer- men Blacksmiths Forgemen and hammermen 38. Boilermakers 39. Cabinetmakers and patternmakers Cabinetmakers Pattern and model makers, except paper 40. Carpenters 41. Compositors and typesetters 42. Electricians Foremen (n.e.c.) 43. Construction 44. Manufacturing Metal industries Machinery, including electrical Transportation equipment Other durable goods Textiles, textile products, and apparel Other nondurable goods (in- cluding "not specified" manu- facturing) 45. Transportation, communication, and other public utilities Railroads and railway express service Transportation, except railroad Telecommunications, and utili- ties and sanitary services 46. Inspectors (n.e.c.) Construction Railroads and railway express service Transportation except railroad, communication, and other pub- lic utilities Other industries including ("not reported" ) DATA ON WAGE TRENDS BY OCCUPATION 225 47. Linemen and servicemen, tele- graphers, etc. 48. Locomotive engineers 49. Locomotive firemen 50. Machinists, millwrights, and tool- makers Job setters, metal Machinists Millwrights Toolmakers, and die makers and setters 51. Masons, tile setters, and stone cutters Brickmasons, stonemasons, and tile setters Stone cutters and stone carvers 52. Mechanics and repairmen, and loom fixers Loom fixers Mechanics and repairmen Airplane Automobile Office machine Radio and television Railroad and car shop Not elsewhere classified 53. Molders, metal 54. Painters (construction), paperhang- ers, glaziers Glaziers Painters, construction and main- tenance Paperhangers 55. Plasterers and cement finishers Cement and concrete finishers Plasterers 56. Plumbers and pipe fitters 57. Printing craftsmen, except composi- tors and typesetters Electrotypers and stereotypers Photoengravers and lithographers Pressmen and plate printers, print- ing 58. Rollers and roll hands, metal 59. Roofers and sheet metal workers Roofers and slaters Tinsmiths, coppersmiths, and sheet metal workers 60. Shoemakers and repairers, except factory 61. Stationary engineers, cranemen, hoistmen Cranemen, derrickmen, and hoist- men Excavating, grading, and road machinery operators Stationary engineers 62. Structural metal workers 63. Tailors and furriers Furriers Tailors Operatives and Kindred Workers 64. Apprentices Auto mechanics Bricklayers and masons Carpenters Electricians Machinists and toolmakers Mechanics, except auto Plumbers and pipe fitters Building trades (n.e.c.) Metal working trades (n.e.c. ) Printing trades Other specified trades Trade not specified 65. Attendants, auto service and parking 66. Brakemen and switchmen, railroad Brakemen, railroad Switchmen, railroad 67. Drivers — bus, taxi, and truck, and deliverymen Bus drivers Deliverymen and routemen Taxicab drivers and chauffeurs Truck and tractor drivers 68. Stationary firemen 69. Mine operatives and laborers (n.e.c.) Coal mining Crude petroleum and natural gas extraction Mining and quarrying, except fuel 70. Motormen — railway, mine, factory, etc. Motormen — mine, factory, log- ging camp, etc. Motormen — street, subway, and elevated railway 71. Painters, except construction and maintenance 72. Sailors and deck hands 73. Welders and flame-cutters Operatives and kindred workers (n.e.c. ) 74. Food and kindred products Meat products Dairy products Canning and preserving fruits, vegetables, and sea foods Grain-mill products Bakery products Confectionery and related prod- ucts Beverage industries Miscellaneous food preparations and kindred products Not specified food industries Packers and wrappers (n.e.c.) (I960) 75. Knitting mills Knitters, loopers, and toppers, textile (1960) 226 APPENDIX C 76. Textile mill products, except knit- ting mills Spinners, textile Weavers, textile Dyeing and finishing textiles, except knit goods Carpets, rugs, and other floor coverings Yarn, thread, and fabric mills Miscellaneous textile mill prod- ucts Graders and sorters, mfg. (1960) 77. Apparel and other fabric textile products Apparel and accessories Miscellaneous fabricated textile products Sewers and stitchers, mfg. (1960) 78. Furniture, and lumber and wood products Sawmills, planing mills, and mill work Miscellaneous wood products Furniture and fixtures 79. Paper, paper products, and print- ing Bookbinders Pulp, paper, and paperboard mills Paperboard containers and boxes Miscellaneous paper and pulp products Printing, publishing, and allied industries 80. Chemicals and petroleum, and coal products Synthetic fibers Drugs and medicines Paints, varnishes, and related products Miscellaneous chemicals and allied products Petroleum refining Miscellaneous petroleum and coal products 81. Rubber products 82. Footwear industries, except rubber 83. Leather and leather products, ex- cept footwear Leather — tanned, curried, and finished Leather products, except foot- wear 84. Stone, clay, and glass products Glass and glass products Cement and concrete, gypsum, and plaster products Structural clay products Pottery and related products Miscellaneous nonmetallic min- eral and stone products See footnote on page 227. 85. 1 85a. 1 8b. 87. 88. 89 90 91 92 Primary metal industries (1960) Blast furnaces, steel works, and rolling and finishing mills • Other primary iron and steel industries Primary nonferrous industries Fabricated metal industries (incl. not spec, metal) (1960) Cutlery, handtools, and other hardware Fabricated structural metal products Miscellaneous fabricated metal products Not specified metal industries Machinery Agricultural machinery and tractors Office and store machines and devices Miscellaneous machinery Electrical machinery, equip- ment, and supplies Assemblers (1960) Checkers, examiners, and in- spectors, mfg. (1960) Motor vehicles and motor vehicle equipment Transportation equipment, except motor vehicle Aircraft and parts Ship and boat building and repairing Railroad and miscellaneous transportation equipment Service Workers Private household workers Housekeepers, private household Living in Living out Launderers, private household Living in Living out Private household workers (n.e.c. ) Living in Living out Baby .sitters (1960) Firemen, fire protection Guards and watchmen Guards, watchmen, and door- keepers Watchmen (crossing) and bridge tenders Policemen, sheriffs, and marshals Marshals and constables Government Private Sheriffs and bailiffs 93. Barbers, beauticians, and manicurists Hairdressers and cosmetologists (1960) DATA ON WAGE TRENDS BY OCCUPATION 227 106. Chemicals and petroleum, and coal products Synthetic fibers Drugs and medicines Paints, varnishes, and related products Miscellaneous chemicals and allied products Petroleum refining Miscellaneous petroleum and coal products 107. Stone, clay, and glass products Glass and glass products Cement and concrete, gyp- sum, and plaster products Structural clay products Pottery and related products Miscellaneous nonmetallic mineral and stone products 1 08. 1 Primary metal industries ( 1 960 ) Blast furnaces, steel works, and rolling and finishing mills Other primary iron and steel industries Primary nonferrous industries 108a. 1 Fabricated metal industries (incl. not spec, metal) (1960) Cutlery, handtools, and other hardware Fabricated structural metal products Miscellaneous fabricated metal products Not specified metal industries 109. Machinery Agricultural machinery and tractors Office and store machines and devices Miscellaneous machinery Electrical machinery, equip- ment, and supplies 110. Motor vehicles and motor vehi- cle equipment 111. Transportation equipment, ex- cept motor vehicle Aircraft and partis Ship and boat building and repairing Railroad and miscellaneous transportation equipment Nonmanufacturing industries : 112. Construction Carpenters' helpers (1960) 113. Railroads and "railway express service 114. Transportation, except railroad Truck drivers' helpers (1960) 115. Telecommunications and utili- ties and sanitary services 116. Wholesale and retail trade Warehousemen (n.e.c. ) (1960) 1 Items designated 85 and 85a, and 108 and 108a, have been merged in the tables which follow for comparability with data for 1939 and 1949 which were not shown separately. 94. Charmen, janitors, and porters Charmen and cleaners Janitors and sextons Porters 95. Cooks, except private household 96. Elevator operators 97. Waiters, bartenders, and counter workers Bartenders Counter and fountain workers Waiters 98. Service workers, except private household (n.e.c.) Kitchen workers, exc. private household (n.e.c.) (1960) Laborers, Except Farm and Mine 99. Fishermen and oystermen 100. Longshoremen and stevedores 101. Lumbermen, raftsmen, and wood- choppers Laborers (n.e.c.) : Manufacturing industries : 102. Food and kindred products Meat products Dairy products Canning and preserving fruits, vegetables, and sea foods Grain-mill products Bakery products Confectionery and related products Beverage industries Miscellaneous food prepara- tions and kindred products Not specified food industries 103. Textiles, textile products, and apparel Knitting mills Dyeing and finishing textiles, except knit goods Carpets, rugs, and other floor coverings Yarn, thread, and fabric mills Miscellaneous textile mill products Apparel and accessories Miscellaneous fabricated tex- tile products 104. Furniture, and lumber and wood products Sawmills, planing mills, and mill work Miscellaneous wood products Furniture and fixtures 105. 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S N S «0 TO TO \t Nt mm «\ m m lOiANftMiAniAvOvOON >AinHff«>0»CMMMS riNfcMOtOTOScMONO cM>ouN>ON)-r on cNj c^nnoo^l-in^t n n Nt \f Nf m n» cn p in TO rH On in N n m t-N> HifNniAn(Mrii*MMrl >t-vft>ONrHCNimtONONO TOt^ONf-CNlC3rH!CNHQ ^ cH m rH L OTOlflNj'fNOSTOS* rH vl-CNlcnCNlcnCNiCNJcn ONCNjt>TO>l-vnOrH -4-TON0cr\r-iTOrHm CNj>i--5>i-o>neN.N0 >n t> t> cn «♦ ■ C\l-strHCNlC~cnf-TO OTOOCnJHnPnPTO^ CMCNlCMCMCNJcn-^rN, CvlCNimcricn-NtCn inmNtCNlrH-^ONCNlrH NtCM>fCMHrlCMH DATA ON WAGE TRENDS BY OCCUPATION 239 3 cf 1 u o 5= u I I ■h -p id 5 I I v "a S ?3 C V a u C o q -p •H td I -P *H C 3 s g w c X O HU 2 I ~ o w X .. a! w < O g 8 '. >- as 1 < U U o t> ia NO ON to o c- o n lAIs-NOstcnststcncncn own lANDsftONOC-iAHNOiA o- cm to sfrHD-NOiAcnONC-CMto « vD 0> CMrHstSf[>cnmsfrHst cn !A CM sfcncnststsfsfstiAst i-l IA IA CM CM N W > m » o n no> >o 88 vO j c\i H to O Ots-NOCMtONOONOlACM on cn rH i-i o no to NO NT o on to ia on on lAcnstiAiAiAiAiAiAiA st st m st st cm ia NOcncntocncnOststt*- u> M m tONOOONststOt>t>iA nvO^ CMONCMsttOcnNOstrHlA cn ia cm stCMcnstststststiAst nootopi t> ON IA tO CM t> cn st to to cn st st en en On cm o st rH cn o> cn st NOstNOrHlAOO-tOtOON vO m m rH in CM st st NO H S C- rH to cn cncMCMrnrncncncnstcn CM cn A CM CM st vO st CM st stONtOC-OONCnts-rHm CN.NOIANO'ANOcn'AStNO cnCMcnCMCMCMCMCNJCMCM NO ON O \0 CM IA i-H IA to cn cn CM cn CM st vO IA O CM t> O O NO O NOstCMCMcnstNONOcnC- HcnCMlArHNOCMHNOtO ONnOOnnOnOvOIAnOiAnO CM O st NO O CM ON to H CM ON St ON L C*^ rH to cn O no en rH NO n cnoNONcnC~-cnrHiA^OH strHs>tOONOO"AtOCM cnNONOOrHNOONOrHNO cncMCMcnstcncncnstcn >A CM CM >A O cn cn cn cn cm st o CM ia o cn en CM rH On IA st CO st st On . . O st 0- On st m st h tn cm st >a srcncnstiAsfststiAst vO st to to CM rn On IA IA O CM nO On NO H ■s — »\ »» r\ st st st st st IA t> NO OlANOlArHcntOIACnrH HOO>0\00>Or|CltN mNocnoNCMNOooNstto cncMCMcnstcnstcnstcn h st to o t>- lA CM IA st rH tO O cn st rH cm st m cn cm ° O t~- IA tD H O [n OstCMC>NOC^rHtOt>tO CM to O CM On to i — I r~- vO cn t~-c^cniAfe)rnoNiAOcn rHrHrHCMCMCMCMCMcnCM IA rH rH cn St IA NO H ON IA St tO NO H t~- 240 APPENDIX G X X < w o 00 ON « ^ > Z — * g 8o * a < n O > o * < pf u. U O ft o < oc X Q z d o > tu O Q w u w z — m Z w a ft 5. x a E c B m c o < CN V/-1 X h (A at « 2 ui at 8^ z > >- < at -> p ■ u, jj o I - J3 -p 60 Cm rl -p T3 -P •H tH B si O -P a> •»-* co