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UD 026 853

O'Neill, June; And Others

The Economic Progress of Black Men in America.

Clearinghouse Publication 91.

Commission on Civil Rights, Washington, D.C.

Oct 86

166p.

United States Commission on Civil Rights, Washington,

DC 20425.

Reports - Research/Technical (143)

MF01/PC07 Plus Postage.

*Black Employment; Blacks; Civil Rights Legislation;

*Economically Disadvantaged; *Education Work

Relationship; Equal Opportunities (Jobs); Labor

Market; *Males; Multivariate Analysis; *Racial

Differences; Racial Discrimination; Research

Proposals; *Salary Wage Differentials;

Unemployment

IDENTIFIERS '.*Economic Equity

ABSTRACT

This report attempts to identify and analyze the

causes of the differences between the earnings and employment of

black males and white males. Although the earnings gap between black

and white men was substantially reduced between 1940 and 1980, black

men still earn less than white men. While the relative earnings of

black men has risen since 1940, their relative employment has

declined. Factors that influence the earnings gap include the

following: (1) discrimination; (2) education; (3) region of

residence; (4) industrial sector; and (5) marital status. The report

finds that while a narrowing of racial differences in worker

characteristics accounts for part of the earnings convergence, other

factors, including declining racial prejudice, federal civil rights

policies, and unmeasured changes in employment skills, must be

considered. The precise effect of civil rights policy remains

undetermined. Some of the evidence attributes earnings differentials

to differences in knowledge and skills acquired in school. Further

research on the following issues is recommended: (1) the effect of

civil rights programs; (2) black-white differentials in educational

attainment; (3) declining labor force participation among younger

black men; (4) upward earnings bias due to labor force withdrawal;

and (5) the failure of the black-white unemployment gap to narrow.

The report includes four appendices, a bibliography, 51 statistical

tables, and nine figures. (AF)

Reproductions supplied by EDRS are the best that can be made

* from the original document.
U.S DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL PESOURCES INFORMATION

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+Ttus document has been reproduced as

received from tne person or organaat.on

ongmating it

C Mmor changes nave been made to improve

reproduce on quality

Points of oew or opmons stated in thiSdOCu

ment do not necessaray represent &two'

UERI position or Polcy

United States Commission

on Civil Rights

Clearinghouse Publication 91

October 1986

WO

The Economic

Progress of

Black Men

in America
U.S. COMMISSION ON CIVIL RIGHTS

The U.S. Commission on Civil Rights is an independent, bipartisan agency first

established by Congress in 1957 and reestablished in 1983. It is directed to:

Investigate complaints alleging that citizens are being deprived of their right

to vote by reason of their race, color, religion, sex, age, handicap, or national

origin, or by reason of fraudulent practices;

Study and coilect information concerning legal developments constituting

discrimination or a denial of equal protection of the laws under the Constitution

because of race, color, religion, sex, age, handicap, or national origin, or in the

administration of justice;

Appraise Federal laws and policies with respect to discriminatir or denial of

equal protection of the laws because of race, color, religion, sex, age, handicap,

or national origin, or in the administration of justice;

Serve as a national clearinghouse for information in respect to discrimination

cr denial of equal protection of the laws because of race, color, religion, sex, age,

handicap, or national origin;

Submit reports, findings, and recommendations to the President and the

Congress.

MEMBERS OF THE COMMISSION

Clarence M. Pendleton, Jr., Chairman

Murray Friedman, Vice Chairman

Mary Frances Berry

Esther Gonzalez-Arroyo Buckley

John H. Bunzel

Robert A. Destro

Francis S. Guess

Blandina Cardenas Ramirez

J. Al Latham, Jr.. Staff Director
The Economic

Progress of

Black Men

in Ameilca

United States Commission

on Civil Rights

Clearinghouse Publication 91

October 1986
Acknowledgments

This report was prepared by June O'Neill, James Cunningham, Andy Sparks, and

Hal Sider, a former employee who worked on the initial stages of the study. Nabeel

Alsalam, Matthew Cooper, Harriet Duleep, Robert E. Johnson, and Philip Lyons

also contributed to the report. Jonathan Dunn, Elizabeth Farkas, and Christopher

Jones provided able research assistance. Editorial and production assistance were

provided by Sally Harriston, Carol-Lee Hurley, Darcy Johnson, Martha Jones,

Felice Roggen, Joseph Swanson, and Linda Zimbla. Appreciation is also extended

to Cathy H. Somers and Audrey H. Wright who typed the many drafts of this

report and helped to prepare the final manuscript.

The report was prepared under the overall supervision of June O'Neill, Assistant

Staff Director for Programs and Policy.

This report is part of a larger project on the incomes of Americans. The members

of the advisory committee to the project are: Prof. Glen Cain, Department of

Economics, University of Wisconsin; Prof. Claudia Goldin, Department of

Economics, University of Pennsylvania; Prof. Glenn Loury, John F. Kennedy

School of Government, Harvard University; Prof. Jacob Mincer, Department of

Economics, Columbia University; Prof. Stephan Thernstrom, Department of

History, Harvard University; Prof. Finis Welch, Department of Economics,

University of California at Los Angeles.

Other outside experts who have provided helpful comments include, alphabetically: Prof. Alfred Blumrosen, Rutgers Law School, Rutgers; Prof. Charles Brown,

Department of Economics, University of Michigan; Prof. Barry Chiswick,

Department of Economics, University of Illinois at Chicago; Prof. Reynolds

Farley, Department of Sociology, University of Michigan; Dr. Harry Gilman, U.S.

Department of Labor; Prof. Nathan Glazer, Graduate School of Education,

Harvard University; Prof. Eric Hanushek, Department of Economics, University

of Rochester; Prof. Robert Higgs Department of Economics and Business,

Lafayette College; Prof. Robert Margo, Department of Economics, Colgate

University; Prof. William J. Wilson, Department of Sociology. University of

Chicago.

iii

5
Contents

Executive Summary 1 Introduction 7

Part I: An Overview of Racial Patterns in Earnings and Employment, 1940-1980 9

1. Trends in Earnings and the Economy 10

Earnings Growth

Changes in the, Relative Earnings Differential

Patterns of Growth

Is Black Earnings Growth a Statistical Illusion?

Distinguishing Fluctuations and Trends

Annual Changes in Relative Earnings

Earnings Inequality

Differences and Trends in Earnings Inequality

Relative Earnings Gains for High and Low Earners

Concluding Comments

7s. Trends in Employment and Unemployment 26

Measures of Current Labor Force Status

Labor Force Participation

Unemployment

Weeks and Hours of Work

Summary

Part II: Sources of the Earnings Gap, 1940-1980 50

3. The Economics of Discrimination: Theory and Measurement 51 Measurement of Discrimination

4. Education and Training

Differences in Years of Schooling

Differences in School Quality arid Educational Achievement

Measures of Educational Outcomes

Summary of Racial Differences in Educational Attainment

The Effect of Racial Differences in Schooling on Raciai Differences in Earnings

iv

54
1

Work Experience and On-The-Job Training

5. Geographic Migration and Other Sources of the Wage Gap 78

Geographic Location and Migration

Industrial Sector

Marital Status

6. A Multivariate Analysis 89

Accounting for the Earnings Gap

Racial Differences in Coefficients

Changes in the Earnings Ratio Over Time

Summary

Part III: Why the Wage Gap Narrowed: ,.1ternative Hypotheses 99

7. Labor Market Effects of Civil Rig Etc Policy 100

Background

Issues in Enforcement

Econometric Studies

Conclusions

8. Unexplained Wage Differentials 110

Factors Underlying the Trend

The Current Wage Gap and Unmeasured Characteristics

Concluding Comments 116

What Has Happened Since 1980?

Issues for Future Research

Statement of Chairman Clarence M. Pendleton, Jr. 118

Statement of Commissioner John H. Bunzel Joined by Vice Chairman Murray

Friedman and Commissioners Esther G. Buckley and Robert Destro 120

Dissenting Statement of Commissioners Mary Frances Berry, Francis S. Guess, and

Blandina Cardenas Ramirez 122

Appendices

A. Data Development 124

B. The Impact of Sample Definition on Relative Earnings 129

C. Regression Analysis: Methodology and Estimates 139

D. Black-White Earnings Ratios 150

Bibliography 152

Tables

1.1 Real Earnings Growth: Average Annual Percentage Rates of Change for

Men by Race and Age 11

1.2 Black-White Annual Wage and Salary Ratios for Men by Age 11

1.3 Black-White Weekly Wage and Saiary Ratios for Men by Age 13

1.4 Black-White Hourly Wage and Salary Ratios for Men by Age 13

1.5 Black-White Annual Total Earnings Ratios for Men by Age 14

1.6 Change in Black-White Earnings Ratios by Decade for Men Ages 25-64 14

1.7 Dispersion of Wage and Salary Earnings by Race 20
L8 Dispersion of Weekly Earnings by Race, Education, and Region 21

1.9 Change in Black-White Earnings Ratios for Men 24

2.1 Male Civilian Labor Force Participation Rates by Race and Age 28

2.2 Black Male Civilian Labor Force Participation Rates by Age and Education 29

2.3 White Male Civilian Labor Force Participation Rates by Aige and Education 30

2.4 Changes in Male Labor Force Participation Rates by Years of School, Race,

and Age 31

2.5 Benefits and Replacement Rates in the Social Security Disability and

Retirement Programs 35

2.6 Percentage of the Male Population Receiving Social Security Benefits by Age and Race 36

2.7 Trends in Nonparticipation in the Labor Force and Social Security Recipien- cy by Race and Age 37

2.8 Male Unemployment Rates by Race and Age 41

2.9 Male Unemployment Rates by Race F.,ducation, and Region 44

2.10 Accounting for the Black-White Gap in Unemployment of Men Ages 25-64, 1980 45

2.11 Weeks and Hours Worked for Men by Race and Age 47

4.1 Mean Years of School of Male Wage Earners Ages 25-64 by Region and Race 55

4.2 Years in Which Successive Birth Cohorts Reach Different Stages in the Life

Cycle 55

4.3 Mean Years of School Completed by Race and Age 56

4.4 Enrollment per 100 Males of School Age by Race 59

4.5 Highest Grade Completed and Years of School Attended by Race for Cohorts Born Pre-1885 to 1961-64 61

4.6 Percentage Distribution of Years of School Completed by Race for Cohorts

of Men Reaching Ages 25-29 Between 1940 and 1980 62

4.7 Measures of School Resources in Public Elementary and Secondary Schools by Race . 64

4.8 Male Illiteracy Rate by Cohort and Race 66

4.9 White-Black Gap in Standardized Test Scores 68

4.10 Mean AFQT Percentile Test Scores of Men Ages 19-21 by Race and Education 70

4.11 Black-White Ratios of Weekly Wage and Salary Earnings by Age and Education 74

4.12 Black-White Ratios of Weekly Wage and Salary Earnings by Education and Age 76

5.1 Regional Distribution of Racial Groups 79.

5.2 Rates of Net Migration from the South for Men Ages 20-24 79

5.3 Annual Wage and Salary Earnings of Men Ages 25-34 by Race, Region, and Education 81

5.4 Black-White Weekly Wage and Salary Ratios by Region and Age 82

5.5 Distribution of White Male Labor Force by Sector and Age 83

5.6 Distribution of Black Male Labor Force by Sector and Age 84

5.7 Male Workers Ages 35-44 Leaving Agriculture Over the Decade 84

5.8 Percentage by Which Weekly Earnings of Married Men Exceed Weekly Earnings of Unmarried Men 85

5.9 Proportion of Men Married with Wife Present by Age and Race 86

5.10 Black-White Ratios of Weekly Earnings by Marital Status and Age 87

6.1 Effects of Differences in Characteristics on the Wage Gap 92

vi
6.2 Effects of Differences in Individual Characteristics on the Black-White

Differential by Selected Age Groups 93

6.3 Estimated Effects of Worker Characteristics on Weekly Earnings of Men

Ages 25-34 by Race 94

6.4 Unadjusted Ratios of Black-White Earnings Compared to Ratios Adjusted to

Reflect 1980 Coefficients 97

7.1 White Parents Objecting to Desegregated Schools 1C,

7.2 Effect of the OFCCP on Employment of Black Men Relative to White Men 107

8.1 Change in Black-White Weekly Earnings Ratios Between Cohorts by

Education, Age, and Region 111

8.2 Change in Black-White Weekly Earning Ratios Within Cohort by Education

and Region 112

8.3 Black-White Earnings Gap in 1980 by Region, Age. and Education 114

Figures

1.1 Civilian Unemployment Rate, 1939-1985 16

1.2 Male Civilian Unemployment I? ate by Race, 1948-1985 17

1.3 Nonwhite-White Male Income Ratios, 1948-1984 19

1.4 Black-White Annual Earnings Ratios, Ages 25-64 23

2.1 Rates of Civilian Unemployment and Labor Force Nonparticipation for

Nonwhite Men Ages 20 and Over, 1954-1985 33

2.2 Rates of Civilian Unemployment and Labor Force Nonparticipation for

White Men Ages 20 and Over, 1954-1985 34

2.3 Black Men Ages 25-64 Not at Work in Previous Year by Reason 39

2.4 White Men Ages 25-64 Not at Work in Previous Year by Reason 40

7.1 Nonwhite-White Earnings Ratios, 1953-1084 103

vii
Executive Summary

The economic status of black men in the United

States has shown substantial long-run improvement.

Between 1940 and 1980, the real earnings of black

men increased 340 percent versus 164 percent for

white men. As a result the earnings gap between

black men and white men was reduced by close to

half.

Although this impressive gain is cause for optimism, the fact remains that black men still do not

earn as much as white men. Moreover, although the

relative earnings of blacks have increased considerably, their relative employment has declined. In the

light of a 350-year history of racial discrimination,

officially sanctioned in many places until less than 25

years ago, the persistence of racial differences in

economic status is a natural source of concern. It

underscores the importance of monitoring and studying the position of blacks in America.

This report constitutes a major attempt to identify

and analyze the causes of black-white differences in

male earnings and employment. It is the first in a

series of studies on the economic status of different

ethnic and racial minorities and women. The idea for

this large-scale project was initially developed by

Commissioner John H. Bunzel. As an analysis of

discrimination in the workplace, the project fulfills

the mandate of the United States Commission on

Civil Rights to present reports to the President,

Congress, and the Nation on discrimination on the

basis of race, color, sex, age, religion, handicap, or

national origin.

The problems facing the black community are

complex. This report examines black-white differences in labor market status among adult men, while

planned reports will deal with black-white differences among women and youth.

The study focuses on the years 1940 to 1980, a

period spanning roughly the 20 years before and 20

years since the Civil Rights Act of 1964 created

legal sanctions against racial discrimination in employment. An important new source of datamicrodata files from the 1940 through 1980 decennial

Censuses of Populationis utilized to derive many

of the measures used in the analysis. The principal

advantages of these data files are that they provide

large samples and define variables consistently over

time.

Trends in Earnings

Between 1940 and 1980, the gap in earnings

between black men and white men was substantially

reduced, although the pattern of change differed

from decade to decade. The earnings gap narrowed

most rapidly during the 1940s. It remained largely

unchanged during the 1950s but then continued to

narrow again during the economic boom of the

1960s and even during the weaker macroeconomic

climate of the 1970s. The uneven growth in relative

earnings during the 1940s and 1950s may reflect the

economic consequences of World War II. Proportionately more white than black men served in the

war, and as a result, the earnings of white men may

have been depressed during the readjustment period

after the war, only to rebound in the 1950s. The

relative earnings of blacks did not slip back during

the 1950s, evidence that the gains made by blacks

during the 1940s were not merely a wartime bubble,

'cut represented genuine progress.

10

1
The decades in which black-white earnings differences have narrowed most sharply are not always

those in which the earnings of blacks, taken alone,

have grown the fastest. For instance, the real

earnings of black men grew rapidly during the 1950s

(at a rate of 3.4 percent a year), out this increase did

not exceed that enjoyed by whites, for whom the

1950s were the best decade of the 1940-1980 period.

Conversely, racial differences in earnings continued

to narrow during the 1970s, even though the real

earnings of black men increased by less than 2

percent a year because of a sluggish economy.