a co -p o •c I WNHOvOH OONO^tOC-ON-NtOO 00 On CN. nD c> CI NH!MHn>CO»CM ci c> cn. cn, c\ cn, (^nn^nncif^ cn. cm cMmc\ooONNO*oco >* O O O rH O C0 NT cm c\ Oi (0 H Q Q »1 iflvO CM CM CM Nt CN, fvl CM CM CM CM CM CMO^frHONCMC^CM to n in h n ^ O C~- t> t> O N0 vOlAC^>ArHOO>A rH^TsfNONOCMOC^ >tr-CN.c«-voininm n H vO m n O vOiHOrHvD^Om •>t ^ ir\ n ^ \0 iniomrim^nm com ooonnto^ill no in <-i>fOcnr>i-irHi-i to en t> on on 1A iTi n >t m H HONCM H^niM \o vo cMft to o*ooc"*c^Nr^rto rH rH o o CM to in^ciHOWiOO • ••••••• i£>ONNONO00t>NO>r rH rH CI rH C~- H >C H Nf tO oooooo oooooooo 888888 88888888 oo oooooooo 88 88888888 oooooo Q n f- CMCNrHCNinCM00I> NO rH CI (> rH m mN*tOO«^ >ooOrlOm CM CMCMCMiH^fr-liAr-l >TtOCMC~tOCMCMtO O CT> Nf >J O rH CM NO CM On CM *vf vn co v\ "\f o vo O tri (H m C~- CO 0* >f CM C0 CO r- vo r- >f co -7 nO* r- C~">f C- nO* Hr> «nC-c\o>QOOOO NOOt^CMCNOOCMCM rHrHC^-icM^C^O ooo^comr-mmm C'CtOmvOtOtom -\t O C v£) n H 00 00 CM >r vO I i-l >o CN. 00 CM op i— 1 00 NO -nJ 00 o NO On -nT CM Ti CM \r\ in irv cm >f Tv ir\CN>i>foO OOCJnc, cpl>N0-Nt in n 0> NO* t" £> CnT <£ -Nt" j-3cMCMc>-i-im t>>TVNO>tir\NONO>* m m c\i fN Oi t> t> no H in CM O 00 O rH t> O ■># -t CMO o> n \f rl to Nr H tO to O OpOOiHNOOOr-tlTl ntONHniOtNHNO CMCMCMnOi-ICICInO t> o m in N n On t> . •vf C\ NO t> 00 ON to Oi >0 H it > 5 cn o m to ci Nt in h n V in\0N0iH>fCMCMC\ O rH m co mtONtWNtm^<\ t 13 CO +> Tt •O -D C 0) 3 ■ to to co -p -p to CO O H •H £ s § c a co CO rl E II II >> so p ho co bo U rH «H •P CO CO rH CO rH H-> CO ~i rH J) o cp e • 0) • rl • CO CO c CO a) «{ O ^ e I ■p co CO CO CO -P t. i) ^5 3 6 3 £ < < CJ O co o o o to co co to U E c co co co a CO CO CO -rl C C C O •rl -rl -H -H tin bO M W Srfll CO -p £ 2 CO rH +J hj co co • to 5 C CO o O ■ X O ft 41 ft. CO CO E- U P CM C rH CO O 60 CO E u a a ) - o 1 Jtf rH i o H n 2: CO CO ^ T3 CO CO c 03 rH ■ CO t> lifi -H CO > -H P -rl CU ft n K 1) O P U CO X U 01 CO TO ti -cm CO C £ rl O* its n 0, C CO -rl CO CO .C -P z: to co DATA ON WAGE TRENDS BY OCCUPATION W Si CU -p Si c ID ,*H CO P ■ 01 -p i-3 ^ t> NO CO CO ->t m cm on O O m r-i omo ^ o><> to n c»n m c*i m«ow\Oo>Hi^too>«\ n w n nto riO0>«) CM vD CM CO t> nD O m n n On On CJ\ lf\(MN«vt(MCOOn CMNOCMmCMO^TrH >£ H to CM co tn -vt o cm HHC«>tO>>0tO nO nO nO * (H >t l> \o n O i-( NT CO r-H cn. cm - t> o t> in co on moo comONCNCo-Ntmc-C-rH " t> On -st •c CM^tcnt>OC--C0C0 (O C« 5> Ml to !C C o o o o o c o o o o c o o o c HrlHHH ooooooo ooo oooooooooo oooooooo o c o o o o o ooooooo r4HHHHrld oocooococc oocococcoo rirlrlriririrlrirld a = 3 c o ■a Q 3 - no o m o no CI NO rH O NO ON CO rH On m m o m on iH r\ o •iNtONOOimNf r> c^ co on o cm no cm m CO nO CM CO CO i-l ^roooNOr^Or-i^vr OOONincoONONO-Ntco mooNinONOcMONONO C^-Ntr-lCMCMNOCMrH oooono^-cmcm l^HOvOtMNtWlTl m nO nO nO nO t> O OC0C0 NOOCOOONONOmmNO OCOONO-tfOOm ON m rH -Nt O n't cm o n lO \0 -Nt H nO On C-\ CO CO CO CM O rH rH m o on m m on mClr-l'tOCMinCONOO nO CM nD "vt" O Q CM rH CM CM vOno-NtHNitMHinn OrHNOOCOCOmr^l rHCM->tONC0ONt>m CMCOOlArHONONin ^tinmm-NtNONO no c- no inNOcONONOininin^tin N0N0ininc\inin-Nt cm O m rH co -n* r\ On On O h Nf cm n (nj m CO ^ On nO O rH in NO CM rH rH m CM O -Nt O CN no cm m O no in On m CM ONrHCNONrHOOrHONCO ONCMCMOCMO^tmOrH OtvONtnwNnriO eo^t-*mcMOONCo H CJi nO CO CM CO CM rH rHNOC-mrHONrHO 8* Pi ■J ^ in ~t n in in in no >o ininoinin^t^j-Ntcn-j- nmNt-lw-tmi'i On r\ CM rH CM ON rH ON O CN t*i c\j cj> n n •t6(M to H to n h to n m no cm Hmin r-i r-i CD NOrlOOiOtOCMnNtH OOOCMCOCOCncnONON H>rr>cMCMNCoc^o>t omocjNNOOcoNO •Jmoi>-NtHtotg Nor\NOrHOt>cosr w n n n cnj n ^ vtmm ■Nt-tinNfNtnjnnHN n^ u • > u • 0) o & rl CO • p S3 X h B p ■a o § — CO i r • as co co -P cu *i • at 34 1 -J f- 1 > a M CO a> CO p. > as Oj c -P CO • 0) a) % 1 ra o P C nu ■ CO cu co d rH CU — 1 s CO a) H 11 t) R 01 CO Eh 2 M 05 CO CO cu ra C • co ^ al C ^ O -h 4) -p O -P -P "H -h C 4) C CO h CU C C O -P E n A a o H S3 U B 4) h a) ctf o rH O o o o M fc. _ o O O O P. *-i O .G -P p CO K W CO W E-i 242 APPENDIX C — c x f ) < — 1 w vr\ Q IVE to Z y u — < a. - cc 8 In - _ H G < — — - CO >- A < uT - U DC u dc — < DC CO Q < 1—1 Z < z < tO — z - — > H SO Q - u z w — DC Z - - 3 AT HE H c\ \r\ Z Cs •—i to DC Z Bi u cc u z >- M CC >< < < < - CO < co Z dc < — AG < S3 -J < 1 s U — a s c u p 8. in c o -Q I CO H x <« bo ih rH x •o -p •H -H T3 c x o -p o <« 41 *h p. 3 c\r>Nru-\ot!o>J:oc-^r ooc~-^oa^ocn>t to en o m oo o nt trvClcrvClClCnCMC^ CMvOvOOClCMOOi rHt>i-ior^coO<> v£> o ci cm r> O vo >J ^ n n CM CM CM CM CM CM CM OC-rHmcnofMcMOCN MO>tOH\»0>'I) -tf O >f >* CO E> o a> o o o o CM H H H W (\ CM -vJO^mt>c\ir>i-ioONr OOmOC-iTiCM^t ^rminc^civoo**) O to O m t> c\ o rH^-l-vrfncnOC^HOCNJ voocnCT>o.f\vDt> cm r> to o >r o >r >tr>OM3\0C0Ot0 t> O O O CO O to oooooooooo oooooooo ooooooo 8888888888 88888888 8888888 CT-ooooojtooor-cNjNj- (Mo cv n o 0> >t O ■a n H to Nt h n r^r^\Dr~\cotc^O O ■* N i"i ^ ^ in wscor-\^fOrHcoc-i ct> o o o O <-h IA>f>f"A>f t £\OvO >» >f IA KMC lO >fl CO^O^fNOtOCMIfN OC--vCCMrHvft>0pCM 0*OOOCMr>CM^coo oj n o _ £• P r 1 St fi c> i-h O r> S r> Q >tO>vOCMvOCMO>-3 lf\ (J\ so O V CM ONfin >I r n \* n ia ^ m r\ >f >t u> ir\ m m CMto-sfOCT-Oc, 0"^ o m oc %r %f ITl rH \£> M3 iH O n h rv n \0 ic\ h» nnnnfiA>J n n ^ s| \f ^ iric^>rcycj^vON£>cor>>* ~ to ^ r> t> n rH r\ >t CO >f t> CO ITl Q so to >f I g ^ C 1 O O n (OCVCMHM^JOn o n to CM H 1A CM r-i n vO to o rl(MCMCMHn>fn CM CM c\i n n n n E IV □ a o c a v B E - p Cl .2 « ■ o r! c ■p x 4> O P •P c 0) -rt O -H € ? e +> 0) to -■ri > 2? -a o c 01 o ^2 - d >» o 03 O i t> -t-> ■H C C ■-I T3 ■H rH C i. tO 5 a E S x to ^ -P O 3 3 •o •O O 01 ~ U Q. •a C *c ■H 01 T3 1 i-t -P • ■H O to 6 3 -P -I p. p £2 01 CJ • u CO XI p 03 o c» 3 , •a fi O 0i H ra P. -p fH O i-l rH vl H T3 oj g a • h • -p • o • 3 • -a O • O •§ g) fe. "a c o •a -h o o ^ Ptj 5 C •o to 1 s | 41 p iH X> O O e 3 ^ g -a -p rH 01 - — ■OP p 2 -a o 3 u c 3 01 aj -a •s P. o 01 g to h u P.i-1 p > a) p -a co O fn O 0) 6u P O p -H U 12 1 C 01 P -3 h < t U -H 01 01 E P P 01 XI x: 3 ex. o cx S - -a to o 006 01 -a to O to •> U a tO P,rH 01 em -H ^ h 01 -a n p x: c 01 to -p d -H 3 to U •o 01 ^ p CH >><-'■ •H to 3 oS rH T3 ^ O C « h -3 01 41 H 5 x; 3 -n ■p p c to Q CO O P O 01 +> 4) P E cu "■S 01 > iH O ti •n O X P 4, I (h • O o P X -I tO 01 5R CJ *j 0) > t-i b 9 x; o c o -p to a o u X. X. £- 0-JtOO>THCMH • ••••••• o\tocnor>t>r>cM ^l-CMCicMcrirric^cri ^tU-lCTlC-.CMCriOOmvO >ACMir\CMir\vDir»>tMDvO CMCMCMCMCMCMCMCMCMCM CMmCM>ACMC>crioOcr\CM CMOt>rHCMr>C>l>vO>t CMiOOvOOCMH^V>» OCM»DOiA-tA\Onin oooooooooo oooooooooo HU\0>jri(MMCMtO>J eoo^cMtooo-^c^oc^ iHm^fin-vfClcrvcnPlr-l ^OlMMnnpS'OiM HHnrMniXJ^^cMO tOHrifflOMCOOHO inn^fncMCMncMi-i CM rH O* O rH m O CM 1*1 H H H H to r- c 41 o * -H (- P o 3 3 a} o to C r. g 8 •p 01 II p o p 01 to H 5 to 01 [-1 • 41 c h T5 p 0] 1 i O X T3 > c •s ■ g: 01 c p 01 to « e * > 01 u •h u ed f. -H 3 O. h O t« -p ■H O r-. -h 01 p x 3 CO 41 ~Xi C 41 . e to 41 u O 41 •H X rH ^ O CD a. cc to a) k > O "rl «» H r •H P fH 9 CO (h o ii 01 8 OTJ 41 P c o 01 « t- -P • 41 U to J &5i x S - 41 u •» C O CO 41 41 » P (-. o E to a 41 -H t, > 03 O 41 -H tj X O rH CO 41 DATA ON WAGE TRENDS BY OCCUPATION 243 V s CCj c V u •- SL C o £ 03 .C -P tin CM H CMNtvOCMCMONCMO O rH to in NO Nt NO in IO Cm o in On ■P .C OJ CM CM CMCMCMCMCMCMCMCM CM CM CM CM CM CM CM £h -P CU E S3 o i •H 0) -p CT> CM NO Cm nO nO rH On r— 1 nO CO O On m rH CM CM cm ON t> C- On NO •H -P Nt [> CM Ir - ^ ' ir\ ir\ ^+ vO l(N n W t MA ^ M 1 rH CM nO a H rH rH I — 1 I — 1 i — 1 i — 1 rH rH H rH rH ,s •H M CU -H •P CO * ft t — i i n \i v l Vi^ uj 1 J \U rH ON [> to to 0) o nO Nt ■sX ^iJ NT 111 nU viJ CO NCJ Nf t> cm m cm M CO ,G 6 *H O o O oooooooo O O O O o o o o o n > l_/ U t_J v_J d d odd o O t~\ r~\ i — i t~\ /~i 8 8 o c o o o cd rH rH t— | f— | H H r | H r | ■ — | rH rH rH i — i rH rH rH C""l vO t> c"\ O Cm m to to c~ m O nO Nt Nl" rH O CM tO rH tD to m t> OOHC^vDOOJH VO O NO to CM On Nt xi ■p no C*"l 0™^ U*\ U"*\ U~\ Nt Nt m Nt Nt 8 45 Cm 00 m vOst-vOvOlArHOvO !> O to CM m m on -P to On O CM(COO>n»00»H ON to !> On rH ON ON 4h ai r-l CM rH OtOtOflOrHtncn t> CM CM c | o to to •H H fN, m CM riCMCMStsfst- c^icr>sftocMir\st O CM CM in nO On Nt rH ■a g CM Nt r-T CM cm" CM CM rH M o Cr> pe p. co r\ vO vO CM C~- CM m Nt CN. H O CM vOmoomoenrH rH to N? [> o to o On vO nO C^lStOrHStrHmCM IT\ ON rH Nt CM to nO -p 69- 0) ID CM rHrHrHCMCMCMCMCM CM rH rH CM H rH >-5 w • • -P • CO O • 73 ' O o q -a h -h o p.-p f-i c p. w -H -P a> M o -a CU CU CO E cu * cu -p c -P w cu co E'-- r-lTJ CO • o p; -p o CO cu w CO -p •P o •• CJ -3 to -j t3 (!) TJ O •rl O U rlH O ft* 3 O T3 - o o id « ft •a (0 0J 9 a cu CU r( E O H Xi CU CO CU x; 3 T) H T3 CU -H C r-P •H 13 X C CU tlO'H +5 C Ai •H - rl T3 cu co h rl CO E CO cu -p p cd ^ CJ 0) rH S 3 H &0 3t o rH o ^ -a CO rl-P fi » •a ft cu co -h C ft r. CO r< ■ •>+> > co - ft co p s cu a) CO rH "a rl ftrH - I % : cu • e • ft cu •H rH 3 O CT -rl * ■§ rH o U •H O -P CU Q fn • O O H-> X g CU *£ co cu cu E rH ft > rl - 0> o CO •H > rl 0) cd co +^ •rl CO ■o CO a) § cu O CO i rl cu H 08 ■a •H CO a- CO CO rl ^ 0) -P >i •H CO -P rH o •H •H rH X rH cc) •H Oj •H a) P rl r< -a o 08 3 a o a « o o s a> rC H>> a o c3 13 rfl a =3 O CC 244 APPENDIX G jy — £ — - < X ^ z ON - Ml Z m - * 2 O U ^ 2 >* o >- < Cs p< -J — ' ji/l 2 < O Z g oc < h id O D < H u u. 3 -p 4) -p bfl *h •H V. o> 8 is p co j3 8 1 w vO in >* O t> O vOvO^l-O^OHO C- en cm r\ vOCMC^^t-J-OOCO OOCOOOQiri>l-ir> O O O m C- c\rr,cM>*ir\00CM>t OOCOrHOOr-IO i-ICMrHCMCMCMCMCM O CM 00 O rH H O O C> «1 \* > O co r- co c\ co o 0> C C> (0 (MD SI o> o ; CT> CO cir-i>rc\i>rc\iovc vcr^vOfio^H cvi>*coc>>rooi- om -n >t vO vO^mcivoiriiriin c~- m i i i i i i i i i i i ■ i i i i OCM>fv«rimcoC*-r-l HHNOmH COvO>£0>CMCMOCO (M> H H Oi-lrHinO^O^O O CM • • n o • ••••••• oooooo oooooooo 888888 88888888 |H rH rH rH r-t r-l l-l oo OOOOOOOO 88 88888888 en >r >t cr> en oo t^>rvn(MOOooc~- O r\ O *3 CO O H N H S O O O »r» O CO 00 CM »£> cTr-Tf-T r-- oo r> cm* C"-* lf\ rH cocncMCMO-tfcoS co >f irvr^imc^r-rgOC- t> CO CM f) 00 >f CO %f op r\ \C 8c"> o oo cm KMC! t» -># <"\ CM o co l> C- 00 >f CO o 38 irv vo in o> t> ft CM C"- •J C tv n r> c> mi oo F> H i > v£) >f ) v to *o n o mo m m ^ tc * O 1 n ^) h _ O H *C ■ H r( OS) >0 >0 >© ft ITl C>-000>t'OT\TlTl 33££££c38 OO^DmOO^OOiAfH rHVO f oo>onno>n m H * ffl 6 " fiHrif nOton r> m vo o >I r> (oo«ooohm^ in o « n in >t n •* CM vf m cm 00 vO OOrHir\cn<"10f*l 05 41 U r. 01 B HHO-< CM t r> C~- C- >t cm cn co n vO ff> vO inif\ niO(VH • ••••• oooooo 8 8 8 8 8 8 »£> c~- >r\ ■# <£> cm <£> cm ^ t> cn - CM O t> v£> vO >f\ vO IA CI 1T\ ITi rH 0> Nt O H Q ^ ^ CM C> -3 C^- Q H H H >fl H vD ITl m 1T> CM >J Pi CM ITv C-l CO • X CO ^ p a g o cm •H P o • tH r. co X! 41 CO 41 0) E e E E 41 P. O 60- CJ M Q *H CO O CO h 03 +> to I co co a: r. T3 CO 41 C 01 r-l a 41 a 41 tH CO > n P -n p. P. OJ >> 41 O -P o cu X u - 41 CO T3 (-c - C 41 2 ffl £ 50 CT r. C-H be . — : to P. c CO -rH 41 4i Si -P s: co w DATA ON WAGE TRENDS BY OCCUPATION 245 V "a c g 8. e o ■D - CQ C - o z 1 >- < CN o* -j «-< < < .. < n 2 Pi < H Bi U 3 < H (J J Oc/5 - - •H Cn — 5, r. p g ^ s: o -p 4) -H - rl 8 n c~- r-i r- cm c- cn cc CO c\ n m CM CM c^ 8 n M n r\ tH m c-i co o • • • • • CT* rH t> m C- o m cc f- cn cm t> i-i rH m oiN'OHO?00'r((Mto cn o cn cm o cn m cm n o m n oioionssc vo \o o vo m \o \o t>- CM C~- m vc \0 OMn>f oi^oinot>r-OT>\OvOvoir\vo C CC O vC O CM >t CI C- rH m -j- rH o m o Cn C- m CM CM r-H O CO CO C rH CM Cccr-nocomir. mor- cncMCncncMCnOCMC>CnO O O C O O in n mi *o d to to Q H (J* Qitt) v s C cn i> cn cn o cn n cm m C- CO ^.t CO CC cn CO ^ O CC t> O CM O cn CC rHCnCM r^CMrHrHm^roa-rHf-o comifiiHnincM'^n^tn OHtMO^nrMnn^'fo O O i-H cn Cn O O CM O rH rH O CO CM cn cn C m cn o co m \o c- t> o o o cococo of-cnr>r-r>NOvO\ooc-- co r> r> >r c- o- m m 0> CM CO rH cn cn cn cn in in cm cm H CM H iO "vf t- comco mcMcoc^NC mnto HOOtoc CO O O CO >fr cn Cn cn !n 5 >r cm >3 co ^ cn in -5 in co m m \0 o m no o OO moccvO\OommmvO\0 \0 \0 m n \0 \D CO CM C> rH O t» CM v CM H H ^1 r. r-H m CM O m CO C CM o c ■« O m rH OHincoc-OOHocom OvO«omOniOOi(MiO(D OvOC^rHvOrHNCCNmrHm nI o> o> C O 1C \* eg o cn ^ cm ^* m m m -tf m m m \0 vo mmr>vomm^r^r>rmm cn -C cm co --t no cm m m m cm m m fflrivonm Ooiono to cm in pi \0 r- cc -f -sf m cn O f> co m vo c~- \c m h 5 o "^t n cji CM cn CM O cn CO m cn rH t>cMrHO>>J--*m\omNr>t mr>CMcncor>\DOcnr>->i' rH cm m vO cn \0 CM co m -sr ci o co Pi t> -n? cm o cn co m m >r >f cn >r >tinin ^-iOm'jnn%fnn^ ■^•-^•^rH^^-cn to o rl • CO 41 c r. >; ^ 41 o Ait U K r. 