(Among younger black men in the 1970s, the rate of

increase was only 0.6 percent annually; white male

earnings fell.) Only during the 1940s and 1960s,

decades of strong economic growth, did blacks

experience both relative and absolute gains in earnings. Still, racial differences in earnings have narrowed considerably, and the process has been

underway since at least 1940.

The report also examines racial differences and

trends in earnings inequality. With the exception of

1940, the analysis reveals that earnings inequality is

greater among blacks than among whites. Unlike the

trend in average earnings, there does not appear to

be any tendency for racial convergence in earnings

inequality.

The relatively high unemployment of black men

and the greater sensitivity of their employment to

the business cycle explain some of the difference in

earnings inequality between blacks and whites as

well as the detailed pattern of this difference from

decade to decade.

Trends in Labor Force Participation and

Unemployment

Although black men have made substantial gains

in relative earnings, their relative employment has

declined as a consequence of both a decline in labor

force participation and a rise in unemployment

relative to whites.

Between 1940 and 1980, the labor force participation of men declined. The decline was particularly

large among older men and men with less than 12

years of schooling, and it accelerated after 1960.

Black male participation fell considerably more than

that of whites, even when schooling and age are

held constant. For example, between 1960 and 1980,

the decline in labor force participation rates among

men aged 45-54 with 0-11 years of school was about

12 percentage points for blacks and 8 percentage points for whites.

Much of the decline in the labor force participation of both black and white men aged 45-64 is

attributed to the liberalization and rising benefit

levels of Federal disability programs (supplemented

by food stamps and other benefits). This hypothesis

is supported by a variety of evidence and outside

research. For instance, during the 1960s and 1970s,

there was a surge in the number of men who

reported not working during the year because of a

disability. This increase coincided with the greatest expansion of disability programs and cannot be

attributed to a worsening in men's health. Unemployment, on the other hand, was found to have

played only a minor role in the downward trend in

labor force participation. This role was largely

cyclical, as fluctuations in unemployment were

echoed by small fluctuations in the number of

discouraged workers and, hence, in the size of the

labor force.

The disproportionate decline in labor force participation among older black men can be traced to their

greater incidence of disability and lower incomes,

and to the fact that Federal disability benefits and

other transfers are relatively more generous at lower

income levels.

The decline in labor force participation among

younger black men (25-.34) was not so great as at

older ages, and it is less readily explained. Increased

involvement in crime and imprisonment and a

decline in marriage possibly underlie the decline in

work attachment, but there may be complex interactions among these factors, each of which may cause

and be affected by the others.

In addition to differences in labor force participation, a significant racial differential in unemployment

has persisted over the decades, even within schooling and regional categories. The differential in

unemployment has always been much larger in the

North than in the South. This was especially true in

the period 1940-1960, despite the greater levels of

discrimination against blacks in the South. One

explanation for the relatively low black unemployment rate in the South was the relative absence of

unionization or other pressures to equalize pay. As a

result, discrimination in the South may have been

reflected in lower pay, rather than in diminished

employment opportunities. The widening of the

black-white gap in unemployment over the 1940-

1980 period remains puzzling, however, in light of

1 1
the narrowing of racial differences in schooling and

occupation.

The relative decline in employment of black

males, in addition to being a matter of concern in

itself, may produce an upward bias in the growth of

relative black earnings. If those who leave the work

force have relatively low earnings, their departure

1.3, ill cause an artificial increase in the earnings of the

remaining work force. Because black employ mein

has declined significantly more than white, the

growth in black male earnings is potentially o erstated to a greater degree than would be the case for

whites. This relative overstatement in earnings

growth would cause an illusory narrowing of the

earnings gap. Empirical research suggests, howex,r,

that this potential bias, under most plausible assum,

Lions, would not account for a large share of tl

growth in the relative earnings of black males.

Discrimination and Other Sources of the

Earnings Gap

One of the goals of this report is to provide

analysis that will help inform the national debate

over how best to aid minorities. Isolating the

underlying causes of racial differences in earnings

will enable government to formulate more effective

civil rights and social policies.

Discrimination is one potential source of earnings

differences between blacks and whites. Discriminatory behavior in the current labor market by

employers, fellow workers, or consumers could lead

to lower earnings and occupational status for blacks.

Because of the influence of education and training

on earnings, however, the shadows of past discrimination must also be considered.

Discrimination against blacks in State and local

government expenditures on schooling is likely to

have affected racial differences in educational attainment seen among workers today. Measures of skills

acquired in on-the-job training over the years can

also reflect employer discrimination in training

offered to blacks. Moreover, past discrimination in

the labor market may have reduced the incentive of

blacks to obtain training or education.

These distinctions are important. Remedies for the

effects of past discrimination (for example, improving school resources) are quite different from remedies for current labor market discrimination (for

example, litigation under the Civil Rights Act).

A method of di:ectly measuring labor market

discrimination has not yet been developed. Instead,

2

empirical studies of discrimination typically assess

the factors that appear to be related to skills or

productivity, and they then adjust the wage gap for

racial differences in these factors. If all racial

differences in productivity could be measured perfectly, then the amount of the wage gap left

unexplained after accounting for skills could be said

to reflect current discrimination in the labor market.

Because of the problems involved in measuring

productivity, definitive estimates of current labor

market discrimination cannot be obtained. But an

analysis of the major factors contributing to the

black-white wage gap can enlighten our understanding of the sources of the gap and why it narrowed

over ti ne. Such an analysis can also provide insight

into the possible role of market and governmental

discrimination.

The report examines at length several broad

factors that are believed to have important effects on

earnings and the wage gap: schooling, region of

residence, industrial sector, and marital status.

Education has traditionally been the key to economic progress for groups starting out with disadvantages, and it has been particularly important to

blacks because of the extreme educational disadvantages that they initially experienced. At emancipation, and for several decades thereafter, most blacks

lived in poor rural counties of the South where they

were allocated a disproportionately small share of

school resources. The men whose experiences are

documented in this study were born between 1876

and 1955. The circumstances of their southern roots

have been an important impediment to black economic development.

Despite these initial handicaps, blacks have made

enormous gains in education, sharply narrowing the

gap with whites in years of school completed. The

measured increase in the relative schooling of blacks

may even be understated, both because the schooling of older black cohorts who attended ungraded

s-itools was likely overstated in the 1940 and 1950

censuses and because racial differences in the quality

of schooling likely narrowed.

Differences in region of residence and industrial

sector of employment have also affected the relative

productivity of blacks. Historically, an important

reason for low relative earnings among black males

has been the disproportionately large concentration

of the black population in the South, where wages

are relatively kw. The migration of blacks from the

South to high -wage urban areas of the North

3
/

between 1940 and 1970 contributed to the reduction

in the earnings gap during these years. Rapid

economic growth in the South relative to other

regions, however, has narrowed the North-South

earnings gap, especially among blacks. Consequently, southern location has had a diminishing effect on

the earnings gap.

Similarly, the relatively large concentration of

black workers in the low-paying agricultural sector

accounted for some of the black-white differential in

earnings in the past, especially prior to the 1960s.

The subsequent shift of blacks into the higher paying

government and nonagricultural sectors accounts

for some of the observed narrowing in earnings

differences. These trends, however, appear to have

run their course.

Accounting for Trends in the Earnings

Gap

Factors such as schooling, geographic region, and

type of employment probably have interactive and

overlapping effects on earnings. This study reports

on a multivariate analysis that was undertaken to

measure the joint effects of these factors on the

black-white earnings gap and on the trend in the gap

over the 1940-1980 period.

Trends in the Gap

Changes in educational attainment, region of

residence, and industry of employment have played

an important role in narrowing the earnings gap

between 1940 and 1980. For instance, between 1940

and 1980 the earnings of young blacks (ages 25-34)

grew 62 percent faster than the earnings of young

whites; of this relative gain, nearly 40 percent can be

attributed to a narrowing in racial differences in

characteristics. Nonetheless, this leaves more than

half of the convergence in earnings unexplained.

The growing similarity between the races in years

of schooling, region of residence, and industrial

sector does not account for much of the observed

narrowing in the racial gap in earnings and suggests

that other factors may supply the full explanation.

The leading candidates that potentially can help

account for the unexplained convergence in the

earnings gap are declining racial prejudice, governmental civil rights policies, and unmeasured changes

in employment skills (for example, from improved

school quality). Overstatement of the earnings gain

due to differential patterns of labor force withdrawal

may also play a role. These factors are hard to

4

quantify, although qualitative evidence and research

findings on their importance can be examined.

Effects of Civil Rights Policy

Federal civil rights programs and policies have

undoubtedly contributed to a reduction in discriminatory behavior in the labor market. Studies reviewed in this report suggest that civil rights policies

have contributed to the improvement in the relative

earnings of black men. Because of data limitations,

however, the studies do not provide conclusive

evidence about the magnitude of the effect of civil

rights policies generally, nor do they determine the

specific contribution of individual pr'icies.

Studies based on time-series "dta have found an

upward trend in relative black earnings after 1964

that cannot be explained by the 1948-1963 earnings

trend or by changes in variables such as relative

black educational attainment. The time-series analyses exclude many important variables, such as

changes in attitudes or changes in unmeasured gkill

factors that may have contributed to the upward

trend in relative black earnings. Because they are

limited to the period after 1948 (when earnings data

first become available on an annual basis), these

studies exclude the 1940s when, according to this

report, the relative earnings of blacks increased

faster than in any other single decade between 1940

and 1980. The omission of the 1940s from these

analyses may result in an overestimate of the effect

of civil rights policies on earnings growth after 1964.

Given these limitations, it has not been established

how much civil rights policies have contributed to

the growth in relative black earnings.

In contrast to time series studies, which examine

civil rights programs as a whole, studies of the

Federal contract compliance program focus on a

specific program, in this case one that imposes

affirmative action requirements on firms with Federal contracts. Although these studies find that the

program is associated with increased black employment in firms with Federal contracts, they do not

provide strong evidence that the program has

provided jobs for those who ordinarily would not

have one. That is, the program may have largely

resulted in the shifting of employed men from one

kind of firm to another. The fact that the relative

employment of blacks declined significantly during

the period under analysis raises the question whether

the contract compliance program has, on balance,

increased black employment.

3
In sum, research has not yet determined the

precise role of civil rights policies in improving the

labor market status of black men. Research in this

area is complicated by the many forces, both public

and private, that have operated to Improve the

economic status of blacks. The same forces, such as

the civil rights movement, that led to the passage of

civil rights legislation, by themselves may have

broken down discriminatory barriers and influenced

public attitudes about race.

Moreover, it has not proven possible to identify

the specific contributions of the various civil rights

programs and policies. The Civil Rights Act of 1964

undoubtedly broke down barriers for many blacks,

and it also may have served as a catalyst in reducing

prejudice among employers and white coworkers.

The ,.ffect: of Title VII litigation and the pressures

of th : Federal contract compliance program may

also be important factors influencing the increase in

relative black earnings. Unfortunately, existing empirical studies have not been able to disentangle the

effects of these different types of civil rights activities.

The Level of the Gap in 1980

The report's analysis of the sources of the earnings

gap in 1980 indicates that racial differences in certain

relevant characteristics can account for 30 to 40

percent of the earnings gap, depending on the age

group examined. After adjusting for years of school,

region of residence, industrial sector, and marital

status, the weekly earnings of black workers aged

25-34 were 12.6 percent lower than those of white

workers; at ages 45-54, this unexplained residual was

22 percent.

The size of the earnings gap varies considerably

among detailed region-education groups and according to the earnings measure used (hourly, weekly or

annual). For instance, the hourly earnings gap is

small among 25-34 year olds living outside the

South: 3.5 percent for college graduates, 9 percent

for high school graduates, and 5.4 percent for those

with 8-11 years of school. This differential is larger

when measured by weekly earnings (ranging from

8.6 to 14.5 percent) and even larger when measured

by annual earnings (from 11.7 to 20 percent). It is a

matter of judgment as to which is the best measure.

The various measures of the earnings gap in part

may reflect past and present discrimination in the

labor market and in part omissions of data on worker

characteristics that affect productivity. Achievement tests are often used to assess the marketable

knowledge and skills acquired in schools. The

evidence reviewed in the report showed large

differences in scores between blacks and whites with

the same nominal amount of schooling. These

differences have been attributed to differences in

family background (parents' education and occupation, and family income) as well as to differences in

the quality of schools attended. Several studies have

attempted to measure the link between earnings and

the skills measured by test scores. Based on these

relations, at least a third of the remaining differential

in weekly earnings among 25-34 year olds may be

attributed to differences in knowledge and skills

!earned in school. The fact that recent results show

that black-white differences in achievement scores

have begun to converge is a hopeful sign for future

convergence in the wage gap.

Concluding Comments

Changing racial differences in measured characteristics, such as years of schooling and geographic

region, account for some of the narrowing in the

wage gap between 1940 and 1980. According to the

data analyzed, however, these changes were not the

primary forces underlying the trend.

Black-white earnings ratios rose considerably

from generation to generation even when the comparison was confined to population groups narrowly

defined by years of school, region, and age. There is

evidence that improvements in the quality of schools

attended by blacks and declining discrimination in

the labor market both contributed to the relative

gain in earnings made by blacks during the 1940-

1980 period.

The decline in labor market discrimination appears to have occurred both before and after the

Civil Rights Act of 1964 was passed. In the earlier

period, the decline in discrimination may have been

prompted by events, such as World War II, that

made white Americans more aware of racial prejudice. In the recent period, the civil rights movement

and government antidiscrimination policy undoubtedly have played a positive role.

Although the wage gap narrowed substantially

over the 1940-1.980 period, it has not been eliminated. After adjusting for years of school completed,

region of residence, and other measurable characteristics, a gap in weekly earnings of 12.6 percent for

25-34 year olds remains. The remaining gap is in

part attributable to unmeasured differences in work-

. 4

5
er characteristics that affect productivity. For instance, racial differences in achievement test scores

suggest that black-white differences still exist in

terms of knowledge and skills acquired in school.

Persistent racial discrimination in labor markets may

well account L'Ir part of the current differential in

earnings, but its share cannot be determined with

available data.

What Has Happened Since 1980?

The black-white gap in earnings has remained

roughly constant since 1975. The constancy of the

gap 6 , -,g the early 1980s is noteworthy because

that period was characterized by the worst recession

since the 1930s. (The overall male unemployment

rate grew from 5.1 percent in 1979 to 9.9 in 1982 and

1983 and then fell back to 7.0 in 1985.) In view of the

greater cyclical sensitivity of black earnings and

employment, it would not have been surprising to

see the relative earnings and employment status of

blacks deteriorate and then rebound during this

period. Such a pattern seems to appear in annual

earnings data from the Current Population Survey.

However, the black-white ratio of annual earnings

for full-time year-round workers stayed relatively

constant during the periodabout 70 percent. Differences in labor force participation rates have also

remained constant, breaking a decades-long trend of

relative declines in black male labor force participation.

Issues for Future Research

Several issues remain unresolved and warrant

additional research. The following are particularly

important:

Existing research has not been able to assess

fully the effects of specific civil rights programs

and policies on the economic status of blacks. For

instance, although studies of affirmative action

have found that Federal contractors increased

their employment . blacks more than noncontractors, it is not known whether the men hired by

contractors would have been employed in good

jobs even without the program or whether the

program resulted in a net increase in black male

employment. More research is needed to deter6

mine the full effect of civil rights programs on the

earnings and employment of black men.

A substantial differential remains in the educational attainment of black and white men in terms

of years of school completed and of scholastic

achievement. A considerable body of research,

including this report, has den nstrated the importance of schooling ..s a mean: ,,f upward mobility.

Future research should investigate the various

public and private factors that affect scholastic

achievement.

The decline in labor force participation among

younger black men, at a time when other indicators of economic success (i.e., earnings) have been

improving, is not well understood. Several causal

factors were suggested, including worsened employment opportunities, increased involvement in

crime and imprisonment, and declining marriage

rates. These and other possible factors, and their

interactions, should be investigated in greater

depth. Research dealing with effects of diminished

work attachment on the future earnings and

employment of younger men is also needed to

help assess the importance of the recent trends.