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T3 rH O O cd O P -P 1 : B a ■a u n — HJ -p 5 - u C Q CO +> rH t § - - a) 2 a : rH ■- — •H rH bO u c 3 P. & tH o" rH ■O CU •a c Ch rH _ T3 cc ci c rH C ■o - o — S -H c >> E -P — tf a) AS rH >> -P O rH rH •a 9 O g - P. a ■H •- D u •a & s z H-> rH o M rH Bh •P T3 T3 rH ad 2 < 268 APPENDIX D OS rCi G\ «— 1 Q z <: p, c\ CS OS ui H < H AND decrea >< « a£ H o c * sign CQ cd o» ^1 rH CD *A C 0> ^ rH P.-H o o 3 0* •o 5 CO O'-*'— ■ rH rH Z Z rHrHrHZZrH^-'ZZZ W in to r~ »»-~ >o H ^ — - 1-HrHrHZZrHrHrHZZ C-- CM O CM cm cm t> o H N H H CM t>- o * r-^r-xCO t> rH r-( rH Z Z rH » — Z rH i-H •vt \D tXI N m m \C to m i vO \0 vO 0> O Nf 03 CO OOrHmCMrHr^^fOrH r^ococo^c^cnvovo-vt CO CM 0^ O O t> r-l -tf vO vO t> vO CO -tf O CM C- IT, CO CO u"\ - ■ >J-C0CMCOt-CMC0>}--J-t> •vt r> CM rHvOOvOinmirir-OO OlAlA^tU^NtC^Nt-vOO r r \c r \c r ir r \r r \r r \c r yr r \r r \f*^ rH rH f- O rH C\i v3 !a vO ^3 vO IT\ 0>^OOIO» » CM vO CM CM CM ir\ O CV — '^0 vO to r^mvOvOiAvO w cn c~i[-~>nrHC'-Q<-H*£>0>r'> COCMCMrHOIvOvOOvCOC-- t> rH r-^-N <^ < << rH Z Z HM> r^l CM ^OrHrHZZOCOZZZ 0><^CMZZCSjr\CMZ vo co HO>HtO Ci CM fr\ CM ■J O CMcnvOOH ^fNOOOCMrH*— ••sJ-.^CM rH CM CM CM CM CM n CM W c'lCOOmCMCMCOmC^ »MioOrino" nooooooo CMtnCMCMCMmrr\CMrriCM I? rH 1T1 CJ> 0> rH CO O f- O (MO N m -J nT ~/ «r> 1T\ {> CO c\ o B *■» O CM \D ■^rHQt-rHO-OacMCOfn CM ^ «-\ ir\ vf CM vO nI CM rH rH CO CO O CO CO t> <^ <*\ < < •*toozz CM O <•> O < rH C~- z co m Q >f O * — ■• — * o *o c~ o o -Ort«0«<«N'On r-OOZZOrHOOCO p 3 go cm iTi t> -J to q to o o o tTl CJ> »D w f> rH t> CM CM CM CM rH CM CM CM rH rH OCMCOvOvOO^irirHOf^ (""VC^^SOrH^tOCMCOCM rHCMCMCMCMCMCMCMCMCM CO O rH CO n r\ N ^ NO(OHHH ■vTo rH SH H O ^ n( H CO oho> it\ \0 c> c? >r> vO CM CM CO -5 CM O cM>t->»->rvf-Nr>r-st-^rH '3 > 09 O z «< z •2 -2 ^ o APPENDIX E STATISTICAL TABLES SHOWING LIFE- TIME EARNINGS BY EDUCATION, COLOR, AND REGION, FOR SELECTED OCCUPATIONS See chapter VI for a general description of the procedures used to estimate lifetime earnings. In preparing the tables that follow, the mean earnings used for each age group are those shown in U.S. Census of Population: I960, Vol. II, Occupation by Earnings and Education. The life tables used are shown below. Lifetime earnings were not estimated where there were three or more age groups with fewer than 1 ,000 workers. Table E-l. — Estimated Number of Man-Years Lived at Each Age by Sur- vivors of 100,000 Male Infants Born Alive: 1959 and 1949 1959 1949 Age group Total White Nonwhite Total White Nonwhite 95,716 96,134 93,297 95,001 95,387 92,431 Man-years in each age group: 191,150 191,996 186,242 189,702 190,496 184,387 190,538 191,408 185,467 189,046 189,896 183,291 28-4,538 285,913 276,487 282,209 283,624 272,456 470,947 473,560 455,110 466,652 469,470 446,652 466,595 469,803 446,108 461,671 465,187 435,896 913,545 922,298 852,380 900,657 910,369 826,606 857,620 870,435 763,353 838,679 853,133 725,547 732,320 749,677 606,476 708,814 727,798 554,105 511,550 529,322 370,316 496,798 514,232 351,286 297,478 306,906 225,411 287,742 296,037 224,990 Source: Data for 1959 derived from Vital Statistics nf the United States, 1959, section 5. Data for 1949 from "United States Life Tables, 1949-51," Vital Statistics— Special Reports, Vol. 41, No. 1, 1954. 269 270 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Less 4 years or more Total 8 1 to 3 4 than 1 to 3 8 years years years years Total 4 5 years years years or more Total experienced civilian labor force UNITED STATES Total C.tC? 184 212 247 293 JO J 4SS 191 221 253 301 "3QS 122 95 123 132 151 162 215 185 246 Ratio of nonwhite to white.... 51 61 64 60 60 54 50 47 53 THE NORTH AND WEST 107 194 223 252 298 X f J 198 229 257 305 ** f\j 154 135 144 152 168 179 239 209 269 Ratio of nonwhite to white.... 61 77 73 66 65 59 55 52 57 THE SOUTH J.J.O 156 184 230 280 j j j 4T7 ± j j 167 197 240 291 4SS 91 77 96 102 115 127 182 154 213 Ratio of nonwhite to white.... 43 58 57 52 48 44 45 42 47 Professional, technical, and kindrec workers UNITED STATES Total 355 199 227 262 288 300 418 349 469 363 208 233 268 292 305 428 357 481 206 111 150 188 179 238 192 264 Ratio of nonwhite to white.... 57 53 56 64 59 56 54 55 THE NORTH AND WEST Total 361 225 239 271 293 306 424 359 472 367 234 243 276 297 310 431 364 481 236 171 211 208 275 225 298 Ratio of nonwhite to white.... 64 62 71 67 64 62 62 THE SOUTH Total 335 159 189 239 268 280 401 320 467 White 348 173 200 248 275 289 419 334 491 167 135 131 198 162 224 Ratio of nonwhite to white.... 48 49 45 47 49 46 Accountants and auditors UNITED STATES Total 313 272 286 292 362 361 369 White 316 274 289 295 366 365 374 THE NORTH AND WEST Total 317 277 287 293 368 364 383 320 280 290 296 373 368 388 THE SOUTH Total 300 284 288 330 338 319 White 303 286 292 335 341 327 Artists and art teachers UNITED STATES 302 300 320 300 299 304 297 307 308 326 305 304 311 302 THE NORTH AND WEST 307 306 321 310 301 310 290 312 310 327 315 306 317 294 THE SOUTH 262 White 267 — Represents zero. DATA ON LIFETIME EARNINGS 271 Table E-2. — Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary- High school College Area and color Total Less 1 to 3 4- years or more than 8 4 1 to 3 8 years years years years Total 4 5 years years years or more Clergymen UNITED STATES Total 175 133 151 156 168 184 180 180 163 167 174 186 185 186 122 Ratio of nonwhite to white.... 68 TKV NORTH AW) UF9T 1 IXC ll^CvXn rUYU NLJ1 174 168 166 179 179 178 177 170 181 181 179 Nonwhite 135 Ratio of nonwhite to white.... 76 inc. ouuin Total 174 142 167 196 181 201 185 178 200 189 204 Nonwhite 114 Ratio of nonwhite to white.... 62 College presidents and deans UNITED STATES Total 367 379 380 College professors and instructors UNITED STATES 324 328 269 335 329 333 275 340 248 252 Ratio of nonwhite to white.... 75 76 THE NORTH AND WEST 334 338 279 345 337 341 282 348 THE SOUTH 295 300 307 304 310 317 Dentists UNITED STATES Total 589 594 597 UVt-i + a 600 606 610 THE NCRTH AND WEST 587 596 598 598 608 610 THE SOUTH 629 624 652 636 631 663 Designers and draftsmen TTWTTPT) ^TATTT^ UM±±XAJ OLAXLO 288 273 289 290 308 306 315 White 291 276 292 294 312 311 319 THE NORTH AND WEST Total 293 277 296 298 312 310 317 296 280 299 301 316 314 321 THE SOUTH 264 269 253 268 271 255 — Represents zero. 272 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary- High school College Area and color Less Total 4 years or more than 8 1 to 3 4 1 to 3 8 years years years years Total 4 5 years years years or more Editors and reporters UNITED STATES Total 358 327 333 357 365 357 363 332 337 362 370 364 THE NORTH AND WEST 343 341 327 386 380 333 348 345 330 392 386 339 THE SOUTH Ts-rt o 1 341 339 346 342 Technical engineers Trrfnl 363 239 271 307 323 339 404 397 417 367 247 274 311 326 342 408 401 422 THE NCRTH AND WEST 369 263 281 315 332 346 407 401 420 373 284 318 335 349 412 405 425 THE SOOTH 341 283 297 313 390 383 408 344 287 300 316 394 386 412 Aeronautical engineers UNITED STATES 395 378 374 418 422 White 399 381 377 423 426 THE NCRTH AND WEST 395 389 377 416 418 399 392 380 421 422 Civil engineers UNITED STATES 335 270 285 310 380 377 387 339 274 288 313 384 381 391 THE NCRTH AND WEST 347 290 298 324 384 381 391 351 295 301 326 389 385 396 THE SOUTH 308 264 288 370 368 382 312 266 291 374 371 387 Electrical engineers UNITED STATES 372 318 327 345 406 400 418 375 322 330 348 410 404 422 THE NORTH AND WEST 379 328 331 354 411 403 424 383 331 335 357 415 408 429 THE SOUTH 343 310 310 387 389 346 314 313 391 393 — Represents zero. DATA ON LIFETIME EARNINGS 273 Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary- High school College Area and color Total Less 4 years or more than 8 1 to 3 4 1 to 3 8 years years years years Total 4 5 years years years or more Mechanical engineers UNITED STATES 360 316 339 350 399 390 425 364 319 342 354 403 394 432 THE NORTH AND WEST 365 319 344 355 404 394 433 369 322 346 359 408 397 440 THE SOUTH 336 378 373 340 381 376 Sales engineers UNITED STATES 398 371 369 429 438 402 374 372 433 442 THE NORTH AND WEST Total 402 379 375 434 441 405 383 378 438 446 THE SOUTH 382 385 Lawyers and judges UNITED STATES Total 621 642 537 680 631 652 546 691 THE NORTH AND WEST 624 644 536 687 634 653 545 697 THE SOUTH Total 619 642 516 661 632 655 524 676 Musicians and music teachers UIMJ.liVL' o1A1£jO 237 217 235 255 260 254 267 White 243 229 246 257 265 262 270 162 Ratio of nonwhite to white.... 67 lfir, NUKln AND W£,ST Total 248 222 243 267 272 272 276 252 235 251 267 276 277 280 THE SOUTH 200 222 210 226 Natural scientists UNITED STATES Total 343 272 307 369 343 388 White 348 276 311 374 347 393 THE NORTH AND WEST 339 269 306 364 333 387 344 273 310 369 337 393 — Represents zero. 274 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less years or more 8 4 than 1 to 3 1 to 3 8 years years years years Total 4 5 years years years or more Natural scientists- -Con. THE SOUTH 354 383 369 390 360 389 374 396 Agricultural scientists UNITED STATES 256 261 Biological scientists Total 310 322 White . . 317 330 Chemists UNITED STATES 327 274 300 351 328 371 White 331 277 304 355 332 376 Irir. Nun In AHL w&oj. 326 274 305 349 328 368 White 331 277 309 353 332 373 Ttre o/ ii ri'ti 1 rit. SUUin Total 329 355 334 359 Geologists and geophysicists UNITED STATES 446 470 501 White 451 474 506 THE NORTH AND WEST Total 421 425 THE SOUTH 470 474 Physicists UNITED STATES Total 415 431 421 437 Physicians and surgeons UNITED STATES 717 721 730 727 White 736 740 774 745 377 379 394 Ratio of nan white to white.... 51 51 53 THE NORTH AND WEST 8*7 851 690 861 873 876 732 886 THE SOUTH 727 733 739 748 ^55 760 — Represents zero. DATA ON LIFETIME EARNINGS 275 Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less than 8 years 8 1 to 3 years 4 years 1 to 3 years 4 years or more years Total 4 years 5 years or more Social scientists UNITED STATES 362 367 319 322 317 321 389 396 410 415 386 394 THE NORTH AND WEST 366 371 404 411 450 456 394 403 THE SOUTH 351 358 361 366 376 381 Economists UNITED STATES 413 417 432 437 427 433 THE NORTH AND WEST Total 424 428 461 465 lnr. oUUln Total . 384 389 Psychologists UNITED STATES Total 335 342 345 352 Statisticians and actuaries UNITED STATES Total 335 340 387 395 THE NORTH AND WEST Total 335 339 400 410 Teachers UNITED STATES Total Ratio of nonwhite to white.... 250 256 183 71 219 224 213 220 257 263 189 72 222 230 164 71 274 279 213 76 THE NORTH AND WEST Total White Ratio of nonwhite to white .... 265 268 216 81 227 229 226 230 272 275 222 81 241 244 285 289 240 83 THE SOUTH Total White Ratio of nonwhite to white .... 211 219 170 78 176 183 217 225 175 78 189 199 156 78 234 240 195 81 — Represents zero. 276 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Sblbcted Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less than 8 years 8 years 1 to 3 years 4 years 1 to 3 4 years or more Total 4 years 5 years or more Elementary school UNITED STATES 232 181 241 208 262 239 184 259 216 268 178 182 159 206 Ratio of nonwhite to white .... 