Accurate measures are needed of the possible

upward bias in earnings resulting from the decline

in labor force participation. Existing research has

used indirect statistical methods to estimate the

possible effect of "selection bias" on earnings

gains and on the black-white earnings gap. Direct

information on the prior earnings of those who

withdraw from the labor force is needed before

any firm conclusions can be drawn. If the earnings

gains of black men are found to be seriously biased

by labor force withdrawal, then it would be

necessary to reevaluate the extent to which

discrimination has abated and, specifically, the

extent to which civil rights policies have raised

the economic status of black men.

The failure of the black-white gap in unemployment to narrow is puzzling in view of the

convergence in education and occupational status.

Research on this subject is limited, and additional

theoretical and empirical work is needed.

"5D
Introduction

The economic status of black men in the United

States has shown substantial long-run improvement.

Between 1940 and 1980, the real earnings of black

men increased by 340 percent versus 164 percent for

white men. As a result the earnings gap between

black men and white men was reduced by close to

half.

Although this impressive gain is cause for optimism, the fact remains that black men still do not

earn as much as white men. Moreover, although the

relative earnings of blacks have increased consieerably, their relative employment has declined. In light

of a 350-year history of racial discrimination, officially sanctioned in many places until less than 25

years ago, the persistence of racial differences in

economic status is a natural source of concern. It

underscores the importance of monitoring and studying the position of blacks in America.

This report constitutes a major attempt to identify m

and analyze the causes of black-white differences in

male earnings and employment. It is the first in a

series of studies on the economic status of different

ethnic and racial minorities and women. The idea for

this large-scale project was initially develop '-)y

Commissioner John H. Bunzel. As an analysis of

discrimination in the work.place, the project fulfills

the mandate of the United St_,,.., Commission on

Civil Rights to present reports 1.1 the President,

Congress and the Nation on discrimination on the

basis of race, color, sex, age, religion, handicap, or

national origin.

The problems facing the black community are

complex and will be addressed in several reports.

This report focuses on research about black-white

differences among adult men, while planned reports

will deal with black-white differences among women and youth.

One of the major goals of this report is to provide

analysis that will help inform the national debate

over how best to aid minorities. Isolating the

underlying causes of the economic condition of

blacks enables formulation of effecth e civil rights

and social policies. If the causes of black gains in

relative economic status are incorrectly identified,

future policies aimed at improving the economic

status of blacks may prove ineffective.

Our conclusions point to a number of factors that

contribute to the wage gap and its narrowing over

time: the convergence in the educational attainment

of blac% and white men; the massive migration of

blacks away from the rural South, long the Nation's

poorest region; the shift of black men away from

agricultural labor and towards more economically

rewarding sectors; and a decline in labor market

discrimination. The report finds that the negative

effect of labor market discrimination on the earnings

of blacks, though still evident, abated significantly

between 1940 and 1980. This is attributed to societal

forces that changed attitudes, such as the civil rights

movement, and to government policy, such as the

Civil Rights Act of 1964. The analysis also suggests

that many of the factors which have increased the

relative wages of black men were themselves facilitated by declining racial discrimination. For instance, governments; discrimination in the provision

of schooling and an atmosphere of declining racial

7
prejudice provided added incentive for blacks to

acquire more schooling and training.

The report is organized as follows. Part I presents

an overview of racial patterns in earnings and

-employment for the years 1940 through 1980.

Chapter 1 explores basic trends in various measures

of individual economic status and in the economy,

examining the shift in the national economic picture

as well as the unique position of black Americans.

Chapter 2 examines trends in employment and

unemployment, and investigates why black labor

force participation has fallen considerably below

that of whites while black unemployment remains

much higher.

Part II examines sources of the earnings gap

between. black and white men. Chapter 3 examines

economic theories of discrimination and the problems of measuring the effect of discrimination on

earnings. Chapters 4 and 5 identify several important

determinants of earnings and examine each as a

potential source of the earnings gap and as a force in

narrowing the gap since 1940. Education (covered in

8

chapter 4) plays a key role in the analysis because it

was withheld from blacks during slavery and was

meagerly provided to them for a 75-year period after

emancipation. The eventual increase in educational

resources available to blacks was an important factor

in their economic rise. Other major factors considered include region of residence and industry (chapter 5). Chapter 6 presents a multivariate statistical

analysis of the effect of all of these characteristics on

the relative earnings of black men over the 1940-

1930 period.

Part III explores various hypotheses as to why the

wage gap has narrowed. Chapter 7 describes the

major civil rights programs and policies and evaluates their effects on black wages and employment.

Chapter 8 provides an overall assessment of the

various forces, measured and unmeasured, that have

contributed to the narrowing of the wage gap and of

the factors that underlie the remaining differential.

The final section of the report presents concluding

remarks and an agenda for future research.
PART I

An Overview of Racial Patterns in Earnings

and Employment, 1940-1980

The first part of this report presents an overview explores trends in employment and unemployment

of patterns in earnings and employment for black and investigates the causes of declining black male

and white men between 1940 and 1980. Chapter 1 employment.

examines basic patterns in earnings. Chapter 2

.1, j a

A

9
Chapter 1

Trends in Earnings and the Economy

Between 1940 and 1980, the earnings of black men

rose from 42 percent to 69 percent of the earnings of

white men, reducing the black-white gap in earnings

by close to half. This chapter describes these gains in

earnings, primarily using the decennial Censuses of

Population from 1940 to 1980. Various methods of

defining earnings and specifying the sample are

employed in the analysis. The analysis tries to

determine to what extent the observed gain in the

relative earnings of black men represents true progress rather than simply reflecting transitory economic conditions in particular census years. In addition

to comparing the average earnings of blacks and

whites, the within-race distribution of earnings is

explored. The basic objective is to examine whether

the gains made by blacks were shared equally by

low- and high-income individuals.

Earnings Growth

The expansion of the aggregate economy is a

principal means by which earnings grow for blacks

and whites. The past 40 years, though punctuated by

recessions, have been, for the most part, a period of

sustained real gains in earnings.' The magnitude of

earnings gains, however, has varied considerably

from decade to decade. Table 1.1 shows these gains

expressed as average annual growth rates.' Between

1 Comprehensive data on the earnings or Income of the

population are not available before 1940. The information that is

available suggests that between emancipation and 1940, in some

periods blacks made greater income gains than whites and in

others they did not. Robert Higgs (1977) estimates that the per

capita income of blacks rose from 24 to 35 percent of the per

capita income of whites between 1867-1868 and 1900. Also see 10

1940 and 1980, the real annual wage and salary

earnings of white men grew by 164 percent while

the earnings of black men rose by 340 percent.

Economic growth during the 1940s was rapid,

propelled, in part, by recovery from the Great

Depression and accelerated by mobilization and

production for World War H. These years were

marked by exceptionally rapid earnings growth

among blacks (5.9 percent per year). In fact, the

earnings gains made by blacks in this decade

exceeded those of any other decade between 1940

and 1980. More modest gains were made by whites

in the 1940s (2.5 percent per year). During the 1950s

earnings growth accelerated rapidly among whites

to 3.8 percent but slowed among blacks to a rate of

3.4 percent. In the 19 i0s, earnings rose among blacks

to an annual rate of more than 4 percent while the

corresponding figure for whites was 3 percent.

During the 1970s, earnings growth slowed considerably for both races although black gains continued

to exceed white gains. This slowdown was particularly severe among younger workersthe members

of the large baby-boom cohort. Among white men

ages 25-34, for example, real earnings actually

declined slightly over the decade.

Higgs (1986) for a discussion of relative changes in black income

and other inuices of economic well-being before 1940. 2 Most tabulations presented in this report are based on

Information derived from the decennial Censuses of Population.

These data are detailed in app. A.

.4 9
TABLE 1.1

Real Earnings Growth: Average Annual Percentage Rates of Change for Men by Race

and Age

Ages 25-34

1940-1950 1950-1960 1960-1970 1970-1980

Whites 3.5 3.9 2.9 -0.2

Blacks 6.5 3.4 4.5 0.6

Ages 35-44

Whites 2.2 3.9 3.0 1.0

Blacks 5.7 3.6 4.0 2.0

Ages 45-54

Whites 1.9 3.4 3.3 1.3

Blacks 5.4 3.2 4.4 2.5

Ages 55-64

Whites 1.9 3.6 2.8 1.6

Blacks 5.0 3.3 4.1 2.6

Total

Whites 2.5 3.8 3.0 0.6

Blacks 5.9 3.4 4.2 1.7

Note Tabulations based on annual wage and salary earnings of male wage and salary workers with any earnings dunny the year The self-employed and unpaid family workers are

excluded Source Census of Population, 1940-1980, Public Use Sample

TABLE 1-2

Black-White Annual Wage and Salary Ratios for Men by Age

Ages 1940 1950 1960 1970 1980

25-34 46.6 62.2 59.6 69.7 75.3

35-44 40.4 56.8 55.4 60.9 67.8

45-54 38.2 53.5 52.5 58.4 65.4

55-64 39.2 52.9 51.3 58.4 64.6

Total 41.5 57.4 55.3 62.3 68.9

Note Tabulations based on wages and salaries of male wage and salary workers who worked in calendar year The self-employed and unpaid family workers are excluded Source Census of Population, 1940-1980, Public Use Sample

11
Changes in the Relative Earnings

Differential

The fact that the earnings of black males have

been rising more rapidly than the earnings of white

males means that the ratio of the earnings of blacks

to the earnings of whites has increased. This section

examines the growth of relative earnings over the

past 40 years using different definitions of earnings.

Summary measures for adult males (ages 25-64)

are shown in table 1.2. The data indicate that the

mean arinual earnings of black wage and salary

workers rose from 42 percent to 69 percent of the

mean annual earnings of whites between 1940 and

1980. Thus, nearly one-half of the earnings gap of

1940 was eliminated over this period.

Table 1.3 presents measures of the black-white

ratio calculated on the basis of mean weekly earnings.' The weekly earnings ratios are higher than

the annual earnings ratios, reflecting the fact that

blacks, on average, work fewer weeks per year than

whites. The overall trends, however, are very

similar. Between 1940 and 1980, the relative weekly

earnings ratio rose 28.4 percentage points while the

annual earnings ratio rose 27.4 percentage points.

Ratios of black-white hourly earnings are higher

still (table 1.4), reflecting the fact that, on average,

blacks work fewer hours per week than whites.'

The increase in relative earnings for blacks between

1940 and 1980 is again somewhat greater when

calculated on an hourly basisup 32.7 percentage

points.

The calculations described above exclude selfemployed workers. This rule is often applied in the

analysis of earnings because of the practical difficulty in separating the returns on labor from the

returns on capital investments by the self-employed

in their own firms. Furthermore, decennial censis

data on self-employment earnings are believed to ''e

of poor quality.

These qualifications notwithstanding, earnings ratios that include self-employed men can be computed for 1950-1980 and are presented in table. 1.5.

These ratios are lower than those based solely on

The 1940 ratios so include a partial control for hours and,

therefore, are not strictly comparable to the other yeas. This is

an unavoidable characteristic of the 1940 census, which asked for

full-time equivalent weeks rather than simply weeks worked.

For 1940. estimates of hours worked per year are based on the

assumption that a full-time equivalent week reflects 40 hours. For

other years, estimated hours worked reflect the product of weeks

worked in the previous year and hours worked in the survey

week. These calculations are limited to individuals at work in the

12

wage and salary workers because the self-employed,

who generally have higher than average earnings,

are disproportionately white. Inclusion of the selfemployed, however, results in a greater apparent

increase in relative earnings over time than is

observed for wage and salary workers alone. Between 1950 and 1980, the "total" earnings ratio

(table 1.5) rose by 15 percentage points compared

with an increase of 11 percentage points for wage

and salary workers.

In sum, the convergence of racial differences in

earnings is clearly evident. Similar trends are observed whether the calculations are made on an

annual, weekly, or hourly basis and regardless of

whether wages and salaries or total earnings are

examined.6

Patterns of Growth

The relative earnings of black men between 1940

and 1980 did not grow at a constant pace (see table

1.6). By far the most rapid advance occurred during

the 1940s. In sharp contrast, relative black earnings

barely increased on an hourly basis and even

declined slightly on an annual basis during the 1950s.

In fact, this was t ie only decade during the 40-year

period in which he earnings of blacks did not rise

more rapidly than the earnings of whites. From 1960

to 1980, the relative annual earnings of blacks rose

steadily, increasing by about 7 percentage points in

each decade.

When hourly earnings are examined, the same

basic pattern of decade by decade changes in

relative earnings appears as in the annual data, but

there are some important differences. For example,

the increase in the hourly earnings ratio exceeded

the gain in the annual earnings ratio during those

decades when the relative unemployment of blacks

increased. These decades are 1940-1950, 1950-1960,

and 1970-1980.6 Similarly, when relative unemployment fell, as from 1960-1970, the annual earnings

ratio increased by more than the hourly ratio.

It is striking that when the analysis is broken into

two periods-1940-1960 and 1960-1980that

survey week. The results of an analysis of the selectivity Impact of

this limitation indicate that restricting the sample in this fashion

has a very small effect on earnings ratios. Hourly earnings

tabulations are based on an hours-weighted mean of individuals'

hourly earnings.

3 The sensitivity of the calculated ratio to inclusion or exclusion

of specific groups such as the self-employed, students, the armed

forces, etc., is examined in detail in app. B

6 See fig. 1.2 and the discussion below. Also see chap. 2

21
TABLE 1.3

Black-White Weekly Wage and Salary Ratios for Men by Age

Ages 1940 1950 1960 1970 1980

25-34 48.9 66.4 63.7 71.7 79.4

- 35-44 43.0 60.6 59.5 63.3 70.8

45-54 40.2 56.0 56.2 60.5 68.2

55-64 40.6 55.9 55.0 59.8 65.7

Total 43.6 60.8 59.2 64.3 72.0

Note: Tabulations are based on wages and salaries of male wage and salary workers who worked In calendar year. The self-employed and unpaid frank, workersare excluded Weeks worked reported In 1940 census are the "full-time equivalent" weeks worked during 1939 Actual weeks worked are reported for 1950-1980

Source: Census of Population, 1940-1980; Public Use Sample.

TABLE 1.4

Black-White Hourly Wage and Salary Ratios for Men by Age

Ages 1940 1950 1960 1970 1980

25-34 48.9 68.4 67.2 76.1 84.3

35-44 43.0 62.6 63.6 67.2 75.9

45-54 40.2 57.7 59.7 64.2 72.7

55-64 40.6 56.3 57.6 62.6 68.6

Total 43.6 62.4 62.6 68.0 76.3

Note: Calculated by dividing weekly earnings (see note to table 1 3) by hours worked during survey week

Source: Census of Population, 1940-1980; Public Use Sample.

13

es 0

4, 4
TABLE t5

Black-qhite Annual Total Earnings Ratios for Men by Age

Ages 1940 1950 1960 1970 1980

25-34 57.5 57.4 68.1 74.0

35-44 51.0 51.8 58.0 64.7

45-54 46.5 48.1 55.5 62.7

55-64 46.5 47.4 54.9 61.5

Total - 51.2 51.6 59.4 66.2

Note: Tabulations are based of sum of wages and se nes and self-employment income for individuals whoworked In calendar ,ear Self-employment income was not reported in 107.

Source: Census of Population. 1940.1980; Public Use Sample.

TABLE 1.6

Change in Black-White Earnings Ratios by Decade for Men Ages 25-64

(percentage points)

Annual

earnings

Hourly

earnings

1940-50 +15.9 +18.8

1950-60 -2.1 +.2

1960-70 +7.0 +5.4

1970-80 +6.6 +8.3

Source Tables 12 and 14

roughly correspond to the decades before and after

passage of the Civil Rights Act of 1964, the

convergence in earnings is found to proceed at

roughly similar rates. For the first 20 years, relative

annual earnings increased by 13.8 percentage points;

for the next 20 years, relative earnings increased by

13.4 percentage points (In percentage terms, the

earnings ratio grew faster during the first half of the

sample period, 33 percent compared to 25 percent.)

This pattern of growth suggests that forces were at

work to narrow the earnings gap even before the

emergence of the major Federal civil rights programs and policies. These forces probably included

relative gains in black educational attainment, migration of blacks from the South to the North, and a general decline in discrimination. (For example, the

specter of Nazism during World War II may have

led to a reduction in racial prejudice.) Although

civil rights programs undoubtedly played an impor14

1

tant role in narrowing wage differences, they were

one of several sources of black gains.