74 73 74 77 THE NORTH AND WEST 248 195 256 226 272 251 197 260 230 276 THE SOUTH Total 193 202 177 224 202 211 185 231 162 167 Ratio oi nonwnite to wnite.... 80 79 Secondary school teachers UNITED STATES 261 228 265 227 281 267 236 270 234 285 193 197 220 Ratio of nonwhite to white .... 72 73 _ 77 THE NORTH AND WEST 276 248 279 243 292 278 250 282 246 294 THE SOUTH 220 224 195 242 228 232 204 248 180 184 202 Ratio of nonwhite to white.... 79 79 81 Technicians (n .e.c. ) UNITED STATES 251 210 221 243 251 254 294 283 319 255 219 226 247 254 259 301 289 326 183 Ratio of nonwhite to white.... 72 tw unnru AMP UT^T UU NUAln AJtU Wto 1 Total 254 227 246 253 257 296 281 316 257 231 250 257 261 302 287 322 196 Ratio of nonwhite to white.... 76 THE SOUTH 239 226 238 247 298 245 232 241 253 307 Medical and dental technicians UNITED STATES 224 234 222 221 249 230 239 228 227 254 THE NORTH AND WEST 227 231 226 228 232 237 232 233 THE SOUTH 214 221 — Represents zero. DATA ON LIFETIME EARNINGS 277 Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Less Total <+ years or more 8 than 1 to 3 4 1 to 3 a o years years years years Total j H 5 years years years or more Electrical and electronic technicians UNITED STATES 268 263 270 263 271 265 272 267 - TKF NORTH AND VEST j. iLLi il \Ji\ ±1.1 All Is n 1* ' J. 270 266 270 266 273 267 273 270 - THF SOUTH 259 265 199 262 267 - Other engineering and physical science technicians UNITED STATES 259 227 241 251 270 326 301 - 263 230 245 254 273 331 306 - THE NORTH AND WEST 261 234 247 254 267 327 — 264 238 250 257 270 332 THE SOUTH 218 242 276 White 245 281 - All other professional , technical, and kindred workers UNITED STATES Total 307 172 216 253 285 304 350 342 357 314 184 223 259 290 310 357 349 365 187 197 220 235 Ratio of nonwhite to white .... 60 68 62 64 THE NORTH AND WEST Total 315 201 229 262 290 307 357 350 364 White 321 213 235 268 294 313 364 356 370 206 236 Ratio of nonwhite to white 64 65 THE SOUTH Total 285 145 184 234 262 294 332 320 349 White 294 155 192 242 268 303 342 330 359 152 Ratio of nonwhite to white 52 Farmers and farm managers UNITED STATES Total 140 84 126 147 168 213 267 271 269 White 147 97 129 151 169 215 272 276 252 59 42 70 93 147 Ratio of nonwhite to white .... 40 43 54 62 87 THE NORTH AND WEST Total 156 128 136 159 168 200 240 243 240 White 157 130 137 160 169 200 243 246 244 166 Ratio of nonwhite to white.... 106 THE SOUTH Total 114 68 100 130 166 243 344 337 White 129 80 106 138 171 250 353 345 Nonwhite 41 39 45 49 Ratio of nonwhite to white .... 32 49 42 36 — Represents zero. 278 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less than 8 years 8 1 to 3 years 4 1 to 3 years 4 years or more years years Total 4 years 5 years or more Managers, officials, and proprietors, except farm UNITED STATES Total 361 221 267 303 346 414 548 548 550 561 368 231 271 308 350 420 557 556 181 119 166 171 210 211 255 243 Ratio of nonwhlte to white.... 49 52 61 56 60 50 46 44 THE NORTH AND WEST 378 243 282 320 355 423 576 571 591 384 253 287 326 359 429 586 579 604 206 145 186 187 231 231 271 Ratio of nonwhlte to white .... 54 57 65 57 64 54 46 THE SOUTH 321 200 231 265 322 389 484 492 475 White 328 212 236 270 327 395 492 499 484 129 94 Ratio of nonwhlte to white .... 39 44 Buyers and department heads, store Total 336 225 265 294 326 370 433 436 444 White 340 267 297 329 374 437 440 448 i nr. Nun J. n An u wlo i Total 346 283 307 334 378 442 449 446 350 286 311 337 382 447 454 451 l tic ouu x n Total 305 261 308 346 407 White 308 264 311 350 411 Inspectors, public administration 246 187 247 245 258 275 270 White 248 188 249 247 260 278 273 WHQTW AMD UV^T inc. iNunin nnu wloi 252 252 251 263 275 254 255 253 265 278 TUTT QH1 FPU 232 232 White 234 234 Officials and administrators (n.e.c), public administration UNI i£.L OlAiu Total 281 186 238 261 284 347 323 372 White 285 241 263 288 352 327 378 I lit NUKiH AND Wrol 278 243 262 284 332 313 358 281 246 265 288 337 317 365 THE SOUTH 288 229 260 289 367 335 395 White 291 232 262 292 371 339 399 Managers, officials, and proprietors (n.e.c. ) UNITED STATES Total 376 223 272 310 359 437 593 590 604 384 233 276 315 364 443 603 599 617 180 118 172 170 208 214 252 243 Ratio of nonwhite to white.... 47 51 62 54 57 48 42 41 — Represents zero. DATA ON LIFETIME EARNINGS 279 Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less than 8 years 8 years 1 to 3 years 4 years 1 to 3 years 4 years or more Total 4 years 5 years or more Managers , of 1 'icials, and proprietors (n.e.c.) — Con. THE NORTH AND WEST 395 247 289 329 368 446 621 616 635 401 255 294 335 373 453 632 625 650 212 155 201 190 231 237 275 Ratio of nonvhite to white .... 53 61 68 57 62 52 44 THE SOUTH 331 £ . . 268 334 413 523 526 524 339 213 236 274 340 420 532 534 534 124 90 Ratio of nonvhite to white.... 37 42 Other managers officials, and proprietors, except farm UNITED STATES Ti-i+.n1 283 214 246 275 287 301 334 332 370 White 288 227 254 280 291 305 338 335 379 152 Ratio of nonwhite to white.... 53 THE NORTH AND WEST 287 195 239 280 292 305 336 333 352 293 210 249 286 296 309 340 337 358 143 Ratio of nonwhite to white .... 49 THE SOUTH Total 271 213 252 263 274 291 335 332 White 275 218 255 265 278 294 338 336 Clerical and kindred workers UNITED STATES 213 169 190 203 218 225 262 258 270 218 176 194 208 222 229 268 264 276 Unnuhi 162 129 145 158 172 176 186 182 Rati n rtf n onijVi i +^ + o ljVi t +^ lul blU \JL UUtlwilx l/C w L»C .... 74 73 75 76 77 77 69 69 THE NORTH AND WEST 217 180 194 207 222 228 263 261 268 White 221 185 197 211 226 232 269 266 274 170 146 153 164 177 179 189 Ratio of nonwhite to white.... 77 79 78 78 78 77 70 THE SOUTH Total 201 152 175 189 207 218 259 252 277 White 208 161 181 195 211 223 267 260 283 144 113 145 156 164 Ratio of nonwhite to white .... 69 70 74 74 74 3ank tellers UNITED STATES Total 202 206 199 White 204 208 201 THE NORTH AND WEST Total 204 208 White 206 210 THE SOUTH Total 196 White 197 — Represents zero. 280 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less years or more than 8 8 1 to 3 4 1 to 3 years years years years Total 4 5 years years years or more Bookkeepers UNITED STATES 204 194 207 203 213 216 206 197 209 205 215 218 TRTT MHRTH AMT1 UF^T inc> - «Ui\l.. niiU RLul 209 199 213 208 219 223 211 202 215 210 220 224 TWTT Q HT TTT4 Total 193 181 195 192 White 195 183 197 194 Mail carriers UNITED STATES 213 185 197 212 219 217 204 206 216 186 200 214 222 220 192 194 Ratio of nonwhite to white.... 89 87 THE NORTH AND WEST 214 196 213 219 214 216 198 215 222 217 196 Ratio of nonwhite to white.... 91 IrLt OUUln 211 207 219 222 214 211 223 224 187 Ratio of nonwhite to white.... 87 Office machine operators UNITED STATES 228 212 240 224 232 216 244 229 TUP KinDTU AMTl UPCT IrLL NUKln AND wjloI 228 214 247 220 231 218 252 224 1HL i>UUln 217 216 222 218 Postal clerks UNITED STATES 217 210 215 224 215 219 219 221 217 219 228 218 217 220 194 197 195 Ratio of nonwhite to white.... 88 86 89 THE NORTH AND WEST 217 209 214 224 214 219 222 221 216 217 229 216 217 194 197 Ratio of nonwhite to white.... 88 86 THE SOUTH 218 217 223 219 223 222 227 225 — Represents zero. DATA ON LIFETIME EARNINGS 281 Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Eleme ntary High school College Area and color Total Less than 8 years 8 1 to 3 years 4 1 to 3 4 years or more years years years Total 4 years 5 years or more Shipping and receiving clerks UNITED STATES 183 168 182 185 190 182 189 174 186 190 195 186 1A2 133 145 146 Ratio of nonwhite to white.... 75 76 76 • 75 THE NORTH AND WEST 189 177 185 191 194 186 194 182 189 195 199 189 151 154 153 Ratio of nonwhite to white.... 78 79 77 THE SOUTH Total 161 148 162 161 173 168 156 167 168 180 121 Ratio of nonwhite to white.... 72 All other clerical and kindred workers UNITED STATES 217 168 189 205 222 231 272 268 280 222 175 194 209 226 236 278 274 286 152 124 140 149 163 167 176 Ratio of nonwhite to white.... 68 71 72 71 72 71 63 THE NORTH AND WEST Total 221 179 195 209 226 235 273 270 278 225 184 199 214 230 239 278 275 284 161 142 150 154 169 172 Ratio of nonwhite to white.... 72 77 75 72 73 72 THE SOUTH Total 204 150 173 190 209 223 272 265 286 White 211 160 178 196 213 228 280 273 292 133 109 68 138 145 150 Ratio of nonwhite to white.... 63 70 68 66 Sales workers UNITED STATES Total 270 167 206 232 265 306 387 387 392 White 274- 173 209 235 269 310 392 392 397 152 101 147 175 183 Ratio of nonwhite to white.... 55 58 63 65 59 THE NORTH AND WEST Total 282 191 218 244 275 313 395 400 378 White 286 197 221 248 278 317 400 404 384 176 164 189 204 Ratio of nonwhite to white.... 62 66 68 64 THE SOUTH Total 236 142 177 200 238 283 363 345 372 White 240 147 181 203 241 287 369 351 377 106 88 Ratio of nonwhite to white.... 44 60 Insurance agents, brokers, and underwriters UNITED STATES Total 320 220 258 276 298 339 406 411 390 White 326 225 262 280 303 346 414 420 396 181 Ratio of nonwhite to white.... 56 — Represents zero. 282 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Area and color Elementary High school College Total Less than 8 years 8 'l to 3 years 4 1 to 3 4 years or more years years years Total 4 years 5 years or more Insurance agents, brokers, and underwriters — Con . THE NORTH AND WEST Total 336 341 302 305 314 318 343 348 423 430 434 442 400 407 THE SOUTH Total White 285 293 239 244 262 268 333 343 361 371 356 367 Real estate agents and brokers UNITED STATES 359 366 306 310 292 296 337 342 370 377 459 468 468 478 416 419 THE NORTH AND WEST Total White 367 373 303 309 343 345 371 379 485 494 519 528 394 399 THE SOUTH Total. . White 342 348 301 304 378 385 412 423 394 Salesmen and sales clerks (n.e. 8.) UNITED STATES White Ratio of nonwhite to white.... 257 261 143 55 163 169 102 60 201 204 227 230 144 63 258 261 164 63 295 299 166 56 371 375 368 372 362 367 1ML NUnln AND WJ£>1 Total White Nonwhite . Ratio of nonwhite to white.... 270 273 163 60 187 192 213 216 239 243 158 65 266 270 173 64 304 308 375 379 376 380 356 360 THE SOUTH Total White Ratio of nonwhite to white.... 224 228 102 45 140 146 170 174 194 198 232 235 269 272 363 368 340 344 378 382 All other sales workers UNITED STATES White 278 284 117 122 181 189 217 222 265 269 319 319 443 450 453 459 THE NORTH AND WEST Total 296 301 198 205 230 236 276 279 332 332 477 485 478 485 TUT O f"\T !"PL1 Total White 229 237 225 232 268 272 Craftsmen, foremen, and kindred workers UNITED STATES Total Ratio of nonwhite to white.... 223 229 141 62 177 185 118 64 207 211 140 66 225 230 148 64 243 247 166 67 253 258 167 65 323 330 188 57 316 320 346 353 — Represents zero. DATA ON LIFETIME EARNINGS 283 Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed High school College Area and color Total Less s years 8 1 to 3 years 4 1 to 3 years 4 years or more years years Total years 5 years or more raftsmen, foremen and kindred workers--Con. TUT? XTAIDTU A KTT^ l.flTCT lrlfc. NUH1H AND V/Iil 236 202 217 236 249 260 329 322 354 White 240 2-~ ! 220 239 253 264 335 327 360 171 155 163 170 184 189 Ro + in rtt nnrrufri t.p to white 71 75 74 71 73 72 THE SOOTH 188 150 178 195 219 230 306 300 322 197 160 184 202 225 239 315 310 329 106 97 106 114 124 121 Ro + i n nf* nmYwhitp to white 54 61 58 56 55 51 TVri nVmasnns . s1\nnpmflsnns . UNITED STATES 209 170 204 218 233 250 221 187 210 228 243 268 126 107 Ratio of nonwhite to white .... 57 57 THE NORTH AND WEST 229 202 218 233 244 White 235 214 220 237 249 Nonwhite 163 Ratio of nonwhi"te to white .... 69 THE SOUTH 168 136 168 189 200 White 187 155 181 208 221 107 96 Ratio of nonwhite to white .... 57 62 Carpenters DNITED STATES 185 145 178 193 209 207 224 229 White 190 152 182 197 212 211 232 112 91 116 121 147 Ratio of nonwhite to white 59 60 64 61 69 THE NORTH AND WEST 209 187 196 215 220 220 237 White 211 190 199 217 223 222 242 Nonwhite 164 138 Ratio of nonwhite to white .... 