In sharp contrast to the growth decades of the

1940s, 1960s, and 1970s, the negligible gains in

relative earnings of black males during the 1950s

appear anomalous. One possible ex,lanation for this

relates to the labor market consequences of World

War II. The expansion of industrial production

during the war is likely to have accelerated the

movement of black workers from low-wage agricultural jobs, predominantly in the South, to higher

paying jobs in urban areas. Had there been no war,

this migration and the concomitant rise in black

wages might have been smaller during the 1940s and

greater during the 1950s. Also, the war interrupted

work careers and postponed schooling for many

men. Since a greater proportion of white than black

men participated in the war, the temporary interruption of skill development might have depressed the
earnings of whites and inflated the black-white

earnings ratio from its "true" level.' The fact that

the earnings of whites accelerated during the 1950s

may reflect a "catch up" following the disruption of

the war. Although the earnings of blacks did not rise

faster than the earnings of whites in the 1950s, they

did not decline as might be expected if the achievements of the 1940s had simply been a wartime

phenomenon.

The 1950s also underscore the point that earnings

ratios are measures of relative economic success and

do not necessarily reveal changes in absolute levels

of success. Although relative gains were negligible

during the 1950s, they were years of rapid gain in

real earnings for blacks as well as whites (see table

1.1). The opposite is observed in the 1970s when the

relative earnings of blacks increased, but only

because real white earnings barely increased at all,

and even fell among men aged 25-34. Black earnings

grew more slowly in the 1970s than in any other

decade, and the gains were negligible for men aged

25-34.

Is Black Earnings Growth a Statistical

Illusion?

One possible explanation for the narrowing of the

black-white earnings gap is that it is largely a

statistical artifact resulting from selective attrition

from the black labor force. As discussed in chapter

2, labor force participation has been falling in recent

decades among all groups of working-age men, but

especially among blacks. If those who leave the

work force have relatively low potential earnings,

the earnings of the remaining work force would rise

as low wage earners are siphoned off. In view of the

relatively large decline in black employment, this

effect is potentially greater for blacks than for

whites, which would cause an illusory narrowing of

the earnings gap. Empirical research suggests, however, that this bias cannot, in fact, account for most

of the growth in relative earnings of black males.°

Distinguishing Fluctuations and Trends

In analyzing data from the decennial censuses, the

question arises whether measured changes in ea.

ings from decade to decade are accurate indicators

of long term trends in labor market conditions or

instead reflect episodic business cycle conditions.

7 Tabulations from the public use sample of the 1950 census

slaw that in 1950 among 25-29 yearold men, 55 percent of

blacks and 77 percent of whites were veterans of World War II.

4....' 14

The distinction is important because the effects of

changes in business conditions on labor market

performance may not be the same for blacks as for

whites. Analyses by Walter Oi (1962) and others

indicate that workers with little schooling and

training are more likely to be laid off during cyclical

downturns than more highly educated and skilled

workers. As black workers are more often less

educated and less skilled than whites, employment

fluctuations are likely to be larger among blacks

than whites. Consequently, the annual earnings of

blacks can vary more than the earnings of whites

over the business cycle, and this would affect

relative earnings.

Figure 1.1 shows the pattern of unemployment

rates by year. Only the aggregate unemployment

rate for the total labor force is available for the years

from 1939 to 1947. Unemployment data by race and

sex are available starting in 1948 and are shown for

men in figure 1.2. The aggregate unemployment rate

series and the separate series by race follow the same

basic pattern during the 1948-1985 period. However, the pattern for black and white males differs in

two important respects. First, in every year the

black unemployment rate is substantially higher than

the white rate, and second, the gap tends to widen as

economic conditions worsen.

The years for which earnings are reported in the

decennial censuses fall in different stages in the

business cycle. (The years in question are the

calendar year preceding the ...ensus year. For example, the 1980 census contains earnings data for 1979.)

In 1939 unemployment had fallen from its Great

Depression peak but was still very high. Although

1949 was a recession year, it was mild compared to

the 1930s depression. Thns, a comparison of 1939

and 1949 partly reflects the Nation's emergence

from the depression.

By contrast, in 1969, which fell at the end of a

high growth period, unemployment was exceptionally low. Comparisons of data from 1969 and 1959,

when unemployment was relatively high, most

likely overstate true long term economic gains.

Comparisons of data from 1969 with 1979, when

unemployment was somewhat higher, most likely

reflect some weakening in the economy. Since the

level of unemployment was almost the same in 1949

The relevant research on this subject is discussed in chap. 7.

15
FIGURE 1.1

Civilian Unemployment Rate, 1939-1985

k

X

111 0-I

a. 2

usz

=

17.5

15.0

12.5

10.0

7.5

5.0

2.5

0.0

1935

, i , i

1940 19" 1950 1955 1960 1.,6 1970 1975 1980 1985

YEAR

c ` 5
FIGURE 1.2

Male Civilian Unemployment Rate by Race, 1948-1985

20.0-

17.5-

15.0-

7.5-

....*

I i

/

it

I ----I 1

it t \i

ii il ii ik, ,, /I \

i '

1kI,

1\ IN,,

.,

I' . *

IT\ g'. 1 / \

/ \

II ''-1 \ It1r , \ I

\ / . q

1 1 \

4 \ k I i

il i 4 11\

g

1.4

1

i \ / 7.., 1

st i \\j

\i\

/ -.4\ % ii /

\ i \ I

\

i -..

-,....../ 5.0-V

2.5-

y1 I 1 1 1 1 i 1 1 i 1945 1950 1955 1960 1965 1970 1975 1980 1985

YEAR

LEGEND: *--- WHITE 411-4 -ND BLACK 4-4-4- BLACK AND OTHERS

Source: The Employment and Training Report of the President, 1982.

Handbook of Labor Statistics, 1983. Bureau of Labor Statistics Data.
and 1959, comparisons of data from these years will

be relatively free of business cycle effects.

The unemployment patterns described above apply generally to both black and white men. However, it is apparent in figure 1.2 that the cyclical

swings are much more pronounced for blacks. Thus,

the decline in unemployment during the 1960s was

relatively sharp for blacks, while the series of

recessions in the 1970s elevated tile unemployment

of blacks more than of vhites, resulting in a

widening of the racial differential in unemployment.

Annual Changes in Relative Earnings

Differential patterns of employment notwithstanding, the large gains in the relative earnings of black

men do not appear to be an accident of the particular

years in which decennial censuses were taken.

Figure 1.3 traces relative earnings for each year

from 1948 to 1984. Relative earnings in this case are

measured by the ratio of the mean total income of

nonwhite men to that of white men, as reported in

the annual Current Population Surveys (CPS). Although Census and CPS data are not strictly

comparable, the basic decade by decade patterns

from the CPS are quite similar to those indicated by

the census data for the same periods

Figure 1.3 also shows the annual black-white

earnings ratios for those who were full-time yearround workers. This ratio is always higher than the

ratio calculated for all men (including those who

experience unemployment) because unemployment

rates are higher among blacks than whites. Moreover, during the 1970s and early 1980s the two ratios

diverged as the series for all men reflected the

dampening effect of rising black male unemployment.'°

Earnings Inequality

The difference in average earnings between black

and white men narrowed substantially during the

1940-1980 period. These statistics, however, do not

show if earnings gains have been experienced equally within the black male population. For example,

The concepts of income and earnings are not identical, and the

CPS sample includes other nonwhites together with blacks. In

addition, the CPS is a much smaller sample than the Census and is

much more likely to fluctuate due to sample variation.

2° That the relative economic gains of black males are relatively

free of influence from business cycles is also supported by a

comparison of annual and hourly earnings ratios derived from

census data. Hourly earnings ratios, free of cyclical changes in

hours and weeks worked, should exhibit a significantly different

18

2

low-wage black workers may have been "left behind."

Two aspects of black and white earnings distributions are examined here. First, the degree of earnings

variation, or inequality, is measured for each race.

Of particular interest is whether earnings inequality

changed significantly across decades, and if it did,

whether the patterns for blacks and whites are

similar or different.

Second, black-white differences in earnings are

-1 the income distribuings ratios are computexamined at different poir

tion. That is, black-white

ed for groups of workers naving the same relative

standing in terms of earnings within their respective

races. These comparisons '..:lp to characterize the

distribution of racial inequality among the working

population and to evaluate how uniformly earnings

gains by blacks have been distributed across economic strata.

Differences and Trends in Earnings

Inequality

When a group, such as blacks or whites, experiences earnings growth, it is very likely that some

members of the group gain more, and others less,

than the average. If an individual's gain is correlated

with his earnings level, the degree of inequality

within the group may increase or decrease. It will

decrease if those with lower earnings experience the

most rapid growth, and- it will increase if their

earnings grow at a slower rate than those of higher

earners. A widely used measure of dispersion, or

inequality, is the standard deviation of the natural

logarithm of earnings, which, roughly speaking,

indicates the average percentage by which earnings

differ from the mean earnings level. Calculations of

this statistic are presented in table 1.7 by race and

census year. With the exception of 1940, the table

shows that carnings inequality is greater among

blacks than among whites. Moreover, unlike the

trend in average earnings, there does not appear to

be any tendency for racial convergence in earnings

inequality.

pattern if such factors are important. Yet the series are very

similar (table I 6). This test is potentially flawed, however,

because hourly wages may themselves fluctuate cyclically

Nevertheless, most of the "cyclical effect" shows up in hours and

weeks worked. Moreover, the theoretical relationship between

the business cycle and hourly wages is ambiguous However, one

recent study by Bils (1985) finds a negative relationship between

unemployment and wages.
FIGURE 1.3

Nonwhite-White Male Income Ratios, 1948-1984

75-

72-

. 69-

66-

63-

60-

57-

54-

51-

/

/

,..-1

1

*

% 7 / t /

/ t /

f % I \ I A , % i )6 , , ,

.6.

... II u

*

I

4, A / . . *

/ V \I /

I

1 . I

1 li1/4 I

**-4

1

1I

/

/

1 1 I I 1945 1950 1955 1960 1965 1970 1975 1980 1985

YEAR

LEGEND: 4 ALL WORKERS 4.-4-* FULL-TIME, FULL-YEAR WORKERS

Source: Current Population Reports, Series P-60.

28
TABLE 1.7

Dispersion of Wage and Salary Earnings by Race

(standard deviation of the log of earnings)

Annual earnings Weekly earnings

Black White Difference

(black-white)

Black White Difference

(black-white)

1940 .826 .843 .017 .717 .700 .017

1950 .781 .720 .061 .663 .597 .066

1960 .871 .711 .160 .726 .581 .145

1970 .790 .688 .102 .695 .604 .091

1980 .929 .794 .135 .800 .691 .109

Note' Tabulations based on wages and salaries of male wage and salary workers ages 25-64 who worked in calendar year The self-employed and unpaid familyworkers are

excluded. Source: Census of Population, 19401980: Public Use Sample

The decade to decade changes in annual earnings

dispersion for blacks and whites are generally in the

same direction. For both races, earnings inequality

declined during the 1940s and 1960s and increased

during the 1970s. However, during the 1950s this

corresponde.:ce did not hold, as the earnings dispersion increased sharply for blacks and decreased

slightly for whites.

An important factor influencing the dispersion of

earnings is unemployment, which generally falls

more heavily on low-skilled, low-wage workers,

thereby increasing the degree of inequality. Weekly

earnings are less affected by unemployment and thus

less dispersed than annual earnings. Since blacks

typically experience more unemployment than

whites, the reduction in earnings dispersion going

from annual to weekly earnings is typically greater

for blacks than for whites.

Similarly, the decade to decade changes in earnings dispersion seem to be closely related to fluctuations in unemployment generated by the business

cycle. The substantial rise in earnings inequality

during the 1970s for both blacks and whites in part

reflects higher unemployment in 1979 than in 1969.

The greater relative increase in unemployment for

blacks than for whites helps explain the greater rise

in earnings inequality for blacks during the 1970s,

and in the 1950s as well.

The greater inequality in earnings among blacks

than whites could be due to racial differences in the

way schooling, region, and other factors are distrib20

uted within the two populations. For example,

educational levels may differ more widely among

blacks than whites, thereby contributing to racial

differences in earnings dispersion. Similarly, regional

differences in wage levels can induce dispersion of

earnings in the population as a whole.

It is difficult to adjust measures of earnings

inequality for all of the relevant characteristics. An

attempt to examine the effect of adjusting for two

characteristics is shown in table 1.8, which provides

measures of weekly earnings dispersion for blacks

and whites within detailed schooling groups and

separately for the South and the rest of the Nation.

The dispersion of earnings is usually lower within

the more homogeneous region-schooling groups

than it is overall, and this is the case for both blacks

and whites. The reduction is generally greater for

blacks, and as a result, the differential in the measure

of dispersion is considerably smaller within detailed

education-region groups. Even within the detailed

schooling and region groups, however, the dispersion in earnings generally remains greater for blacks

than for whites in 1960 and 1980, although the

reverse is true for 1940.

In the United States, as a whole, the black-white

differential in earnings inequality converged somewhat between 1960 and 1980, whereas the opposite

is true within regions and most region-education

groups. This indicates that factors (such as regional

developments) that may have been narrowing over-
TABLE 1.8

Dispersion of Weekly Earnings by Race, Education, and Region

(standard deviation of the log of earnings)

Region and years

of school

Non South

Blk.

1940

Wht. Diff. Blk.

1960

Wht. Diff.

1980

Blk. Wht. Diff.

0-7 601 .619 -.018 .661 .589 .072 .879 .793 .085

8-11 533 .619 -.086 .555 .499 .056 .804 .707 .098

12 572 .630 -.058 .527 .465 .062 .764 .619 .145

13-15 718 .661 .058 .508 .524 -.016 .684 .616 .068

16 525a .841 -.316 .416 .576 -.160 .641 .661 -.020

17+ 491b .891 -.400 .480 .630 -.150 .652 .684 -.033

All groups 580 .667 -.086 .586 .542 .044 .770 .677 .093

South

0-7 687 .749 -.063 .767 .715 .052 .828 .803 .025

8-11 599 .698 -.098 .662 .585 .077 .823 .731 .092

12 689 .668 .021 .541 .512 .028 .762 .639 .123

13-15 597 .705 -.108 .612 .579 .033 .742 .655 .087

16 626 .725 -.099 .614 .561 .053 .630 .652 -.022

17+ 859° .926 -.068 .468 .584 -.117 .741 .701 .041

All groups 689 .781 -.092 .741 .660 .081 .806 .717 .089

US.

All groups 717 .700 .017 .726 .581 .145 .800 .691 .109

efewer than 100 Observations bFewer than 50 observations Note Tabulations based on wages and saltines of male wage and salary workers ages 25-64 who worked in calendar year The self-employed and unpaid family workers are

excluded Source Census of Population, 19404980, Public Use Sample

21
all racial differences in inequality masked other

developments that were increasing inequality."

Changes in the composition of workers by age, more

detailed geographic areas, and industry are among

the possible causes of the pattern.

Relative Earnings Gains for High and

Low Earners

This section compares the earnings of blacks and

whites who hold the same relative earnings position

within their respective groups. For example, the

earnings of the black man who earns more income

than only 10 percent of his fellow blacks are

compared with the earnings of the white man who

earns more than only 10 percent of his fellow whites.

Matching of blacks and whites by earnings rank

provides a way to characterize the distribution of

racial earnings inequality in the working population.

The following questions are addressed: (1) How

does the black-white earnings ratio vary at different

points of the earnings distributione.g., at the 10th,

50th (the median), and 90th percentiles? (2) Has the

earnings ratio increased at the lowest percentiles as

much as it has at the middle or top percentiles?12

Figure 1.4 shows the black-white annual earnings

ratio at different percentiles of the income distribution between 1940 and 1980. In each year, except for

1940, the earnings ratios are considerably higher at

the higher percentiles than they are at the lower

percentiles. Another striking feature of figure 1.4 is

that the earnings ratio curves have shifted upward

over time. This shift indicates that blacks have

progressed, relative to whites, at each percentile of

the earnings distribution. This progress appears to

have been uneven because certain portions of the

curves have shifted up much more than others.

More precise measures of these patterns are reported

in table 1.9.

Examining the change over the entire 40-year

period reveals that relative black annual earnings at

or above the 25th percentile have increased by a

substantial and remarkably uniform amount. At the

10th percentile, however, relative black earnings

have grown very little. Thus, blacks at or above the

25th percentile have made rapid gains relative to

" The dispersion of earnings of both blacks and whites is

substantially greater in the South than in the non-South in 1940

and 1960. The greater concentration of blacks in the South, therefore, would have generated greater inequality for blacks

overall. In 1980 the regional effect was considerably smaller and

would not ha,e been a major factor causing greater inequality of

black earnings.

22

,. 1

whites over the period in terms of annual earnings,

while blacks at the very lowest end of the distribution appear to have progressed little.

This pattern varies from decade to decade, and

there is an indication that the business cycle is one

factor influencing the pattern. Thus, during the

1960s, the largest relative earnings gain was made by

blacks at the lower percentilesthe 10th and 25th.

The 1960s saw sharply falling unemployment, which

seems to have had disproportionately positive effects

on blacks with lower earnings. During the 1970s, the

situation was reversed. Unemployment rose, more

for blacks than for whites, which may explain why

relative earnings growth was lower (or even negative) for those at the lowest percentiles.

Black-white ratios of weekly rather than annual

earnings adjust partially for unemployment, since

they control for weeks worked. As shown in table

1.9, such ratios of weekly earnings reveal more

uniform changes from decade to decade at the

different percentiles than do the ratios of annual

earnings. In fact, between 1970 and 1980, the

adjustment for weeks seems to explain fully the poor

performance at the 10th percentile of the blackwhite ratio of annual earnings. On the other hand,

the pattern of declining ratios from 1950 to 1960

remains about the same whether annual or weekly

ratios are observed. Thus, although important, it is

unlikely that unemployment fluctuations are the

only explanation for the unevenness of progress

among percentiles over time.

In sum, this brief analysts shows that earnings are

generally more unequally distributed among blacks.

Related to this finding is the observation that the

ratio of black to white earnings is lower at the 10th

percentile than it is at the median or at higher

percentiles. Moreover, unlike trends in average

earnings, there does not appear to be any tendency

for convergence in racial differences in earnings

inequality.

Concluding Comments

This chapter has presented a broad overview of

trends in the earnings of black and white men.

Between 1940 and 1980 substantial progress was

" The pth percentile corresponds to the earnings level below

which p percent of the group is found For example, the 10th

percentile is the earnings level below which 10 percent of the

group (black or white) earns The 90th is a higher les el of

earnings, below which 90 percent of the group earns

TABLE 1.9

Change in Black-White Earnings Ratios for Men

(percentage point changes)

Annual earnings 10th 25th 50th 75th 90th

1940-50 + 4.5 +14.6 +18.0 +18.9 +12.5

1950-60 -12.5 4.1 1.0 0.7 0.1

1960-70 +13.3 +11.0 + 4.1 + 5.7 + 3.5

1970-80 1.4 + 3.8 + 6.0 + 7.4 +10.7

1940-60 8.0 +10.5 +17.0 +18.2 +12.4

1960-80 +11.9 +14.8 +10.1 +13.1 +14.2

1940-80 + 3.9 +25.3 +27.1 +31.3 +26.6

Weekly Earnings

1940-50 +11.9 +15.0 +18.3 +17.1 +16.5

1950-60 -11.5 5.8 3.3 1.5 + 0.8

1960-70 +11.8 +10.1 + 7.5 4- 0.8 0.7

1970-80 + 9.0 + 6.5 + 4.0 + 8.7 +11.0

1940-60 + 0.4 + 9.2 +15.0 +15.6 +17.3

1960-80 +20.8 +16.6 +11.5 + 9.5 +10.3

1940-80 +21.2 +25.8 +26.5 +25.1 +27.6

Note. Tabu leans based on wages and sakines of male wage and salary workers ages 25-64 who worked in cale-.dar year The self-employed and unpaidfamily worker's are excluded Source. Census of Population, 1940-4980. Public Use Sample

24
made in narrowing the black-white earnings gap.

The decade to decade pattern of convergence in the

earnings gap was uneven, and it did not always

parallel the underlying trend in the real earnings

growth of blacks. For example, although the 1950-

1960 decade was the only one studied in which black

earnings gains did not outpace those of whites, it

was also a period when the real earnings of the

average black male increased substantiallyby 3.4

percent a year. This increase just was not as rapid as

that of whites, for whom the fifties were the best

decade between 1940 and 1980. Conversely, racial

differences in earnings continued to narrow during

the 1970s, but this was a period of economic

stagnation, and the real earnings of black men

increased more slowly than in any other decade

examined. Only during the 1940s and the 1960s,

decades of strong economic growth, did blacks

experience substantial gains in earnings both in

relative and absolute terms.

There is no simple explanation for the substantial

rise in the relative earnings of blacks over the 1940-

1980 period. Although Federal civil rights policies

undoubtedly played a role, their effect was largely

confined to the 1960-1980 period. A complex set of

economic, political, and social forces was involved

in narrowing the black-white earnings differential.

Identifying and evaluating these forces is the primary objective of this report.

Although trends in earnings are typically analyzed

by examining the mean or median earnings, such

measures overlook potentially important differences

in the way earnings are distributed among blacks

and among whites. Consequently, the second part of

this chapter looks at the distribution of earnings

within each race and also examines the black-white

earnings ratio at different percentiles in the earnings

distribution. With the exception of 1940, black

earnings have been more unequally distributed than

white earnings. Black earnings inequality increased

relative to that of whites between 1940 and 1960, but

since 1960 there has been no clear trend in relative

inequality. The relatively high unemployment of

black men and the greater sensitivity of their

employment to the tusiness cycle explain some of

the difference in inequality between blacks and

whites as well as the pattern of this difference from

decade to decade.

When black-white earnings ratios are compared

for blacks and whites at the same percentile earnings

rank, racial differences are greatest among those

with low rank. At higher earnings percentiles, racial

differences are substantially smaller. During the

1940-1980 period, black-white earnings ratios generally rose at all percentiles. However, blacks at the

lowest percentile ranks did not keep pace during the

1970s due, in part, to rising unemployment rates,

which had a disproportionately large effect on

blacks with low earnings. 'The next chapter investigates patterns and trends in employment and unemployment in greater detail.

25
Chapter 2

Trends in Employment and Unemployment

The preceding chapter documented the great

economic progress made by black men between

1940 and 1980 as their earnings rose rapidly, substantially outpacing the gains made by whites. Yet, some

troubling signs were evident in the fact that the

black male unemployment rate remained considerably higher than the white rate.

This chapter focuses on racial differences in work

activity. It reports that a greater fraction of black

men than white men are not in the labor force and

that blacks generally work fewer hours and weeks

during a year. Furthermore, these disparities have

shown no sign of narrowing over the past four

decades. In light of the apparent earnings gains by

blacks during this period, the persistence of differences in work activity is surprising. Generally, when

earnings and employment opportunities improve,

individuals work more. The question then arises

whether particular changes in the economy actually

served to limit the employment opportunities of

black men or whether factors on the supply side (for

example, health or transfer payments) affected black

male work patterns.

z Members of the armed forces are counted among the employed

in all tabulations presented in the section. 2 There have been some changes in the wording of unemployment questions in the censuses over the decades. In the 1960-1980

surveys, for example, the survey sought information about

whether an individual looked for work in the previous 4 weeks.

In the 1940 and 1950 surveys, however, the job search reference

period was not explicitly defined. It is possible that respondents

inferred a one-week reference period due to the question's

position in a sequence that referred to work activities in the

previous week.

26

The discussion below examines several dimensions

of work activity, including labor force participation

rates, unemployment rates, and weeks and hours

worked by the working population.

Measures of Current Labor Force Status

As a rule, official labor force statistics classify

individuals as either employed, unemployed, or out

of the labor force. Employed persons are defined to

include individuals who were at work during the

week the survey was taken, regardless of the number

of hours worked.' Unemployed individuals are

defined to include persons not at work but actively

searching for a job.2 The labor force, in turn,

consists of persons who are either employed or

unemployed. Those who are neither at work nor

unemployed are considered to be out of the labor

force. This last group may have particular impairments making it difficult to work, or they may have

decided, given the type of jobs or pay available, that

their time is better spent in other activities such as

attending school, working in the home (not for pay),

or simply at leisure. The line between being unemployed and being out of the labor force is sometimes

In 1940 Census Bureau tr bulations counted persons working on

emergency public works projects among the unemployed. These

individuals are coded separately in available microdata and for

the purpose of current tabulations are counted as employed. This

maintains consistency with the treatment of workerc on government projects in later censuses and affects only about one percent

of the labor force More specifically, if workers on emergency

public works projects are counted as employed, the unemployment rate for males is 9.7 percent If they are counted as

unemployed, the overall rate for males is 10 8 percent
thin, since in periods of high unemployment some

workers, termed "discouraged workers," may stop

actively searching for work for a time because they

believe none is available; they would then be

counted as out of the labor force.

The concepts of labor force and unemployment

can be summarized in two basic measures of current

labor force status: the labor force participation rate,

which reflects the share of the population who are in

the labor force, and the unemployment rate, which

reflects the percentage of the labor force not

working.

Labor Force Participation

In 1940 there were only small racial differences in

labor force participation among working age men

(table 2.1). White male participation rates were

stable between 1940 and 1960 and inched down

between 1960 and 1980 for those aged 25-54.

Among older white workers, however, labor force

participation declined more significantly, falling by

nearly 20 percentage points for 60-64 year olds

between 1940 and 1980. This reflects the trend

toward early retirement.

Stronger and more pervasive downward trends

are observed for blacks, whose labor force participation rates declined in most decades and at all ages.

The declines were initially modest, but tended to

accelerate over successive decades. For example,

among black 35-44 year olds, the participation rate

fell 2 percentage points between 1940 and 1960 and

another 5.4 points by 1980. Similar to whites, the

declines in participation were largest among older

persons, falling nearly 29 percentage points over the

40-year period for 60-64 year-old black men.

As a result of these trends, racial differences in

labor force participation have increased substantially

over time. While the labor force participation rate of

black men ages 35-44 was 1.5 percentage points

below that of white men in 1940, the differential had

widened to almost 8 percentage points by 1980.

The decline in labor force participation has also

been concentrated among persons with less schooling (tables 2.2 and 2.3). Although both races exhibit

this pattern, the decline within education groups is

again more pronounced for blacks. Table 2.4 sumThe argument that automation was displacing workers and

causing "structural" unemployment was promoted by vilingsworth in the mid-1960s (see Killingsworth, 1965) but co,inteled

by other economists, who saw the problem of the day as lack of

aggregate demand (see Council of Economic Advisers, 1964). For

marizes these trends for the age groups 25-34 and

45-54 years.

Why, during a period of rising relative wages and

expanding civil rights programs would greater

numbers of men, particularly black men, withdraw

from the labor market? Various explanations for this

apparent paradox have been offered.

One argument is that the economy has been

generating fewer employment opportunities overall,

or for certain groups of workers, as a result of

changes in its industrial structure. These changes

have been attributed to forces such as automation or

foreign competition.3

Another hypothesis is that workers have been

induced to leave the labor force as a result of rising

benefits from activities other than work. It is argued

that during the past 40 years increasing numbers of

individuals have gained access to alternative sources

of income such as government transfer payments as

well as to illegal or "underground" activities. Clearly, when opportunities for obtaining nonmarket

income increase, the incentive to work in the market

is weakened, particularly among those whose work

prospects are poor to begin with. Thus, blacks,

whose earnings are more likely to be low, would be

affected more than whites. This section examines the

evidence for these different explanations.

Have Employment Opportunities Declined?

TI.- &cline in labor force participation described

above is sometimes attributed to shrinking employment opportunities. The emi:rical validity of this

hypothesis is questionable, however, in view of the

fact that the economy generated more jobs, not

fewer, over the period of labor force decline. In

1960, 54.9 percent of the population aged 16 and

over was employed, and this ratio rose to 56.1

percent in 1970 and 58.5 percent in 1980. This

increase, admittedly, was driven by a rise in the

proportion of women and teenagers who were

working. Thus, it is possible that the overall rise in

employment masked worsening opportunities for

men, resulting in their displacement from jobs. This

displacement would cause a decline in labor force

participation if unemployed workers eventually become so pessimistic about the prospect of finding a

a more recent discourse on the subject of job displacement caused

y "deindustrialization," Bluestone and Harrison (1982). But

see the analysis by Koster~ (1986) suggesting that the importance

of job displacement has been greatly exaggt rated

0

27
.41110.

TABLE 2.1

Male Civilian Labor Force Participation Rates by Race and Age

Race and age 1940 1950 1960 1970 1980

Blacks:

25-34 96.0 91.0 93.4 91.4 87.8

35-44 95.3 94.5 93.3 91.2 87.9

45-54 92.3 91.9 90.1 86.4 82.3

55-59 90.8 83.5 82.9 79.5 70.1

60-64 83.8 74.2 70.0 66.6 54.9

Total 93.9 91.2 89.9 86.7 82.5

Whites:

25-34 97.2 94.6 96.7 95.8 95.0

35-44 96.8 97.0 97.2 96.5 95.8

45-54 94.0 94.2 95.1 94.2 91.7

55-59 89.6 87.7 89.7 88.5 82.2

60-64 80.9 80.0 80,0 74.9 61.1

Total 94.4 93.6 94.3 92.8 90.0

Difference in participation (white minus black):

25-34 1.2 3.6 3.3 4.4 7.2

35-44 1.5 2.5 3.9 5.3 7.9

45-54 1.7 2.3 5.0 7.8 9.4

55.59 -1.2 4.2 6.8 9.0 12.1

60.64 -2.9 5.8 10.0 8.3 6.2

Total 0.5 2.4 4.4 6.1 7.5

Source: Census of Population. 1940-1980; Public Use Sample.

28
TABLE 2.2

Black Male Civilian Labor Force Participation Rates by Age and Education

Age and years of school 1940 1950 1960 1970 1980

25-34

0-11 yrs. 95.9 92.1 93.1 89.0 81.2

12-15 95.6 86.0 93.8 94.0 89.6

16+ 96.7 89.6* 95.5 91.3 92.7

35-44

0-11 95.3 94.6 92.5 89.4 82.3

12-15 95.6 93.4 95.7 93.6 90.7

16+ 96.9 95.6* 98.0 97.4 94.4

45-54

0-11 92.2 91.9 89.6 84.3 77.7

12-15 94.4 91.1 92.6 92.2 87.2

16+ 94.8 95.1 96.6 95.7 93.6

55-64

0-11 87.5 82.6 73.6 72.2 59.1

12-15 95.3 80.7' 87.1 81.0 71.8

16+ 89.1 92.9* 88.1 92.0 81.8

Ibtal

0-11 93.8 91.4 88.8 83.6 74.2

12-15 95.7 88.5 93.7 92.6 88.0

16+ 95.8 93.2 95.8 94.2 92.3

'Less than 100 obsorvetions per au.

Bourg: Census of Population, 1940.1980; Public UN Smpl.