78 73 THE SOUTH Total 139 120 139 148 167 163 White 146 127 145 154 172 170 Nonwhite 81 79 84 ItO UXU Wi. liUllWlli. W .... 55 62 55 Cement and concrete finishers UNITED STATES Total 196 163 205 207 237 White 222 194 223 226 126 115 Ratio of nonwhite to white .... 57 59 THE NORTH AND WEST Total 226 213 222 228 236 227 230 238 161 Ratio of nonwhite to white.... 68 — Represents zero. 284 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less than 8 years 1 to 3 years 1 to 3 years 4 years or more years years Total 4 years 5 years or more Cement and concrete finishers — Con. THE SOUTH 138 122 168 110 Ratio of nonwhite to white.... 65 Compositors and typesetters IINTTFD STATES 247 250 205 207 229 233 247 250 254 257 248 251 THE NORTH AND WEST 252 235 254 258 251 256 239 256 261 254 THE SOUTH 224 220 239 229 225 242 Electricians UNITED STATES 251 215 236 251 257 259 \JV\ ^ +£1 254 219 239 254 259 263 189 Ratio of nonwhite to white.... 74 THE NORTH AND WEST 261 239 245 260 266 268 264 241 248 263 269 272 THE SOUTH 223 196 217 228 228 231 226 200 219 231 230 235 Foremen (n.e.c.) UNITED STATES 282 230 259 278 293 313 372 362 406 286 234 262 281 296 316 376 366 411 196 167 196 Ratio of nonwhite to white.... 69 71 70 THE NORTH AND WEST 292 246 269 287 300 318 379 369 418 296 251 272 291 303 322 384 373 423 212 205 Ratio of nonwhite to white.... 72 70 THE SOUTH 252 209 226 249 270 293 349 340 256 214 229 252 273 297 352 343 157 Ratio of nonwhite to white.... 61 Linemen and servicemen, telegraph, telephone, and power UNITED STATES 253 206 228 251 263 272 256 216 231 254 266 275 THE NORTH AND WEST 259 234 233 258 267 272 262 237 236 261 269 275 — Represents zero. DATA ON LIFETIME EARNINGS 285 Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary- High school College Area and color Total Less <+ years or more than 8 8 1 to 3 4 1 to 3 years years years years Total 4 5 years years years or more Linemen and servicemen, telegraph, telephone, and power- -Con. THE SOUTH 234 186 216 235 252 239 198 219 239 254 Locomotive engineers UNITED STATES 298 241 292 307 White 300 242 294 310 THE NORTH AND WEST 293 282 312 295 285 315 THE SOUTH 300 303 Machinists UNITED STATES 229 201 215 230 239 239 232 206 218 233 242 242 173 Ratio of nonwhite to white.... 75 THE NORTH AND WEST 233 212 217 233 242 240 236 216 219 235 244 243 183 Ratio of nonwhite to white .... 78 THE SOUTH 213 182 204 217 227 217 187 210 221 230 Mechanics and repairmen UNITED STATES Total 201 167 191 204 216 220 236 237 231 206 174 195 208 220 225 242 243 239 140 117 136 145 163 Ratio of nonwhite to white .... 68 67 70 70 74 THE NORTH AND WEST Total 211 186 199 212 222 225 237 237 235 White 214 191 202 215 225 229 241 241 245 164 147 154 163 178 Ratio of nonwhite to white .... 77 77 76 76 79 THE SOUTH Total 175 146 168 182 197 206 183 155 174 188 202 212 105 98 104 109 120 Ratio of nonwhite to white .... 57 63 60 58 59 Airplane mechanics and repairmen UNITED STATES Total 248 206 229 245 253 273 252 212 233 248 257 277 THE NORTH AND WEST Total 257 238 254 262 275 261 241 257 265 280 — Represents zero. 286 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less than 8 years 8 1 to 3 years 4 1 to 3 years 4 years or more years years Total 4 years 5 years or more Airplane mechanics and repairmen- --Con. THE SOUTH Total . . 231 229 236 White 235 232 240 Automobile mechanics and repairmen UNITED STATES Total 187 156 182 195 204 199 White 192 164 186 199 207 201 132 108 133 140 168 Ratio of n on unite to white.... 69 66 72 70 81 THE NORTH AND WEST 201 182 192 205 213 204 White 204 186 195 209 216 206 164 157 164 186 Ratio of nonwhite to white.... 80 81 78 86 THE SOUTH Total 153 133 154 166 172 181 White 161 142 160 172 177 184 96 90 100 Ratio of nonwhite to white.... 60 63 58 Radio and television mechanics and repairmen UNITED STATES Total 183 137 155 180 196 199 187 139 159 184 199 202 THE NORTH AND WEST Total 194 166 187 206 206 White 197 168 191 210 207 THE SOUTH Total 159 163 171 White 164 168 174 Painters, construction and maintenance UNITED STATES Total 167 136 167 173 189 182 White 173 142 171 178 194 190 Nonwhite 107 92 108 Ratio of nonwhite to white.... 62 65 61 THE NORTH AND WEST 184 157 180 187 200 196 189 161 183 192 204 202 132 Ratio of nonwhite to white.... 70 THE SOUTH Total 134 118 136 141 157 White 141 125 141 146 164 83 75 Ratio of nonwhite to white .... 59 60 Plasterers UNITED STATES Total 206 162 197 223 239 223 184 210 238 249 124 Ratio of nonwhite to white.... 56 — Represents zero. DATA ON LIFETIME EARNINGS 287 Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Total Less than 8 8 1 to 3 years 4 1 to 3 years 4 years or more years years Total 4 5 years years years or more Plasterers- -Con. THE NORTH AND WEST 223 185 208 237 248 232 195 215 247 253 THE SOUTH 166 133 - - - 196 103 Ratio of nonwhite to white .... 53 Plumbers and pipe fitters UNITED STATES Total 236 195 222 242 252 258 241 206 227 246 256 263 141 113 Ratio of nonwhite to white .... 59 55 THE NORTH AND WEST 252 238 238 255 259 267 255 244 241 258 262 270 196 Ratio of nonwhite to white .... 77 THE SOUTH 197 163 186 208 227 207 176 192 214 233 103 Ratio of nonwhite to white .... 50 Toolmakers, and die makers and setters UNITED STATES 276 244 264 271 282 288 279 248 266 274 285 291 THE NORTH AND WEST 280 246 266 275 285 292 282 251 269 277 288 295 THE SOUTH 233 235 Other construction craftsmen UNITED STATES 206 172 204 212 230 229 211 180 208 216 234 232 133 113 Ratio of nonwhite to white .... 63 63 Total 225 201 217 228 237 245 228 205 220 231 240 247 172 Ratio of nonwhite to white .... 75 THE SOUTH 168 149 174 174 203 175 158 178 179 209 108 100 Ratio of nonwhite to white .... 62 63 — Represents zero. 288 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less than 8 years 8 years 1 to 3 years 4 1 to 3 years 4 years or more years Total 4 years 5 years or mere Other metal craftsmen UNITED STATES 232 202 220 237 250 244 237 208 223 241 254 250 IT . .V. J + i~. 171 168 174 natio oi nonwnite to wmte,,.. 72 81 72 THE NORTH AND WEST Total 239 215 226 242 255 249 244 221 229 247 258 254 IT aw i fU 4 * n 18C 179 182 riatio oi nonwnixe vo wmw • , • . 74 81 74 THE SOUTH 203 175 193 214 225 208 181 196 218 230 135 Ratio of n on white to white .... 65 Other printing craftsmen UNITED STATES 268 230 252 275 276 258 272 235 256 279 280 262 _ lot NUK1H AND Wul 274 252 281 282 266 White 277 255 285 285 270 i fit. 5Uu 1 M 242 244 243 247 249 246 All other craftsmen, foremen , and kindred workers UNITED STATES 225 183 204 218 235 259 362 352 390 230 189 208 223 239 265 367 357 395 149 134 145 153 164 Ratic of nonvh i "to white a , , . 65 71 '70 69 69 TKF NORTH AMD WRST 235 201 212 226 241 268 366 355 395 239 205 215 230 244 272 370 359 400 173 164 171 Ratio of n on white to white.... 72 80 74 THE SOUTH 197 162 178 193 215 230 353 362 205 170 185 200 222 238 360 368 119 114 127 Ratio of non white to white.... 58 67 64 Operatives and kindred workers UNITED STATES 188 154 186 197 210 216 229 229 228 196 165 191 203 215 222 236 237 234 129 111 135 141 151 157 Ratio of nonwhite to white .... 66 67 71 69 70 71 THE NORTH AND WEST Total 202 178 195 206 216 218 228 228 228 206 183 199 211 220 223 233 233 233 158 148 157 161 169 171 Ratio of nonwhite to white .... 77 81 79 76 77 77 — Represents zero. DATA ON LIFETIME EARNINGS 289 Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selbcted Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary- High school College nl ea fcuiu loiui Total Less than 8 years 8 1 to 3 years 4 1 to 3 4 years or more years years years Total 4 years 5 years or more Operatives and kindred workers- - Con. THE SOUTH 152 127 155 166 186 199 233 240 165 140 163 176 195 210 252 262 100 91 107 109 116 122 Ratio of noivwhite to white .... 61 65 66 62 59 58 Bus drivers 172 137 172 176 196 181 176 146 175 182 198 179 133 - 135 Ratio of nonwhite to white .... 76 - 74 THE NORTH AND WEST Total 192 172 188 200 203 186 191 169 189 200 204 181 187 tiaxio oi nonwxii oe uo wmw; • • • • 98 THE SOUTH 135 111 135 144 175 145 123 140 153 182 1 1 _ ^ - . ■ J » 83 naT/io ox nonwni lc ou wiij. mi 57 Mine operatives and laborers (n. e.c.) UNITED bTATEo 180 152 173 196 212 268 183 155 176 199 216 274 132 122 Ratio of nonwhite to white . . . , 72 79 THE NORTH AND WEST Total 187 162 177 197 208 258 189 165 178 197 210 264 LttJL ouuin 176 148 170 195 217 180 151 173 200 223 124 120 Ratio of nonwhite to white .... 69 79 Truck and tractor drivers UNITED STATES 185 146 189 202 212 211 White 197 162 196 214 219 217 114 97 127 130 139 Ratio of nonwhite to white .... 58 60 65 61 63 THE NORTH AND WEST 210 183 204 220 225 221 215 189 208 226 229 225 154 140 158 156 167 Ratio of nonwhite to white .... 72 74 76 69 73 THE SOUTH 138 117 147 160 167 176 155 132 158 175 179 188 94 86 106 106 114 Ratio of nonwhite to white .... 61 65 67 61 64 — Represents zero. 290 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary- High school College Area and color Total Less than 8 years 4 1 to 3 years 4 1 to 3 4 years or more years years years Total 4 years 5 years or more Operatives and kindred workers (n. e.c. ) UNITED STATES 190 159 188 198 212 218 239 236 249 196 167 192 204 217 225 246 243 256 137 143 150 158 164 Ratio of nonwhite to white .... 70 72 74 74 73 73 _ a THE NORTH AND WEST 200 178 194 205 216 219 239 233 253 White 204 181 197 210 219 224 245 240 259 162 153 160 167 172 175 — Ratio of nonvhite to white .... 79 85 81 80 79 78 _ THE SOOTH 157 131 161 171 197 210 253 ioy 143 168 181 206 221 _ _ 105 97 113 116 122 m ■ Ratio of nonwhite to white.... 62 68 67 64 59 All other operatives and kindred workers UNITED STATES 189 156 184 194 209 211 217 222 200 196 166 189 200 214 218 223 229 204 130 112 132 138 149 148 Ratio of nonwhite to white.... 66 67 70 69 70 68 THE NORTH AND WEST 201 178 193 202 215 217 220 226 202 205 183 197 207 219 222 224 230 206 154 146 151 155 165 162 Ratio of nonwhite to white.... 75 80 77 75 75 73 THE SOUTH 153 128 152 164 180 185 164 140 160 172 189 196 98 89 103 106 112 Ratio of nonwhite to white.... 60 64 64 62 59 Service workers, including private household UNITED STATES 157 122 147 160 181 183 203 201 207 170 133 157 173 192 194 217 216 216 109 98 108 113 123 127 136 Ratio of nonwhite to white.... 64 74 69 65 64 65 63 THE NORTH AND WEST 168 136 155 170 188 189 211 212 207 176 141 161 178 195 197 219 221 213 126 118 121 129 137 139 Ratio of nonwhite to white.... 72 84 75 72 70 71 THE SOUTH Total 127 103 122 133 155 159 170 149 118 138 154 178 178 90 84 91 92 101 109 Ratio of nonwhite to white.... 60 71 66 60 57 61 Barbers UNITED STATES 180 159 184 186 189 177 189 164 189 195 196 193 113 Ratio of nonwhite to white.... 60 — Represents zero. DATA ON LIFETIME EARNINGS 29 Table E-2. — Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less 4 years or more than 8 1 to 3 4 1 to 3 8 years years years years Total 4 5 years years years or more Barbers- -Con. THE NORTH AND WEST 192 169 196 198 197 190 197 171 200 205 201 137 - jravio oi iiuiiwiix ia= uo win. utr • • « • 70 THE SOUTH 154 144 153 159 166 167 154 162 171 181 91 - 54 Protective service workers UNITED STATES 206 157 186 204 221 228 260 253 270 209 160 188 207 224 231 266 260 275 167 Ratio of nonwhite to white .... 80 THE NORTH AND WEST 216 166 194 212 227 235 264 259 270 218 171 197 215 230 238 270 265 177 Ratio of nonwhite to white .... 81 THE SOUTH 179 146 162 181 198 202 White 182 149 164 183 200 206 141 l\tx 11U UL IIUIIWIIX Ufci WJ WIIX UC . * • . 77 Firemen fire protection UNITED STATES Total 233 192 215 228 244 259 White 235 199 217 230 246 262 200 Ratio of nonwhite to white .... 85 THE NORTH AND WEST 242 227 237 250 267 Uh t + a 244 229 238 252 269 THE SOUTH 206 201 209 220 White 208 204 211 222 Policemen and detectives UNITED STATES Total 224 168 192 217 230 246 296 286 White 226 172 194 220 233 250 301 187 Ratio of nonwhite to white .... 83 THE NORTH AND WEST Total 233 181 197 228 237 252 298 236 186 200 231 239 255 303 THE SOUTH Total 194 156 172 185 205 White 196 158 174 186 207 — Represents zero. 292 APPENDIX E Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Less than 8 years 8 years 1 to 3 years 4 years 1 to 3 years 4 years or more Total 4 years 5 years or more All other service workers, including private household UNITED STATES Total 135 115 135 140 154 152 160 163 156 147 125 144 152 167 164 170 176 162 106 97 107 111 117 119 Ratio of nonwhite to white.... 72 78 74 73 70 73 THE NORTH AND WEST Total 146 130 143 150 162 158 168 176 157 White 152 134 148 157 169 165 174 184 122 117 119 125 129 128 Ratio of nonwhite to white.... 80 87 80 80 76 78 THE SOUTH Total 105 94 105 108 127 133 121 103 116 124 152 154 89 83 90 91 98 105 Ratio of nonwhite to white.... 74 81 78 73 64 68 Farm laborers and foremen UNITED STATES Total 80 62 90 103 128 151 192 91 70 96 111 134 155 200 49 45 56 62 86 Ratio of nonwhite to white.... 54 64 58 56 64 THE NORTH AND WEST Total 100 81 100 115 134 150 White 102 82 102 117 136 152 84 74 76 90 Ratio of nonwhite to white.... 82 90 75 77 THE SOUTH Total 58 50 67 81 113 71 58 75 95 130 42 40 46 47 Ratio of nonwhite to white.... 59 69 61 49 Farm laborers, wage workers UNITED STATES Total 76 60 88 97 117 138 167 White 87 68 93 105 121 141 49 45 55 59 77 Ratio of nonwhite to white.... 56 66 59 56 64 THE NORTH AND WEST Total 96 79 98 110 123 142 White 98 80 100 113 125 144 79 73 73 83 Ratio of nonwhite to white.... 81 91 73 73 THE SOUTH Total 55 49 63 72 96 White 65 57 70 84 110 42 40 45 47 Ratio of nonwhite to white.... 65 70 64 56 All other farm laborers and foremen UNITED STATES Total 138 96 124 150 195 White 144 106 126 153 198 90 Ratio of nonwhite to white.... 63 — Represents zero. DATA ON LIFETIME EARNINGS 293 Table E-2.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Selected Occupations, by Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less than 8 years 8 1 to 3 years 4 1 to 3 4 years or more years years years Total 4 years 5 years or more All other farm laborers and foremen — Con. THE NORTH AND WEST 158 130 128 156 191 156 131 128 154 190 THE SOUTH 118 76 132 86 Laborers, except farm and mine UNITED STATES 1A3 118 150 157 173 174 189 192 157 131 158 168 182 185 199 204 105 95 115 118 128 128 Ratio of nonwhite "to white.... 67 93 73 70 70 69 THE NORTH AND WEST 163 147 161 170 181 180 193 196 169 152 165 175 186 186 197 200 135 129 134 141 146 144 Ratio of nonwhite to white.... 80 85 81 81 78 77 iric, oUUln Total 105 92 114 119 141 158 118 99 122 135 159 183 87 82 97 95 105 111 Ratio of nonwhite to white.... 74 83 80 70 66 61 Occupation not reported UNITED STATES 215 157 185 205 239 281 360 345 386 232 173 194 218 251 294 375 359 400 133 118 133 137 145 167 180 rtdT^XO Ui. IIULIWIIX oc UU WIlXUc. • * • 57 68 69 63 58 57 48 THE NORTH AND WEST 225 171 192 213 245 281 366 350 395 239 181 200 225 256 293 379 364 407 1-48 138 143 148 155 176 Ratio of nonwhite to white.... 62 76 72 66 61 60 THE SOUTH Total 187 133 159 183 217 259 345 330 359 213 154 172 198 233 274 364 347 383 107 96 112 113 116 Ratio of nonwhite to white.... 50 62 65 57 50 — Represents zero. Source: Unpublished data of the Bureau of the Census. 294 APPENDIX E Table E-3.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Major Occupation Group, for the North and West Regions [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Area and color Elementary- High school College Less Total 4 years or more than 8 8 1 to 3 4 1 to 3 years years years years Total 4 5 years years years or more Total experienced civilian labor force THE NORTH Total 240 171 192 220 249 299 433 403 469 247 177 195 226 254 306 441 410 478 150 136 142 150 160 175 229 199 254 Ratio of nanwhite to white.... 61 77 73 66 63 57 52 49 53 Irlt wr.ol Total 254 164 206 231 263 294 401 369 436 263 171 211 237 269 300 409 378 445 166 131 150 163 184 189 265 226 326 Ratio of nonwhite to white.... 63 77 71 69 68 63 65 60 73 Professional, technical, and kindred workers THE NORTH 362 223 239 271 291 306 426 359 476 368 232 242 275 295 311 433 365 485 218 182 191 252 270 Ratio of nonwhite to white.... 59 62 61 58 56 THE WEST 358 228 239 272 301 303 417 356 458 White 364 237 246 278 305 308 424 362 466 275 238 336 392 nn Itiu Ul i i\M i wi i x lct win be • t t i 76 77 79 84 Farmers and farm managers THE NORTH 144 123 130 147 156 177 200 202 White 145 124 131 148 157 179 202 204 THE WEST Total 216 159 188 212 227 252 332 326 White 220 171 191 213 231 253 353 338 179 Ratio of nonwhite to white.... 81 Managers, officials, and proprietors , except farm THF NORTH Total 378 239 276 317 351 428 602 594 622 384 249 281 322 355 434 611 601 569 183 126 148 159 192 Ratio of nonwhite to white. 48 51 53 49 54 THE WEST Total 376 257 309 332 369 411 496 492 505 White 383 272 312 338 375 418 507 502 517 246 272 Ratio of nonwhite to white.... 64 73 Clerical and kindred workers THE NORTH Total 215 179 193 206 221 228 267 264 273 White 219 184 197 210 225 233 272 269 279 167 146 148 162 174 181 Ratio of nonwhite to white.... 76 79 75 77 77 78 THE WEST Total 223 185 200 214 227 229 254 250 260 White 227 191 203 218 232 234 261 257 266 177 174 185 179 Ratio of nonwhite to white. . . . 78 80 80 76 — Represents zero. DATA ON LIFETIME EARNINGS 295 Table E-3.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Major Occupation Group, for the North and West Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Years of school completed Elementary High school College Area and color Total Less than 8 years 8 1 to 3 years 4 years 1 to 3 years 4 years or more years Total 4 years 5 years or more Sales workers Total 282 188 218 245 274 317 403 405 396 White 285 194 221 248 277 320 408 410 402 Nonwhite 158 156 159 Ratio of nonwhite to white.... 55 63 57 TT-TF URQT lrLD wro x Total 284 213 224 244 278 306 372 383 352 289 221 228 248 282 310 377 388 359 203 Ratio of nonwhite to white.... 70 Craftsmen, foremen, and kindred workers Total 233 199 214 234 248 260 335 328 358 237 204 218 238 251 264 340 333 365 164 153 159 163 175 187 Ratio of nonwhite to white.... 69 75 73 68 70 71 lilt wlibl Total 245 212 230 243 255 259 315 306 345 White 249 218 235 247 259 264 320 311 351 Nonwhite 187 162 174 188 198 Ratio of nonwhite to white.... 75 74 74 76 76 Operatives and kindred workers THE NORTH Total 199 177 194 204 213 214 226 227 223 White 203 181 197 208 217 219 231 232 228 158 150 156 159 168 172 Ratio of nonwhite to white.... 78 83 79 76 77 79 THE WEST 212 182 203 218 227 229 236 233 217 189 207 222 231 234 240 236 159 140 157 168 173 171 Ratio of nonwhite to white.... 73 74 76 76 75 73 Service workers, including private household THE NORTH Total 165 135 153 168 185 181 207 210 202 White 172 140 160 177 192 189 216 220 209 124 115 117 126 136 138 Ratio of nonwhite to white.... 72 82 73 71 71 73 THE WEST Total 178 141 161 174 197 202 216 215 White 187 144 166 182 205 210 222 221 Nonwhite 135 129 136 139 141 142 Ratio of nonwhite to white.... 72 90 82 76 69 68 Farm laborers and foremen THE NORTH Total 93 74 91 103 122 White 96 76 92 104 123 Nonwhite 64 55 66 69 Ratio of nonwhite to white.... 67 72 72 66 THE WEST Total 108 86 115 127 146 150 White 110 87 120 131 149 154 92 83 Ratio of nonwhite to white.... 84 95 — Represents zero. 296 APPENDIX E Table E-3.— Estimated Lifetime Earnings for Males, by Years of School Completed, Color, and Major Occupation Group, for the North and West Regions— Con. [Thousands of dollars. Earnings from age 18 to 64 years] Area and color Years of school completed Total Elementary High school College Less than 8 years 8 years 1 to 3 years 4 years 1 to 3 years 4 years or more Total 4 years 5 years or more Laborers, except farm and mine THE NORTH 161 147 159 167 177 178 195 199 166 151 163 172 182 184 202 135 130 134 139 143 Ratio of nonwhite to white.... 81 86 82 81 79 THE WEST 171 148 170 179 191 185 White 177 153 175 184 196 191 138 126 133 148 153 Ratio of nonwhite to white. . . . 78 82 76 80 78 Occupation not reported THE NORTH 224 173 191 215 243 274 383 367 415 238 183 199 228 253 286 396 381 427 147 139 143 150 151 171 Ratio of nonwhite to white.... 62 76 72 66 60 60 THE WEST Total 230 168 198 209 257 276 321 303 350 242 176 207 220 269 283 333 314 359 155 137 142 171 Ratio of nonwhite to white.... 64 78 65 64 — Represents zero. Source : Unpublished data of the Bureau of the Census. INDEX A Accountants and auditors. See Profes- sional, technical, and kindred workers and Clerical and kindred workers. Accuracy of income statistics, 169 Adjustments in family income: Census — OBE comparisons, 184-186 Census — Sales Management compari- sons, 193 CPS— OBE comparisons, 187-189 Price change adjustments, 10 Aeronautical engineers. See Professional, technical, and kindred workers. Age and income: Related to education, 130-156 Related to occupation, 153-156 Age of family head, 34, 39 Top 5 percent of families, 23 Aggregate income: Census — Sales Management estimates, 195, 196 Families and unrelated individuals, 7, 8, 11, 13, 43-46 OBE— Census compared, 11, 173-183 Type of income, 173, 178 Agricultural scientists. See Professional, technical, and kindred workers. Airplane mechanics and repairmen. See Craftsmen, foremen, and kindred work- ers. Apprentices. See Operatives and kindred workers. Artists and art teachers. See Professional, technical, and kindred workers. Attendants, parking, etc. (see also Opera- tives and kindred workers), ranked by wage or salary income, 96, 97 Authors, editors, and reporters. See Profes- sional, technical, and kindred workers. Automobile mechanics and repairmen. See Craftsmen, foremen, and kindred workers. Average income: Families and unrelated individuals, 6-13, 18, 34, 43 After Federal income tax, 9, 10 Growth in real income, 9-11 In current and 1962 dollars, 9 Average income — Continued Wage or salary income by occupation, 236, 248, 252 B Baggagemen, express messengers, railway mail clerks. See Clerical and kindred workers. Bakers. See Craftsmen, foremen, and kindred workers. Bank tellers. See Clerical and kindred workers. Barbers, beauticians, and manicurists. See Service workers. Becker, Gary S., 166 Biological scientists. See Professional, tech- nical, and kindred workers. Blacksmiths, forgemen, and hammermen. See Craftsmen, foremen, and kindred workers. Boilermakers. See Craftsmen, foremen, and kindred workers. Bookkeepers, cashiers, ticket agents. See Clerical and kindred workers. Bowman, Mary Jean, 166 Brady, Dorothy S., 1, 27, 30, 74 Brakemen and switchmen, railroad. See Operatives and kindred workers. Brickmasons, stonemasons, and tile setters. See Craftsmen, foremen, and kindred workers. Bridgman, Donald S., 166 "Broken" homes, 39, 57 Bureau of Labor Statistics data, 76-79 Burns, Arthur F., 2 Buyers and department heads, store. See Managers, officials, and proprietors. C Cabinetmakers and patternmakers. See Craftsmen, foremen, and kindred workers. Carpenters. See Craftsmen, foremen, and kindred workers. Cement and concrete finishers. See Crafts- men, foremen, and kindred workers. Characteristics of families, 29-74 Changes in income level, 32 297 298 INDEX Characteristics of families — Continued Employment .status of head, 34, 42, 43 High-income families, 59, 65, 72 Low-income families, 39, 57, 64, 71 Occupational distribution, 57 Socioeconomic characteristics, 34, 50 Type of income, 42, 43 Characteristics of unrelated individuals : By income level, 33, 34 Changes in composition, 60-65 Charmen, janitors, and porters. See Serv- ice workers. Chemicals and allied products workers: Median income, by States, 258 Wage and