29

18
TABLE Z3

White Male Civilian Labor Force Participation Rates by Age and Education

Age and years of school 1940 1950 1960 1970 1980

25.34

0-11 yrs 97.2 95.5 96.0 93.8 89.9

12-15 97.6 94.3 97.4 96.9 95.8

16+ 95.6 91.6 96.6 95.3 95.7

35-44

0-11 96.5 96.5 95.8 94.1 90.7

12-15 97.5 97.9 98.4 97.6 96.7

16+ 98.1 98.0 98.9 98.5 98.1

45-54

0-11 93.6 93.4 93.9 91.4 85.9

12-15 95.5 95.9 97.0 95.9 93.3

16+ 95.9 96.5 97.8 97.8 96.8

55-64

0-11 85.2 84.8 83.8 78.5 65.3

12-15 87.5 88.8 88.5 87.1 75.3

16+ 90.0 89.8 92.5 89.9 84.3

Total

0-11 93.8 92.8 92.2 88.5 80.8

12-15 96.2 95.0 96.7 95.4 92.1

16+ 95.7 94.3 97.1 96.1 95.1

Sauce Census of Population, 1940.1980 Petite use Sample

30
TABLE 2.4

Changes in Male Labor Force Participation Rates by `tears of School, Race, and Age

Ages 25-34

Black

1940-1960 1960-1980

0-11 yrs. -2.8 -11.9

12-15 yrs. -1.8 - 4.2

16+ yrs -1.2 2.8

Total -2.6 5.6

White

0-11 yrs. -1.2 6.1

12-15 yrs. -0.2 - 1.6

16+ yrs +1.0 0.9

Total -0.5 1.7

Ages 45-54

Black

0-11 yrs. -2.6 -11.9

12-15 yrs. -1.8 5.4

16+ yrs +1.8 3.0

Total -2.2 7.8

White

0-11 yrs. +0.3 - 8.0

12-15 yrs. +1.5 3.7

16+ yrs +1.9 1.0

Total +1.1 - 4.3

Sown Tables 21.22. and 23

31
job that they cease all job search activity and drop

out of the labor market.4

If steadily deteriorating job opportunities were

the major reason for declining labor force participation, an upward trend in the unemployment of black

men would be expected that roughly corresponded

to the upward trend in nonparticipation in the labor

force. In fact, figures 2.1 and 2.2 suggest that while

nonparticipation has trended upwards since the mid1950s, .unemployment rates have shown no such

corresponding pattern.

For instance, during the 1960s, the black rate of

unemployment fell sharply while the black rate of

nonparticipation continued to rise steadily. Further,

although unemployment increased in the 1970s,

labor force nonparticipation rose little after 1975 and

even leveled off during the early 1980s. The only

periods when the two series do move in the same

direction appear to be of short duration, corresponding to the ups and downs of cyclical fluctuations. In

sum, the evidence presented in figures 2.1 and 2.2

suggests that diminishing employment opportunities

are not likely to, have played a significant role in

generating the trends in labor force participation.

The Effects of Disability Transfers

In seeking causes of the decline in labor force

participation, several authors have focused on the

role of disability transfer programs such as social

security and supplemental security income.5 These

programs, it is argued, create incentives for the

disabled and elderly to reduce the amount that they

work. The availability of benefitsa nonwage

source of incomewould itself tend to discourage

work. Furthermore, the social security and SSI

disability programs effectively preclude work, since

an inability to perform significant work is a condition for program eligibility. Similarly, the social

security retirement program limits work through an

earnings test which restricts the amount that can be

earned without forfeiting benefits.

At its inception social security was a retirement

program for worker- aged 65 and over. Sin- ;e then

4 Surveys show that most displaced workers tic -it, find

jobs. For instance, despite the weaken& economy early

1980s 69 percent of workers displaced from jobs during tl 1979-

81 period were employed in January 1984, only 15 per nt quit

the labor force. See Kosters (1986).

Parsons (1980a, b) and Leonard (1979) have argued that

increased benefit levels and coverage in the social security

,usability program have reduced labor force participation, and

disproportionately more so for blacks For a different view, see

Haveman and Wolfe (1984).

32

the program has been greatly expa.ided. Coverage

for disabled workers was first extended in 1956 to

those aged 50-64 years, and in 1960 it was extended

to all ages. In 1961 partial benefits were made

avai: hle to able-bodied workers choosing to retire

early at ages 62-64. Rising benefits also contributed

to the expansion of the program. Thus, the annual

real benefit received by the average person rose by

5.2 percent from 1960 to 1965, by 14 percent from

1965 to 1970, and by 21 percent from 1970 to 1975

(table 2.5).

During the late 1960s and early 1970s, benefits

grew faster than earnings, and as a result, the

"replacement rate"the ratio of the worker's own

benefit (the "primary insurance amount") to past

earningsrose as well. For the worker with average

earnings, the replacement rate increased from about

33 percent in the 1960s to 51 percent in 1980. These

figures typically understate the true extent to which

benefits replace earnings, since benefits are no'

taxed, while earnings are subject to both income and

social security tax.6 Moreover, the primary benefit

is supplemented for workers with dependents. One

study of disability awards found that the average

benefit for workers with dependents replaced 75

percent of prior gross earnings and close to 100

percent of after-tax earnings.?

The social security system is more generous to

low-wage than to high-wage workers because benefits replace a decreasing share of earnings as earnings

rise. Owing to changes in the benefit structure,

replacement rates also rose much more among lowwage than high-wage earners. The social security

benefits for a disabled low-wage worker replaced 45

percent of earnings in 1960 and 64 percent in 1980.

Among high-wage earners, the replacement rate

only increased from 30 to 32.5 percent over the same

period. The introduction and growth of noncash

benefits, such as food stamps and medicaid, in the

late 1960s enabled those with low incomes to

supplement their benefits' As a result of these

factors, the pecuniary incentive to retire on social

security disability benefits is greater for low-wage

6 Since 1981 benefits have been subject to income taxation

These statistics refer to social security Lnefits awarded to

disabled workers in 1976 and are based on an unpublished study

of the Congressional Budget Office (April 1979).

" The March 1982 Current Population Survey found that among

the work disabled, 15 percent of whites and 47 percent of hl,cl.s

received food stamps and 16 percent of whites and 37 percent of

blacks were covered by medicaid
FIGURE 2.1

Rates of Civilian Unemployment and Labor Force Nonparticipation for Nonwhite Men

Ages 20 and Over, 1954-1985

25-

I 20-

1

t

15-

10-

5-

o=

r

.../ A.--sr

A''..... . ,...........-41

41--41/4 lit

.11e' .

lo--41

1950 1955 1960 1965 1970 1975 1980

YEAR

LEGEND: - UNEMPLOYMENT 4P-4.-. NONPARTICIPATION

Source: Economic Report of the President, 1982 and Bureau of Labor Statistics Data.

1985

42
FIGURE 2.2

Rates of Civilian Unemployment and Labor Force Nonparticipation for White Men Ages 20 and Over, 1954-1985

2G-.

VI 57

MI

.4' 41e- ...**".' ...*....4e

...oh' -41r- ..4e

.ir.

Ar...e" .al..4e"*...

.......4...-4/1

..4r

......-.4.- -41-.- 41--

0-

1950 1955 1960

LEGEND:

1 1965

YEAR

1 1970 1975 1980

4e UNEMPLOYMENT 1--41-411 NONPARTICIPATION

Source: Economic Report of the President and Bureau of Labor Statistics Data.

-,-,--r

1985
TABLE 2.5

Benefits and Replacement Rates in the Social Security Disability and Retirement

Programs

Year

Low

earner

Annual benefit'

Average Maximum

earner earner3

Replacement rate2

Low Average Maximum

earner earner earner's

1955 3,001 4,230 4,583 49.6 34.6 32.8

1960 3,286 4,507 4,583 45.0 33.3 29.8

1965 3,428 4,741 5,207 40.0 31.4 32.9

1970 3,804 5,410 6,098 42.7 34.3 29.2

1975 4,461 6,566 7,675 59.5 42.3 30.1

1980 4,865 7,390 9,375 64.0 51.1 32.5

1983 4,637 6,968 8,934 63.6 45.8 26.3

1984 4,344 6,523 8,461 62.3 42.8 23.7

1985 4,224 6,274 8,207 63.8 41.0 22.9

'The benefit is the pnmary insurance amount (PIA) in he year of entitlement The annual benefit is the sum of the monthly PIAc and is expressed in 1984 constant dollars

2The annual benefit expressed as a percentage of lings in the year prior to entitlement

3For the hypothetical worker who earned the i,oclal secunty maximum

Source US. Congress. House Committee on Ways and Means. 1985

earners than higi.-w7z,e earners, and the incentive

for low-wage earners grew larger after 1960.

Black men are likely to have greater incentives

than white men to retire early cn a disability pension

because of their lower earnings as well as their

higher incidence of disability. Surveys typically find

that blacks are more likely to be disabled than

whites.9 Moreover, mortality rates, which are

correlated with disability and are free of subjective

reporting, are more than twice as high for workingage blacks than for working-age whites.u) These

For example, the March 1982 Current Population Survey

found that about 21 percent of blacks aged 45-54 reported having

a disability that prevented them from working or limited the

work they could do, compared to I I percent among whites of the

same age (Current Population Reports. series P-23, no 127 )

Also see the Report of the Secretary's Task Force on Black and

Minority Health (U.S. Department of Health and Human Services).

'° In 1970 the mortality rate among men aged 35-44 was 2.8

findings are supported by the fact that black men

tend to work in blue - cellar occupations whereas

white men tend to work in sedentary white-collar

occupations." Not only is the risk of injury higher

in blue-collar jobs, but because more physical labor

is involved, a given injury will generally be more

debilitating.

It is not surprising, therefore, that black men of

working age are more likely to receive social

security benefits than whites. As shown in table 2.6,

the roportion of men receiving benefits has intimes as great for blacks as for whites, and for men 45-54, the

lack-white mortality ratio was 2 0. The mortality differential by

race has narrowed over time, however (U S Bureau of the

Census, Statistical Abstract of the United States. 1981, table 109.) " In 1970, for example, 61 percent Jf black men and 46 percent

of white men were employed in blue-collar occupations This

disparity has tended to narrow over time (Census of Population:

1970, Detailed Characteristics, Final Report PC(1)-D1 )

44

35
TABLE 2.6

Percentage of the Male Population Receiving Social Security Benefits by Age and Race

Year

Nonwhite men

25-34 35-44

Age group

45-54 55-59 60-64

1 950 0.0 0.0 0.0 0.0 0.0

1 960 0.2 0.3 1.3 3.3 6.6

1 964 0.3 1.3 2.9 6.1 27.1

1 969 1.8 2.1 4.2 8.0 26.8

1 972 2.2 2.5 5.2 10.0 29.9

1 976 3.6 3.3 6.8 1 2.9 37.5

1 980 1.8 3.2 6.8 1 2.8 37.7

1 983 1.6 2.9 5.6 11.3 39.0

White men

1 950 0.0 0.0 0.0 0.0 0.0

1 960 0.2 0.3 0.8 2.2 4.5

1 964 0.5 0.9 1.7 3.6 19.4

1 969 0.6 1.3 2.4 4.7 21.7

1 972 0.8 1.5 3.1 6.0 26.6

1 976 1.1 2.0 4.1 8.1 33.5

1980 1.0 2.0 4.2 8.3 35.0

1 983 0.9 1.8 3.5 7.3 36.6

Note: Beneficiaries are measurod at the end of the year and include all male old age and disability beneficianes Population estimates refer to the civilian resident populabon

Source. Woman, 1986.

creased for both blacks and whites, but by much

more for blacks at ages 25-59.12 Furthermore,

growth in social security recipience appears to be

closely linked to the decline in labor force participation. Among white men (table 2.7), the increase in

the number receiving social security potentially

accounts for all of the increase in the number out of

the labor force at some ages and for a substantial

share at other ages.13 Among black men, growth in

social security recipience could account for from

half to all of the labor force change at ages 35 and

over, although it does not appear to be an important

factor among young blacks, 25-34 years of age.

" Note that table 2.6 relates to nonwhite men. In vie.:, of the

large proportion of this group who are black, the text refers to

nonwhites as black.

The increase in social security recipients can exceed the

increase n nonworking men if some recipients would not have

36

Individuals who actually receive social security

disability benefits cannot do significant work if they

expect to remain in the program and are, therefore,

likely to be classified as out of the labor force.

However, the number of recipients understates, by a

large measure, the full effect of such programs on

labor force participation because it excludes individuals who quit the labor force with the expectation of

(and as a prerequisite to) qualifying for benefits. For

every recipient, there is an unsuccessful applicant

who will spend a considerable amount of time in the

application and appeal processes. Moreover, relatively more black men would be in this group

because a greater number of blacks have disabilities,

worked even without benefits Since the participation of thi:.

group is likely to have been quite high from the inception of these

programs, most of the increase in program participation after 1960

should represent individuals who would have been in the labor

force had benefits not been available.

4 5
TABLE 2.7

Wends in Nonparticipation in the Labor Force and SJcial Security Recipiency by Race

and Age

Change in share

of population out

of the labor

force, 1960-1980

(percentage

Race and age point change)

Black men'

Change in share of

population receiving

social security,

1960-1980

(percentage

point change)

Change in social

security recipients

as percent of

change in men out

of the labor force,

1960-1980

25-34 5.6 1.6 28.5

35-44 5.4 2.9 53.7

45-54 7.8 5.5 70.5

55-59 12.8 9.5 74.2

60-64 15.1 31.1 206.0

White men

25-34 1.7 0.8 47.1

35-44 1.4 1.7 121.4

45-54 3.4 3.4 100.0

55-59 7.5 6.1 81.3

60-64 18.9 30,5 161.4

Note: Social Security beneficiaries are csotntially recipients of disability pensions up to age 62, recipients ages 62-64 include recipients of old age pensions choosing theearly

retirement option.

'Social security data refer to nonwhite men. Source Tables 2.1 and 2 &

37

6
and among the disabled, a higher percentage of

blacks apply for benefits."

Another way of relating disability and labor force

activity is presented in figures 2.3 and 2.4. They

show, for each year since 1964, the percentage of

black men and white men who did not work during

the year, classified by the reason given by the men

for not working. The major reasons for not working

are disability, retirement, and a perceived lack of

employment opportunities ("discouraged workers").

Figure 2.3 shows the rapid rise since 1964 in the

proportion of black men aged 25-64 who did not

work at all during an entire ,ear. It is apparent that

the primary factor underlying this trend through the

1960s and into the mid-1970s is the rising proportion

of men who reported not working because of a disability. In 1964, 4 percent of black men (ages 25-

64) did not work due to disability; by 1975 this

proportion had risen to 10.3 percent (11.5 percent

including retirees). Significantly, this was a period

when social security benefit levels increased and

eligibility standards were relaxed.13

Starting in the late 1970s, a series of actions was

taken to slow program growth. These actions appear

to have met with some success as accessions to the

program declined. This is reflected in a leveling off

and then a decline in the rate of nonparticipation for

reason of disability. The patterns in figure 2.3 also

show that discouraged workersthose who cite

inability to find work as a reason for nonparticipationplayed a very minor role until the recessions

of 1975 and 1982.'6

" The initial application process involves a 5-month waiting

penod during which time any substantial work activity would

jeopardize the claim.

In 1981, 70 percent of initial claims were denied, 49 percent of

those denied appealed to the State-level agency, State agencies

denied 87 percent; 68 percent of these denials appealed to an

administrate law judge; of these 58 percent were allowed and 42

percent denied; and so on through to the U.S district court In

earlier years initial denial rates were closer to 50 percent.

(Committee on Ways and Means, 1982, table 4).

Data tabulated by Halpern and Hausman (1985) from the 1972

Survey of Disabled and Non-Disabled Adults (matched with

social security records) show that 54 percent of disabled black

men had ever applied for disability benefits compared to 37

percent of white men Of the applicants, approximately the same

proportion of black and white men were eventually awarded

benefits (57 percent) Hos ever, because of their largerproportion

of applicants, the black male population would likely have larger

proportions of individuals without work activity involved in

applying and reapplying for benefits

" During this period the administration of the program accepted

an increasing number of applicants who did not meet the strict

medical definition of a severe disability but who met nonmedical

38

i

The broad pattern shown in figure 2.4 for white

men is similar to that of black men, although the

level and rise in the proportion out of the labor force

are considerably smaller for whites. Early retirement

is a relatively more important reason for labor force

withdrawal among white men than it is among

blacks, because the rise in white labor force withdrawal is more concentrated among older men (60-

64).

In sum, the data presented here and in other

studies support the hypothesis that the decline in

labor force participation among men ages 45-64 is

due in large measure to the expansion in Federal

disability programs and, for those aged 62-64, to

early retirement under social security." 38

A final cautionary comment pertains to judgments

that may be formed about the relation between work

and disability and retirement transfers. To observe

that a r. gram has reduced labor force participation

is not i zessarily a condemnation of the program.

Some i dividuals, including disabled individuals,

who otherwise would have been productive workers may have been induced by transfers to withdraw

from the labor force. However, transfers also may

have enabled many disabled workers to retire who

otherwise would have further impaired their health

by continuing to work. A full evaluation if the

effects of transfer programs would require a detailed

analysis of the health benefits associated with early

retirement, a study beyond the scope of this report.

standards such as inability to perform one's usual work (U.S

Congress, House of Representatives, Committee on Ways and

Means, 1985).