salary trends, 119 Chemists. See Professional, technical, and kindred workers. Children, number in family, 34 Civil engineers. See Professional, techni- cal, and kindred workers. Clergymen. See Professional, technical. and kindred workers. Clerical and kindred workers: Education and income, 148, 150, 164 Income characteristics, 236, 248 Full-year workers, 252 Income distribution, 228, 240 Full-year workers, 232, 244 Income trends, 80-91 Lifetime earnings, 279, 294 Median wages, 82, 83 Wage trends, by States, 84-88 College graduates {see also Education and income) : Income pattern, 130-165 Lifetime earnings by occupation, 270-296 College presidents and deans. See Profes- sional, technical, and kindred workers. College professors and instructors. See Professional, technical, and kindred workers. Color and income : Education, 130-143, 146, 150, 157, 163, 270 Farm and urban, 157, 199 Income level, farm and nonfarm, 34 Lifetime income, 164, 270 Median income, 198 Money income, 34 Occupation, 150, 157, 163, 270 Color and longevity, 269 Components of change in income, 135-137 Components of income, 41, 173, 184, 188, 208 By States, 178, 182 Composition of broad income groups: In constant dollars, 50-64 Socioeconomic characteristics, 33-50 Compositors and typesetters. See Crafts- men, foremen, and kindred workers. Computation procedures, 213-221 Constant dollars, 213 Gini Index of Concentration, 220 Income aggregates, 215-220 Quintile distribution, 215 Ccnant, James B., 157 Concentration of income : Effect of changes in living arrangements, 5, 22 Gini ratio, 23, 220, 236, 248, 252 Share received by top 5 percent, 2, 19- 26, 90 Constant dollar computations, 213 Constant dollar income limits: Families, 51 Unrelated individuals, 61 Consumer's Price Index, in constant dollar computations, 214 Cooks. See Service workers. Copeland, Morris A., 28 County income data, sources, 190 Comparison of Census — Sales Manage- ment data: Adjustments of census data, 191 Summary of differences, by States, 195 Craftsmen, foremen, and kindred workers: Education and income, 149, 150, 164 Income characteristics, 237, 249 Full-year workers, 253 Income distribution, 229, 241 Full-year workers, 233, 245 Income trends, 80-91 Lifetime earnings, 282, 295 Median wages, 82 Wage trends, by States, 84-87 Current Population Survey (CPS) : CPS — Census matching study, 205-209 CPS — decennial census comparisons, 197-205 OBE-Census comparisons, 170-190 D Delaney, Marie M., 212 Denison, Edward F., 166 Dentists. See Professional, technical, and kindred workers. Designers and draftsmen. See Professional, technical, and kindred workers. INDEX 299 Douty, H. M., 91 Drivers, bus, taxi, and truck, and delivery- men. See Operatives and kindred workers. E Earned income of male wage and salary workers : At quartile positions, 236 By quintiles, 240, 244 Detailed occupations, 228, 232 Earnings (see also Wage or salary income) : Lifetime earnings, 270, 294 Ratio of initial to peak earnings, 143 Earning trends. See Wage or salary pat- terns. Economic growth, effect of education, 123 Economic welfare factors, 3, 10 Economists. See Professional, technical, and kindred workers. Editor and Publisher Company, county in- come series, 190 Editors and reporters. See Professional, technical, and kindred workers. Education and income, 123—167 Advantages of graduation, 142 Annual income, 138, 143, 145 By age, 130-160 Average money income, 139, 159 Change in mean income, 130, 143 Rate of increase, 135 By color and region, 130, 135, 139, 141, 145 Average money income, 139 By occupation, 147, 150, 164 White and nonwhite, 164 Changes since 1939, 156-163 Comparison of elementary school, high school, and college graduates, 158— 163 Components of change, 135 Concept of education, 1 25 Discrimination of non whites, 125 Effect on national economy, 123 Lifetime income, 162, 270, 294 Opportunities for occupational advance- ment, 144 Problems of interpreting data, 124 Variations about the average, 124 Women excluded from analysis, 138 Education concept, 125 Educational Policies Commission, 166 Elderly people, income, 22 Electrical and electronic technicians. See Professional, technical, and kindred workers. Electrical engineers. See Professional, tech- nical, and kindred workers. Electricians. See Craftsmen, foremen, and kindred workers. Elementary school graduates (see also Edu- cation and income) : Income pattern, 130-165 Lifetime earnings, 270, 294 Elementary school teachers. See Profes- sional, technical, and kindred workers. Elevator operators. See Service workers. Employment status: Family heads, 34 Wives, 23, 34, 40, 50 Evaluation data, sources, 169-172 Bureau of Old Age, Survivors, and Dis- ability Insurance (BOASDI), 171 Current Population Survey (CPS), 170 Internal Revenue Service (IRS), 171 Office of Business Economics (OBE), 169 Reinterview surveys, 170 F Fabricated metal workers: Median income, by States, 258 Wage and salary trends, 110 Families and unrelated individuals, number, 11, 13, 14, 16 Family (see also Family income) : Characteristics, 23, 29-74 By income level, 34 Top 5 percent, 23, 69, 70, 73 Composition changes, 50—61 High-income groups, 59 Low-income groups, 57—59 Defined, 4, 33 Household formation, 7 Living standards, changes, 32 Family income: Adjustments for comparability, 184, 189 Aggregates, 7, 8, 11, 13 Average, 6, 7, 11, 13, 18 After Federal income taxes, 9, 10 In current and 1962 dollars, 9 By States, 182 Definitions, 4-7 Farm and nonfarm families, 199 Growth in real income, 9—11 Income levels, 3, 12-15, 18, 21 Median, 16, 199 300 INDEX Family income — Continued Money income: Compared with personal income, 11, 21 In current and 1962 dollars, 16 Regions and States, 182 Quintile distribution, 3 Income limits, 2, 5 Sources, 41-50 Top 5 percent of families, 19, 23 Trends : Average income, 6-12 Inequality, 15, 19 Interpretation problems, 3 Type of income, 42, 43, 49, 50 Farioletti, Marius, 212 Farm income and urban income, 22 By color and sex, 199 Farm laborers and foremen: Education and income, 150 Income trends, 80-91 Lifetime earnings, 292, 295 Median wages, 82 Wage trends, by States, 84-88 Farmers and farm managers, 150, 277, 294 Firemen, fire protection. See Service workers. Fishermen {see also Laborers, except farm and mine), ranked by wage or salary income, 96 Fitzwilliams, Jeannette M., 7, 9, 27, 183 Food processing workers: Median income, by States, 258 Wage and salary trends, 115 Foremen {see also Craftsmen, foremen, and kindred workers), income pattern, 150, 156, 164 Full-year workers, 232, 248, 252 Furniture and lumber and wood products workers : Median income, by States, 258 Wage and salary trends, 118 G Galbraith, J. K., 30 Geographic distribution of income: Estimated lifetime earnings by occupa- tion, 270, 294 In manufacturing. See specific industry. Median income of laborers and opera- tives, 258 OBE — Census aggregates, 176-183 Occupational wage trends, 84-88 Geologists and geophysicists. See Profes- sional, technical, and kindred workers. Gini ratios: Compared with standardized ratios, 25 Computation procedure, 220 Top 5 percent of families, 23-26 Wage or salary income, 236, 248, 252 Goldsmith, Selma F., 3, 11, 27-29, 185, 212 Guards and watchmen. See Service workers. H Harrington, Michael, 28 Harris, Seymour E., 157 Havemann, Ernest, 166 High-income groups: Change in characteristics, 59 Characteristics of families, 23, 39, 67, 72 Dollar values used, 215 Occupations, 90, 248, 252 Share of total income, 2, 14, 19-26 Source of income, 40, 47 Top quintile compared to top 5 percent, 73 Total compared to urban, 23 Wage and salary workers, 248, 252 High school graduates {see also Education and income) : Income patterns, 130-165 Lifetime earnings, 270-294 Household formation, 7, 8 Household workers ranked by wage or sal- ary income, 96 Houthakker, H. S., 166 I Income and economic growth: By age groups, 129-138 For nonwhites, 135, 138 Increase through productivity, 133 Income concepts: Adjustments for price change, 10 Family income, 5, 33 Income-receiving unit, 4, 200 Measures of income status, 6, 29 Money and nonmoney income, 6 OBE — Census aggregates, 177 OBE — Census distributions, 181 Occupational series, 76, 84, 93 Sales Management, county estimates, 190 Income levels in constant dollars: For families and unrelated individuals in 1962 dollars, 14 For families in 1959 dollars, 51 INDEX 301 Income levels in constant dollars — Con. For unrelated individuals in 1959 dollars, 61 Income sources by income level, 41—50 Type of income, 49 Individuals. See Unrelated individuals. Inequality trends: Of family income, 15 Within major occupation groups, 88-91 Inspectors. See Craftsmen, foremen, and kindred workers. Inspectors, public administration. See Managers, officials, and proprietors. Insurance agents, brokers, and underwriters. See Sales workers. Internal Revenue Service (IRS) data: Adjusted gross income for 100 standard metropolitan areas, 218 IRS — Census matching study, 171 J Janitors, etc., ranked by wage or salary in- come, 96 K Kaitz, Hyman, 221 Keyserling, Leon, 30, 32 Kinds of income, 41-50 Kolko, Gabriel, 27 Kuznets, Simon, 1, 5, 15, 20, 27 Kuznets' income series, defined, 19 L Laborers, except farm and mine : Education and income, 150, 164 Income characteristics, 239, 251 Full-year workers, 255 Income distribution, 231, 243 Full-year workers, 235, 247 Income trends, 80—91 Lifetime earnings, 293, 296 Median wages, 82 Wage trends, by States, 84-87 Laborers, operatives, and other workers, median income, by industry and States, 258 Laborers, ranked by wage or salary income, 96 Lampman, Robert J., 31 Lawyers and judges. See Professional, technical, and kindred workers. Liebenberg, Maurice, 27, 183 Lifetime income or earnings, 162-165, 270, 294 Estimating procedures, 126-138 Linemen and servicemen, telegraph, tele- phone, and power. See Craftsmen, foremen, and kindred workers. Locomotive engineers. See Craftsmen, foremen, and kindred workers. Longshoremen and stevedores. See Labor- ers, except farm and mine. Lorenz curve, 15, 20, 220 Low-income groups: Characteristics, 33-41, 64, 65, 71 Compared with lowest quintile, 71 Composition changes: Families, 57-60 Unrelated individuals, 60-64 Income limits, 29—32 Income trends, 12—15 Sources of income, 47 Lumbermen, raftsmen, and woodchoppers. See Laborers, except farm and mine. Lumbermen, ranked by wage or salary in- come, 96 M Machinery manufacturing workers: Median income, by States, 258 Wage and salary trends, 113 Machinists. See Craftsmen, foremen, and kindred workers. Mail carriers. See Clerical and kindred workers. Man-years lived, white and nonwhite males at each age level, 269 Managers, officials, and proprietors, except farm: Education and income, 150, 164 Income characteristics, 236, 248 Full-year workers, 252 Income distribution, 228, 240 Full-year workers, 232, 244 Income trends, 80-91 Lifetime earnings, 278, 294 Median wages, 82 Wage trends, by States, 84-87 Mandel, B. J., 212 Manufacturing wage and salary trends (see also specific industry) : Income concept, 108 Industries covered, 107 Limitations of data, 108 Median income, by States, 258 Patterns of specific industries, 109-122 Source of data, 107 Marital status of family head, 34 Mechanical engineers. See Professional, technical, and kindred workers. 