" The proportion of the population who cite inability to find

wok,. as a reason for nonparticipation (discouraged workers) can

be seen in figures 2.3 and 2.4 as the area between the line showing

the percentage "Disabled, Retired or Discouraged Worker" and

the line showing the percentage "Retired or Disabled Worker."

Discouraged workers averaged only 0 5 percent of the population

among b:ack men ages 25-64 in the period 1964-1973, but rose to

3 percent of the population in 1975, subsided to 1.3 percent in

1978, and then shot up to 6.8 percent in the 1982 recession. 17 As noted, see Parsons (1980a, I980b), and Leonard (1979) and

for criticism of Parsons, see Haveman and Wolfe (1984) For a

recent anal) sis which shows that rising levels of disability benefits

have a strong effect on benefit applications and, thus, on work

participation, see Halpern and Hausman (1985)

" The argument that transfer programs have caused falling labor

force participation rates does not apply, of course, to the 1940s

Yet, participation rates generally fell during tlii decade, especially among older black men A likely cause for this trend was the

shift of employment out of agriculture towards manufactui ing

employment and from rural to urban residence

47
FIGURE 2.3

Black Men Ages 25-64 Not at Work in Previous Year by Reason

22.5-

20.0-

17.5-

12.5-

7.5-

S.0-

2.5-

/6\

frN

"-

rer

eI

14

.e°

1960

LEGEND:

Source: Current Population Survey Data.

1966 1970 1975 1980

YEAR

a S * ALL REASONS f -- DISABLED

*-4,-* DISABLED, RETIRED OR NO WORK +-4-- RETIRED OR DISABLED

1985
FIGURE 2.4

White Males 25-64 Not at Work in Previous Year by Reason

22.5

20.0

17.5

15.0

12.5

10.0

7.5

5.0

2.5

0.0

1960

LEGEND:

"Or=.4.004

311- -

Source: Current Population Survey Data.

1965 1970

YEAR

* ALL REASONS

1975 1980

-* DISABLED

1S-6-4: DISABLED, RETIRED OR NO WORK 4 -+ -I. RETIRED OR DISABLED

1985
TABLE 2.8

Male Unemployment Rates by Race and Age

Black

1940 1950 1960 1970 1980

25-34 10.0 7.3 7.9 4.6 11.3

35-44 9.7 6.4 7.9 4.2 8.1

45-54 9.0 4.9 7.0 4.0 7.5

55-64 9.2 6.5 8.2 3.9 5.1

Total 9.6 6.4 7.8 4.2 9.0

White

25-34 7.7 3.5 3.7 2.8 5.6

35-44 6.5 3.0 3.2 2.3 3.7

45-54 7.4 3.3 3.8 2.4 3.5

55-64 9.6 4.2 4.7 2.9 3.8

Total 7.6 3.4 3.7 2.6 4.4

Black relative to white unemployment rate

RaVo 1.3 1.9 2.1 1.6 2.0

Difference 2.0 3.0 4.1 1.6 4.6

Note Unemployment as a percentage of the civilian labor force

Source Census of Population. 19401980. Public Use Sample

Declining Work Participation at Younger Ages

The increase in social security beneficiaries seems

to account for little of the decline in labor force

participation among young men, ages 25-34 (table

2.7). Participation did not fall as much at these ages

as it did at older ages, but the decline is noticeable

nonetheless, particularly among men who have not

graduated from high school (tables 2.3 and 2.4).

Between 1960 and 1980, the participation rate for

black men with less than a high school education fell

from 93.1 to 81.2 percent; for white men of the same

age and education, the decline was from 96 to 89.9

percent. Although a co reprehensive analysis is beyond the scope of this report, several forces can be

noted that may have contributed to the decline in

labor force participation among younger men.

19 Annual data from the CPS show that the labor force

participation rate of nonwhite men ages 25-34 declined from 95 7

percent in 1965 to 94 4 percent in 1969, and from 93 7 percent in

1970 to 91.7 percent in 1973, declining not quite a percentage

point to 909 percent in 1980. (The figure for 1980 refers to blacks

only, for 1973 the black-only figure is 91 8, but only data for all

nonwhites are available before 1972 ) The pattern of unemployment for this group, however, was a decline from a rate of 6 2

One possibility is that forces in the economy

reduced employment opportunities for younger

men. Unemployment rates for men 25 -34 did rise

between 1970 and 1980, and particularly sharply for

blacks (see table 2.8). Unemployment, however, is

not likely to have influenced the decline in participation during the 1960s, since this was a period of

declining unemployment and of rapid economic;

growth generally. Moreover, more detailed examination of the 1970s using annual data from the

Current Population Survey (CPS) shows that the

decline in force participation among black men

25-34 was largely concentrated in the years 1970-73

which were still a period of relatively low unemployment.'9

Several other developments are likely to be

associated with declining labor force participation

percent in 1965 to 3 4 percent in 1969 (which is not consisr-nt

with the declining participation), and a rise in unemployment ti

6 1 percent in 1970 (which is consistent with declining participation) Unemployment remained at roughly the 1970 level until

1973 and then fluctuated up and down around a much higher

level between 1974 and 1980. when it reached 13 4 percent Yet

the decline in labor force participation was more modest during

this high unemployment period.

41
among younger men and particularly black men.

Increased criminal involvement, declining marriage

rates, and increased levels of transfer payments are

among these factors. In each case, declining labor

force attachment may be a cause as well as a result

of the development.

Blacks are disproportionately involved in crime,

and their involvement seems to have increased. In

1960 blacks were 34.3 percent of all prison admissions; by 1980 their share had risen to 42.7.2° Census

data show that the proportion incarcerated among

black men ages 25-34 rose from 3.5 percent in 1970

to 4.2 percent in 1980, while the white male

proportion remained the same at only 0.6 percent.

Although the prison population is itself excluded

from our calculations of labor force participation,

criminal activity and imprisonments could have a

significant effect on the labor force statistics in

several ways. The proportion of blacks out of prison

who are involved in crime is considerably larger

than the prison population. Alfred Blumstein and

Elizabeth Grady (1981-1982) estimate that the cumulative lifetime probability of at least one arrest for

a felony is 51 percent among black men living in

large metropolitan areas compared to a cumulative

probability of 14 percent for white men in the same

cities. Arrests, trials, and the like would certainly

interrupt employment; and those who have been in

prison must surely experience increased difficulty in

finding employment when they are released. It is not

really known how active offenders would report

their labor force status to the census or if they are

less likely to be counted at all.

Another trend that may be related to the dec-line

in labor force attachment among younger men, and

blacks in particular, is the decline in marriage.

Between 1970 and 1980, the proportion of married

men ages 25-34 declined from 82 to 69 percent for

whites and from 74 to 56 percent for blacks (see

20 See Langan (1985) for these statistics (table 1). Also note that

the available evidence suggests that the high proportion of blacks

appearing in arrest and prison data appears to be explained by

disproportionate involvement in criminal activity rather than by

racial differences in the administration of justice See Langan on

this point; also Blumstein (1982). 2, In 1970, among 25-34 year-olds, 95 percent of married black

men were in the labor force, compared to 73 percent of single

men For white men these proportions were 98 percent and 83

percent. (Statistics are from the 1970 Census of Population.)

22 See J. O'Neill (1983). The earnings of white women did not

rise significantly over this period relative to those of white men. 23 For a discussion of the relation between women's work,

marriage, and divorce, see Becker, Landes and Michael (1977).

42

chapter 5). Married men typically have much higher

rates of labor force participation than single men.

Therefore, the decline in marriage rates may have

led to reduced labor force participation overall."

The increasing labor force participation and career commitment of young women during this

period may have been a causal factor for delayed

marriages among both blacks and whites. Additionally, the earnings of black women have increased

sharply, rising from 65 percent of black male

earnings in 1966 to 79 percent in 1980.22 This may

have been a destabilizing factor for marriages."

From 1965 to about 1973, rising welfare payments

and a large increase in participation in the aid to

families with dependent children program may have

also contributed to a lower propensity for women to

marry." It is also possible that causality goes the

other way; i.e., that the decline in labor force

participation led to the decline in marriage. Thus,

labor force participation, marriage rates, and possibly criminal activity may interact with each other;

and these relations are likely to be complex.

A final possibility stems from the fact that benefits, such as food stamps, did not exist until the late

1960s. Although food stamps are unlikely by themselves to induce an individual not to work, nonetheless, they are available as supplements to unemployment compensation (or to unreported criminal or

underground activity) and therefore, may enable

individuals to be out of work longer and more

frequently.25

In sum, the decline in labor force participation

among younger black men was not as great as for

older men. The possible explanations for the decline

are complicated, and the issue is by no means

resolved. It is an important issue, however, because

extended periods out of the labor force at younger

ages are likely to have negative effects on earnings

opportunities at older ages.

24 See J. O'Neill (1986).

24 Tabulations from the microdata file of the March 1980 Current

Population Survey show that among black men ages 25-44 who

worked less than 27 weeks in 1979, the following percentages

received particular transfers. food stamps (26 percent); SSI (6

percent); social security (10 percent); welfare (10 percent);

unemployment compensation, veteran benefits, or worker's compensation (24 percent). These percentages are similar for white

males of the same age and work experience, with the exception of

food stamps and welfare, for which whites have lower recipience

rates. These percentages, it should be noted, are underestimates.

Based on a comparison with program data, actual food stamp

receipt, for example, is about 30 percent higher than the selfreported data show.
Unemployment

Racial differences in unemployment, like racial

differences in labor force participation, have tended

to widen between 1940 and 1980. As indicated in

table 2.8, blacks consistently have had higher rates

of unemployment than whites, and this gap has

grown over time. In 1940 blacks were 30 percent

more likely than whites to be unemployed; by 1980

they were more than twice as likely to be unemployed.

The forces generating trends in unemployment

appear to differ from those generating trends in

labor force participation. Most of the increase in the

unemployment gap occurred between 1940 and

1960, whereas a substantial increase in black-white

differences in labor force participation occurred

between 1960 and 1980.

Causes of Unemployment

To examine more precisely the black-white gap in

unemployment, table 2.9 presents unemployment

rates classified by level of education and region of

residence. One of the strongest patterns emerging

from the table is that more highly educated individuals are not as likely to be unemployed as less

educated individuals. Education is associated with

lower unemployment, in part, because firms tend to

make larger investments in skilled workers (in the

form of hiring costs and traini ;*g) and would,

therefore, be reluctant to lose them through layoffs.26 Since blacks, on average, have less education

than whites, it follows that racial differences in

education are a contributing factor to racial differences in unemployment. Nevertheless, education is

clearly not the only factor creating the racial gap in

unemployment. Even within groups narrowly defined by education, blacks still have higher rates of

unemployment.

Another strong pattern emerging from the table is

that unemployment is substantially lower in the

South than in the rest of the country. Since blacks

are more likely to live in the South than whites,

racial differences in region of residence should serve

to reduce the black-white gap in unemployment.

Even when comparing individuals who reside in the

same region, however, blacks still have higher rates

of unemployment.

Marital staPis and typ, of industry or occupation

are other factors that 'night contribute to racial

" See Becker (1964) and 01(1962)

differences in unemployment. To explore this possibility, table 2.10 shows black-white differences in

unemployment in 1980 adjusting for age, education,

marital status, and industry and occupation of

employment. In both the South and non-South,

adjusting for marital status reduces the black-white

gap in unemployment (row 3).27 Adding an adjustment for industry and occupation of employment

further reduces racial differences in unemployment

(row 4), indicating that blacks are more likely than

whites to work in industries and occupations with

high unemployment. The effect of industry and

occupation of employment on the black-white gap in

unemployment may reflect racial differences in skill.

However, it also may reflect discriminatory practices that prevent blacks from freely entering certain

industries and occupations.

A simple discrimination argument alone does not

explain the patterns observed it tables 2.9 and 2.10.

The unemployment differential in the South is

usually quite small even before adjusting for various

characteristics, and at least in 1980, after adjusting

for other characteristics, it becomes statistically

insignificant from zero (table 2 10). Moreover, unlike the gap in wages, the black-white unemployment differential in the South is much smaller than it

is elsewhere. This is especially true in the decades

from 1940 to 1960. Yet, in this period, the South was

highly segregated, and it is widely believed that

discrimination was more deeply rooted there than in

the rest of the country.

Nevertheless, it is possible that discrimination

contributes to the black-white gap in unemployment.

As chapter 3 explains, in a competitive economy

with flexible wages, discrimination is likely to drive

a wedge between black and white wages. This wage

differential might influence even prejudiced employers to hire blacks. However, H....ry Gilman (1965)

points out that, "if there are legal or quasi-legal

pressures towards nonwhite-white wage equality,

discrimination may take the form of reducing the

employment opportunities of nonwhite relative to

white workers. Thus, we would expect a greater

effect of such factors as statutory and union minimum wages on the employment opportunities of

nonwhite than of white workers; employment opportunities should fall more for nonwhite than for

white workers."

" See the discussion of marital status in chap.

43
TABLE 2.9

Male Unemployment Rates by Race, Education, and Region

1940 1950 1960 1970 1980

Black

Less than 12 years

Non-South 17.0 10.3 10.7 5.7 14.9

South 7.1 4.6 6.8 3.9 8.6

12 years or more

Non-South 12.6 5.6 5.9 3.8 9.4

South E.0 3.3 3.9 2.4 5.6

Total 9.6 6.4 7.8 4.2 9.0

White

Less than 12 years

Non-South 9.5 4.7 5.5 4.2 8.4

South 5.9 3.0 4.9 2.8 5.6

12 years or more

Non-South 5.2 2.3 2.1 2.0 4.0

South 3.3 1.6 1.6 1.3 2.3

Total 7.6 3.4 3.7 2.6 4.4

Difference (black minus white)

Less than 12 years

Non-South 7.5 5.6 5.2 1.5 6.5

South 1.2 1.6 1.9 1.1 3.0

12 years or more

Non-South 7.4 3.3 3.8 1.8 5.4

South 1.7 1.7 2.3 1.1 3.3

Total 2.0 3.0 4.1 1.6 4.6

Ratio (black divided by white)

Less than 12 years

Non-South 1.8 2.2 1.9 1.4 1.8

South 1.2 1.5 1.4 1.4 1.5

12 years or more

Non-South 2.4 2.4 2.8 1.9 2.3

South 1.5 2.1 2.4 1.8 2.4

Total 1.3 1.8 2.1 1.6 2.0

Notes Ages 2564

Source Census of Population. 1940.1980, Pubic Use Sample

r

tl 3
TABLE 2.10

Accounting for the Black-White Gap in Unemployment of Men Ages 25-64, 1980

Unemployment gap South Non-South

(1) Unadjusted 3.3 6.6

(2) Adjusted for: education, age 1.9 5.2

(3) Adjusted for: (2) + marital status 1.2 4.2

(4) Adjusted for: (3) + industry and occupation 0.5" 3.2

Percent of gap explained by characteristics 85% 52%

Note. Estimates are based on a knear probability model of the determinants of unemployment The sample consists of persons currently in the labor force. and robs 24 measure

the effect on the unemployment gap resulting from the addition of the vanables indicated m the table

Stack rats of unemployment minus the white rate of unemployment

Not Statistically different from Zero at the 95 percent confidence level

45

r"
A key factor in explaining regional differences in

unempluyment is whether wages are more flexible in

the South than elsewhere. In fact, unionization,

which typically reduces wage flexibility, has always

been lower in the South.28 Moreover, until the late

1960s, the South had a smaller proportion of

employment covered by the minimum wage, and

enforcement also seems to have been weaker in the

South." Thus, discrimination outside the South may

surface in racial differences in unemployment,

whereas discrimination in the South may be reflected in racial differences in wages.

This is one of several nossibilities. Many factors in

addition to or in conjunction with, discrimination

could also be producin3 these patterns in unemployment, and more re, ^ch is needed to identify the

causes of the black-white gap in unemployment.

Trends in Unemployment

As previously noted, the black-white gap in

unemployment increased substantially between 1940

and 1980, with the primary increase occurring

between 1940-1960. Part of the reason for this

pattern may be due to the effects of migration.