302 INDEX Mechanics and repairmen. See Craftsmen, foremen, and kindred workers. Median income: By industry and State, 258 By residence, color, and sex, 198 Families and unrelated individuals, 16 Wage or salary workers, 75 Median wages, occupational trends: Detailed occupations, 93-105 Major occupation groups, 82 Manufacturing. See specific industry. Medical and dental technicians. See Pro- fessional, technical, and kindred workers. Messengers, ranked by wage or salary in- come, 96 Miller, Herman P., 17, 77, 162, 165, 193, 212 Mine operatives and laborers. See Opera- tives and kindred workers. Molders, metal. See Craftsmen, foremen, and kindred workers. Money income: Census — CPS comparison, 200 Census — OBE estimates, 11, 21 Characteristics of income groups, 33 Defined, 6 Distribution trends by sex, by quintiles, 77 For top quintile, 25 In current and 1959 dollars, 16 Kinds of income, 43-46 Morgan, James, 221 Motormen, railway, mine, factory, etc. See Operatives and kindred workers. Musicians and music teachers. See Profes- sional, technical, and kindred workers. N National Science Foundation, education study, 125 Natural scientists. See Professional, techni- cal, and kindred workers. Net income defined, Kuznets' series, 19 Newsboys ranked by wage or salary income, 96 O OBE — Census income aggregates com- pared : Adjustments for comparability, 172 Differences in concept, 177 Earnings and other income, 174—177 Procedural differences, 174 Self-employment income, limitations, 177 OBE — Census income aggregates com- pared — Continued Total money income, by States, 175-181 Components of income, 178 Data for families, for persons, 181 Ratio of wages and salaries to total, 180 Trends in family income, 1 1 OBE — Census income distributions com- pared : Adjustments to CPS data, 187-189 Adjustments to 1960 Census data, 184- 187 Comparison of adjusted CPS and OBE data, 189 Differences in concept, 181 Low-income group discrepancy, 187 OBE estimating procedure, 184 OBE family personal income concept, 184 OBE, 1960 Census, CPS compared, 181— 190 Trends in family income, 12-21 OBE estimates: Income aggregates, 172-183 Income size distribution, 183-190 National income accounts, 169 Ratio of wages and salaries to total in- come, 180 Trends in family income, 7-12 Ober, Harry, 79 Occupation of head of family, 34 Occupational classification, detailed, 223- 227 Occupational wage trends for major groups, 75-91 BLS wage differentials by skills, 76-80 By States, 84-87 Differential changes, 80-84 For women, 88 Income concepts, 84 Inequality within groups, 88-91 Median wages, 82 Workers in top quintile, 88-91 Workers in top 5 percent, 90 Occupational wage trends for specific oc- cupations : By wage level, 95-97, 228-255 Changes in dispersion, 98-102 Dispersion within occupations, 99, 100, 104 Limitations of data, 93 Mean income, 248, 252, 258 Occupations excluded, 94 Occupations included, 223 Patterns of wage increase, 102, 103 Source of data, 93 INDEX 303 Office machine operators. See Clerical and kindred workers. Office of Business Economics data. See OBE estimates and OBE — Census in- come entries. Officials and administrators, public. See Managers, officials, and proprietors. Operatives and kindred workers: Education and income, 150, 164 Income characteristics, 238, 250 Full-year workers, 254 Income distribution, 230, 242 Full-year workers, 234, 246 Income trends, 80-91 Lifetime earnings, 288, 295 Median wages, 82 Wage trends, by States, 84-88 Ostheimer, Richard S., 212 Ozanne, Robert, 91 P Painters, construction and maintenance. See Craftsmen, foremen, and kindred workers. Painters, except construction and mainte- nance. See Operatives and kindred workers. Paley, Leon R., 212 Pareto curve: Described, 216 Pareto Law, 15, 216 Use in computation of constant dollars, 213 Use in computation of income aggre- gates, 173, 215 Validity test, 219 Pharmacists. See Professional, technical, and kindred workers. Physicians and surgeons. See Professional, technical, and kindred workers. Plasterers. See Craftsmen, foremen, and kindred workers. Plumbers and pipe fitters. See Craftsmen, foremen, and kindred workers. Policemen, detectives, sheriffs, and marshals. See Service workers. Postal clerks. See Clerical and kindred workers. Poverty limits, 30 Price change adjustment, 10 Primary and fabricated metals workers: Median income, by States, 258 Wage and salary trends, 112 Primary metals workers: Median income, by States, 258 Wage and salary trends, 109 Printing craft. See Craftsmen, foremen, and kindred workers. Private household workers. See Service workers. Professional, technical, and kindred workers : Education and income, 150, 164 Income characteristics, 236, 248 Full-year workers, 252 Income distribution, 228, 240 Full-year workers, 232, 244 Income pattern, 40, 161 Income trends, 80-91 Lifetime earnings, 270, 294 Median wages, 82 Wage trends, by States, 84-88 Protective service workers. See Service workers. Psychologists. See Professional, technical, and kindred workers. Purchasing power in 1962 dollars, 9-11 Q Quality check, 170 Quintile distributions: Computation procedures, 215 Families and unrelated individuals, 3, 21 Highest quintile, 67, 72 Inequality within occupation groups, 88 Limits, 215, 240, 244 Lowest quintile, 64, 71 Selected occupations, 240, 244 Wage or salary workers, 76 R Radio and television mechanics and repair- men. See Craftsmen, foremen, and kindred workers. Real estate agents and brokers. See Sales workers. Real income growth, 9-11 Reder, M. W., 91 Regional distributions: Education and income, 130, 135, 139, 141, 146 Census — Sales Management income series, 195 Lifetime earnings, 270, 294 OBE — Census income aggregates, 176- 183 304 INDEX Regional distributions — Continued Wage or salary income, percent of total income, 180 Wage trends, by States, 84-88 Reinterview surveys, 209-211 Renshaw, Edward F., 166 Rivlin, Alice M., 166 Rollers and roll hands, metal. See Crafts- men, foremen, and kindred workers. Roofers and sheet metal workers. See Craftsmen, foremen, and kindred workers. S Sailors and deck hands. See Operatives and kindred workers. Sales engineers. See Professional, techni- cal, and kindred workers. Sales Management, income series, 190-197 County data compared with census data, 195-197 Standard metropolitan statistical area data, 194 Sales workers: Education and income, 150, 164 Income characteristics, 237, 249 Full-year workers, 253 Income distribution, 229, 241 Full-year workers, 233, 245 Income trends, 80-91 Lifetime earnings, 281, 295 Median wages, 82 Wage trends, by States, 84-88 Salesmen and salesclerks. See Salesworkers. Samuelson, Paul, 2 Schmid, Calvin F., 166 Schultz, Theodore W., 166 Secondary school teachers. See Profes- sional, technical, and kindred workers. Self-employment income, farm and non- farm, 43-49 Service workers, including private house- hold: Education and income, 150, 164 Income characteristics, 238, 250 Full-year workers, 254 Income distribution, 230, 242 Full-year workers, 234, 246 Income trends, 80-91 Lifetime earnings, 290, 295 Median income, 82 Ranked by wage or salary income, 96 Wage trends, by States, 84-88 Sex distributions: Median income, 198 Total money income, 206, 211 Type of income, 208 Wage or salary workers, 76, 82, 88 Shipping and receiving clerks. See Cleri- cal and kindred workers. Shoemakers (see also Craftsmen, foremen, and kindred workers), ranked by wage or salary income, 96 Size of families, 34 Skilled and unskilled workers: Earning ratio, skilled to unskilled, 79 Earning trends, 76-80 Social scientists. See Professional, tech- nical, and kindred workers. Social Security, effect on household forma- tion, 8 Social, welfare, and recreation workers. See Professional, technical, and kin- dred workers. Source of income: By income level, 42, 47 By States, 178 High-income families, 48 Low-income families, 47 Type of income, 41-50, 173, 208 Sports instructors, athletes, entertainers. See Professional, technical, and kin- dred workers. Stability of wage structure, by occupations: By deciles, 95-98 Effect of automation, 98 Standard metropolitan statistical areas: Adjusted gross income, 218 Census and Sales Management income data, 196 Standard Rate and Data Service, county income data, 190 Standardization of Gini ratio, 25 State data: Aggregate money income, by type, 178, 182 Differences between Census and Sales Management income estimates, 195 Estimated lifetime earnings by occupa- tion, 270, 294 Manufacturing wage trends. See spe- cific industry. INDEX 305 State data — Continued Median income by industry, 258 OBE — Census income aggregates com- pared, 11, 176-183 Occupational wage trends, 84-87 Source of income, 178 Wage or salary income as percent of total income, 180 Stationary engineers, cranemen, hoistmen. See Craftsmen, foremen, and kindred workers. Stationary firemen. See Operatives and kindred workers. Statisticians and actuaries. See Profes- sional, technical, and kindred workers. Stenographers, typists, and secretaries. See Clerical and kindred workers. Stone, clay, and glass products workers: Median income, by States, 258 Wage and salary trends, 120 Structural metal workers. See Craftsmen, foremen, and kindred workers. Survival rate of male infants, 269 T Tailors and furriers. See Craftsmen, fore- men, and kindred workers. Tax Foundation, 27 Teachers. See Professional, technical, and kindred workers. Technical engineers. See Professional, technical, and kindred workers. Technicians. See Professional, technical, and kindred workers. Telegraph operators. See Clerical and kindred workers. Textile and apparel manufacturing workers : Median income, by States, 258 Wage and salary trends, 117 Toolmakers, and die makers and setters. See Craftsmen, foremen, and kindred workers. Transportation, communications, and other public utilities workers, median in- come, by States, 258 Transportation equipment manufacturing workers : Median income, by States, 258 Wage and salary trends, 114 Trends of income shares, measures used, 6 Type of family income, 41-50 U Unearned income: By States, 178, 182 By type, 184, 188, 189 Detailed sources of family income, 41-50 Unemployed family heads, 34 Unrelated individuals: By age, 33 Changes in composition by income level, 60-64 Characteristics by income level, 33-41 Definition, 5, 33 Low-income groups, 33-37 Sources of income, 41-48 Urban family income, top 5 percent of families, 23 W Wage or salary income: By States, 176, 178, 182 Median income by sex, 76 Quintile distribution by sex, 77 Ratio to total income. 180 Selected occupations: Arithmetic mean and Gini ratio, 236, 248, 252 Income level, 228, 232 Quartile distribution, 236 Quintile distribution, 240, 244 Wage or salary patterns: By education. See Education and in- come. By sex, 76, 80, 82, 88 Detailed occupations, 93-105 Labor demand changes, 102 Major occupation groups, 80-91 Manufacturing. See Manufacturing wage and salary trends. Quintile distribution, 77, 88-91 Skilled and unskilled workers, 76-79 Variations in employment, 102—105 Wage or salary workers, income character- istics for selected occupations: Distribution by income size, 228 Gini ratio, 236, 248, 252 Income at quartiles, 236 Income at quintiles, 240, 244 Interquartile range, 236, 248, 252 Mean income, 236, 248, 252 Proportion of full-year workers, 248 Share of income received by top 20 per- cent, 248, 252 Waiters, bartenders, and counter workers (see also Service workers), ranked by wage or salary income, 96 306 INDEX Wealthiest 5 percent of families. See High- income groups. Weisbrod, Burton A., 166 Welders and flame cutters. See Operatives and kindred workers. Welfare factors, 3, 10 West, Patricia, 166 White and nonwhite workers: By occupation, 164, 270, 294 Education and income, 130-165 Lifetime earnings, 165, 270, 294 Median family income, by sex, 198 Wholesale and retail trade workers, median income, by States, 258 Wife in paid labor force, 22, 34, 40, 50 Wolfle, Dael, 166 Wolkstein, Irwin, 212 Women : Heads of families, 34, 39 Income distribution, 76-78 Indirect effect of education on income, 138 Median income, 198 Total money income, 206, 211 Type of income, 208 Wage trends by occupation, 80-83, 88 Working wives, 22, 34, 40, 50 it U. S. GOVERNMENT PRINTING OFFICE : 1968 O - 327-625