Chapter 5 details the large-scale migration of blacks

from the rural South to the urban North between

1940 and 1960. Newcomers in an area tend to have

higher unemployment rates than long term residents.

Consequent. y, migration itself would have generated unemployment among newly arrived blacks. In

addition, the compositional shift of blacks towards

the North, where unemployment is greater, would

have t nded to increase the overall black-white gap

in unemployment. (Within the South, migration also

occurred from rural to urban areas, which might

explain why the black-white gap in unemployment

increased moderately there.)

Nevertheless, migration cannot explain all of the

observed patterns. Between 1940 and 1980, blackwhite differences in educational attainment and

occupational status narrowed dramatically, which

" See Gilman (196.5), p 1092

" Gilman (1965) footnote p. 1092. 3° Blacks hold different occupations than whites with the same

age and education, but the difference has narrowed over time. We

have computed indices of oc':upational dissimilarity which

measure the percentage blacks that would have to change

occupations to make the distribution of blacks across occupations

the same as that of whites A value of zero would indicate that

blacks and whites have identical occupational distributions, a

value of 100 percent indicates total racial separation by occupation. Between 1960 and 1980 these indices changed as follows

46

should have contributed to a reduction in the

unemployment gap. For the 1940-1960 period, the

effects of migration may simply have overwhelmed

advancements in education and occupation. For the

1960-1980 period, however, migration was much

smaller, and blacks continued to register impressive

gains relative to whites in educational attainment

and occupational status; yet, there was no systematic

narrowing of the unemployment gap over the

period."

Thus, the constancy of the black-white gap in

unemployment between 1960 and 1980 remains a

puzzle. It may :,-impiy reflect changes in various

factors that offset the improvements in black educational attainment and occupational status. For example, the generally higher level of transfer payments

in the 1970s, downward trends in rates of marriage,

and increases in the rate of crime may have contributed to the increase in the unemployment gap,

though a case could be made that the cause-effect

relations go the other way. Possibly, cyclical factors

played a role, since the overall level of unemployment was somewhat higher in 1980 than in 1960.

Additionally, as discussed in chapter 7, enforcement

of civil rights laws may have increased black

earnings as well as reduce , overall black employment. These are just conjectures, however. Blackwhite differences in unemployment are not well

understood, and further research is clearly required.

Weeks and Hours of Work

Lower labor market participation and higher

unemployment rates among blacks mean that the

average black is employed for less time during the

year than the average white. This accounts for part

of the black-white gap in annual earnings.

Census data for 1950 through 1980 report the

number of hours worked by each person during the

week in which the survey was taken and the number

of weeks worked during the previous calendar year.

Based on these data, table 2.11 presents average

Index of Oa upatninal Dicsandarar

Lducatron 1960 1980 Men 25-39

0-11 )rs 1.70 306

12.15 451 298

16+ yrs 47 I 27 8

All groups 44 0 331
TABLE 2.11

Weeks and Hours Worked for Men by Race and Age

Black

1950 1960

Mean weeks per year'

1970 1980

25-34 40.3 44.5 47.4 44.1

35-44 44.2 45.0 47.7 46.7

45-54 44.1 44.4 47.4 46.8

55-64 42.6 43.0 46.4 46.2

Total 43.6 44.4 47.3 45.9

White

25-34 45.9 47.6 48.7 47.3

35-44 47.1 48.4 49.5 48.8

45-54 46.2 47.6 49.1 48.9

55-64 45.0 46.1 47.5 47.0

Total 46.2 47.6 48.8 47.9

Mean hours worked per week2

Black

25-34 41.8 40.6 40.2 40.0

35-44 43.2 41.0 40.8 41.1

45-54 43.4 40.6 40.4 40.7

55-64 43.3 39.8 39.4 39.8

Total 42.8 40.6 40.3 40.4

White

25-34 44.6 44.0 43.3 43.5

35-44 46.0 45.3 44.8 45.2

45-54 45.7 44.8 44.1 44.5

55-64 44.6 43.2 42.6 42.7

Total 45.3 44.5 43.0 44.0

I Weeks worked refer to male workers who worked during the preceding calendar year

2 HourS worked refer to hours worked by mateworkers at work dunng the week of the census survey

Source Census of Population. 1940-1980, Public Use Sample

47
weeks and average hours for people who worked in

the previous year. The table shows that blacks work

fewer weeks and fewer hours per week than whites.

In 1950 white men (who worked) were employed

2.6 weeks per year more than blacks. Between 1950

and 1970, weeks worked rose for both groups, but

more among blacks; and the racial differential in

weeks worked fell to 1.5. Between 1970 and 1980,

however, weeks worked fell for both blacks and

whites by about one week.

Similarly, white men tend to work more hours per

week than ola, ' men, and this differential has been

stable at about 3 to 4 hours over the past 30 years.

Hours worked per week fell between 1950 and 1960

among both races but have since remained steady.

Estimates of annual hours of work, a broader

measure of work activity, can be calculated by

multiplying average weeks and hours per week.

Such estimates indicate that black men ages 25-64

worked on average from 10 to 17 percent fewer

hours annually than white men. In 1980, for example, black men worked 14 percent fewer hours than

white men, a difference of about 250 hours. This

implies that adjusting for differences in hours

worked would raise the annual earnings of blacks by

14 percent, which would eliminate roughly one third

of the gap in relative earnings (see table 1.2). The

same calculations for other years and specific age

groups reveal basically the same result: that racial

differences in annual hours of work account for an

important share of the overall differential in annual

earnings.

Since the earnings gap is smaller when based on

hourly or weekly earnings than on annual earnings,

the question arises whether one measure is more or

less appropriate than another for analyzing blackwhite earnings differences and for drawing inferences about the extent to which discrimination may

affect the differences. The answer depends on the

reasons for the racial differential in weeks and hours

worked. As noted in the discussion of unemployment, in free and unrestricted markets discrimination

could affect hourly pay rates rather than employment. The presence of wage rigidities, however,

such as equal pay laws or wage floors mandated by

" Wage rigidities would also increase unemployment among

those blacks or whites whose product's ity had a lower value to

the employer than the regulated wage in practice, it could be

difficult to distinguish the two situations due to imperfect

measures of worker productivity " It should he noted, however, that hours worked are not likely

48

union arrangements, would prevent employers from

discriminating against blacks in the form of lower

pay in many situations; but discrimination might

then emerge as higher unemployment for blacks.3'

Discrimination may also influence employment indirectly through occupation or training.

If wage rigidities were pervasive, it would be

appropriate to use annual wage ratios to compare

the earnings of blacks and whites because discrimination in this case is more likely to affect weeks

worked than hourly pay rates. On the other hand, if

markets were relatively free of rigidities, the hourly

wage rate would, in principle, be the most accurate

measure because it is not affected by differences in

the amount of time worked. In many circumstances,

hours worked reflect voluntary decisions about the

amount of time the individual wishes to work.

To take account of both possibilities, this report

examines annual earnings ratios as well as weekly or

hourly wage ratios.32 When only one measure is

considered, it is usually weekly earnings ratios.

Summary

In 1940 labor force participation rates of black

men and white men were approximately the same.

Over the ,.ext four decades, participation declined

among all men, particularly o'ider meli and those

with less than 12 years of schooling. The decline in

labor force participation was considerably greater

for blacks than for whites, even with schooling and

age held constant. For example, between 1950 and

1980, the decline in labor force participation rates

among men aged 45-54 with 0-11 years of school

was 14.2 percentage points for blacks and 7.5

percentage points for whites.

Much of the decline in the labor force participation of both black and white men aged 45-64 is

attributed to the liberalization and rising benefit

level in Federal disability and retirement p, grams

(supplemented by food stamp, medical, and other

benefits). The relatively greater decline among black

men can be traced to their higher incidence of

disability and their lower iocomes, and to the fact

that transfers are relatively more generous at lower

income levels.

to be as well measured as weeks worked flours Mist: usually been

measured in the census survey week in the spring However,

weeks worked and taming% refer to the previous calendar year

Hours worked per seek during the calendar year may have

averaged to differert numbers than hours during the stirs ey week.

thus producing a possible bias
The decline in labor force participation among

younger men (ages 25-34) was not as great as for

older men. Possible explanations for it include

increased criminal involvement, declining marriage

rates, and the introduction of transfers such as food

stamps. These factors may interact in a complicated

way, and the issue is by no means resolved.

A significant racial differential in unemployment

has persisted over the decades. This differential can

be partly attributed to schooling differences. However, black male unemployment rates exceed those

of whites within schooling and regional categories.

The differential in unemployment has always been

much larger in the North than in the South. This

was especially true in the period 1940-1960, despite

the apparently greater level of discrimination against

blacks in the South during the period. One reason

for the relatively low black unemployment late in

the South was the relative absence of unionization or

other pressures to equalize pay. As a result, discrimination may have been reflected in the form of lower

pay rather than unemployment differentials. The

widening of the black-white gap in unemployment

over the 1940-1980 period remains puzzling in light

of the convergerce in racial differences in schooling

and in occupations.

Levels of work activit; over the year are lower

among blacks because those who work are employed fewer weeks per year and fewer hours per

week. Because of these differences in time worked,

the earnings gap is smaller when based on weekly or

hourly earnings than on annual earnings.

49
PART II

Sources of the Earnings Gap, 1940-1980

The earnings gap between black and white men

clearly requires an explanation. One obvious possibility is labor market discrimination. Another is

differences in skills or in other characteristics known

to affect earnings. Although the acquisition of skills

may be affected by discrimination in the labor

market (e.g., in the provision of training) and by past

discrimination by government (e.g., in the provision

of schooling), it is, nonetheless, useful to tin formation of effective policies to separate out the effects of

the various factors. Part II examines in detail likely

sources of the earnings gap, first individually and

then as a whole.

50

Chapter 3 discusses the economic theory and

measurement of discrimination. Chapters 4 and 5

identify several important characteristics associated

with earnings and examine each as a potential source

of the earnings gap and as a force in narrowing the

gap since 1940. Education and training are the focus

of chapter 4; geographic region and other factors are

discussed in chapter 5. Of course, these characteristics may be interrelated. While chapters 4 and 5

examine each characteristic separately, chapter 6

presents a multivariate statistical analysis that takes

account of possible interdependencies among the

variables.

rntoo
Chapter 3

The Economics of Discrimination: Theory

and Measurement

Discrimination against blacks can lead to racial

differences in wages among workers with identical

labor market productivity. The theory of labor

market discrimination developed by Gary Becker

demonstrates that such discrimination may arise

even in competitive markets if employers are so

strongly prejudiced against a group that they would

employ group members only at a lower wage

(Becker, 1957). Becker terms this wage discount a

measure of the employer's "taste for discrimination"the employer's distaste for or psychic cost of

employing the worker.

Discrimination is not costless to the emploer. If,

as a result of discrimination, blacks (equal in productivity to whites) had lower wage rates, an employer

with relatively more white workers would have

higher costs and, therefore, could lower these costs

(and increase the firm's profits) by hiring more

blacks. If a sufficient number of nondiscriminatory

employers entered the market, or if existing nondiscriminatory employers expanded production, blacks'

earnings we ild eventually be bid up, and the gap

due to discrimination would close. Becker's theory,

on the other hand, shows that discrimination could

persist for long periods if prejudice was strong and

pervasive or if constraints were imposed on the

' See Becker (1957) for more details Also, note that the few

black workers who were skilled might be downgraded occupationally rather than paid less if the premium required by skilled

whites to work alongside skilled blacks was more costly than the

growth of firms that did not discriminate 0; on the

mobility of black workers.

In Becker's model, coworkers and customers may

also be sources of discrimination "en if employers

themselves do not discriminate. if white workers

demand higher wages to wor c with blacks, employers would have an incentive to operate segregated

establishments because integration would be more

expensive. In this case the wages of blacks and

whites with the same productivity would tend to be

equalized, though they would work in different

establishments. It is possible, however, to conceive

of situations where the operation of fully segregated

plants is not feasible; for example, if there were too

few skilled black workers to complement unskilled

blacks. This case would lead to integrated plants

with discriminatory wage differentials between

blacks and whites.'

Consumer prejudice could lead to discriminatory

pay differentials in situations whet workers and

consumers interact, such as a doctor-patient or

salesman-client relationship, if consumers were willing to pay a premium for services provided by a white. If blacks and whites were equally productive

in these tasks, however, less prejudiced consumers

would have an incentive to take their business to a

black, thereby increasing the demand for blacks in

efficiency loss from employing skilled blacks in a lesser capacity

(Discrimination in capital markets likely would have been a barrier to self-employment of skilled blacks, which might otherwise have been an escape route )

C 0

51
these jobs. Moreover, consumer prejudice may

simply lead blacks to seek employment in occupations with minimal consumer contact (such as

factory work) or in businesses catering to a black

clientele. Thus, jobs with little consumer contact

and the existence of unprejudiced consumers reduce

the extent to which prejudiced consumers can create

racial differences in pay.

As discussed in chapter 2, if wages were completely flexible, discrimination would primarily affect hourly wage rates, rather than employment. In

this case discriminatory preferences would be largely reflected in a lower wage rate for blacks; as a

result, even some prejudiced employers would have

an incentive to employ blacks.

If wages are not flexible, however, discrimination

against blacks may well take the form of reduced

employment for blacks. Forces affecting wage flexibility include Animum wage laws and union wage

floors. Equal pay laws may also have the same

unintended effect.' Firms that would have employed blacks at a lower wage rate will now have

less of an incentive to do so, making it less costly for

firms to discriminate against blacks and employ only

whites.'

As an alternative to Becker's theory, some authors

have developed the idea of statistical discrimination.

According to this theory, employers who may not

be prejudiced may still treat blacks differently from

whites.' This theory presumes a world of limited

information. whet ! employers can only imperfectly

assess the individual productivity of their employees. As a result they us-, rough proxies for productivity based on race, sex, schooling, nnd other

readily observed characteristics. Thus, if employers

find it difficult to evaluate black workers, they may

treat individual blacks as having the average characteristics of all blacks. In this situation, talented blacks

would earn less than their true skills would warrant,

while blacks with below-average skills would earn

See chap 2 for further discussion of this point.

Laws and institutions that keep wages artificially high may

increase or decrease the relative hourly wage of blacks. If all

sectors of the economy were covered by the law or institution,

the relative wage would likely increase, although employment of

blacks would likely fall. If part of the economy is not covered by

the law or institution (e.g , the nonunion sector), relative wages of

black workers could fall. In particular, black workers who cannot

obtain jobs in the covered sector may take jobs at a lower wage in

the uncovered sector If this effect is sufficiently large, the overall

average wage of blacks would decline relative to that of whites.

' See Phelps (1972), Arrow (1972 and 1973), and especially the

discussion in Aigner-Cain (1977).

52

more.5 However, while the employer's inability to

sort out the different types of labor may result in

individual instances of discrimination, it will not

necessarily lead employers to pay blacks less, on

average, than they pay whites.'

The relevance of statistical discrimination for

explaining black-white earnings differences has been

questioned by D.J. Aigner and G.C. Cain (1977),

who point out that the cost of obtaining information

about workers may not be large relative to the gains

from more precisely identifying worker productivity. Testing, reference checking, and trial work

periods are methods that employers use to gain

information that enables them to distinguish among

individuals.' Moreover, black workers themselves

would have an incentive to obtain credentials (such

as licenses, degrees, school grades, and references)

that would provide pertinent information to employers. Statistical discrimination may be rclevant in

some instances, such as choosing workers for summer jobs or other short duration employment where

investment in information would not have a large

payoff. However, it remains questionable whether

statistical discrimination could be a significant factor

in the long run for adult workers.

Becker's theory of discri aination has proven

durable over the years as a basic framework for

analyzing discrimination. It implies that labor market discrimination could persist over time, even in

competitive markets, if a significant proportion of

employers were strongly prejudiced or if laws and

regulations interfered with the market process or

impeded the mobility of blacks.

It is perhaps because market forces do tend to

erode discrimination that groups wishing to perpetuate racial discrimination have sought to institutionalize it through legislation or to perpetuate it through

regulation. For example, government laws and

regulations in the Soathern States clearly impeded

the mobility of blacks in many ways. The unequal

5 This would also apply to whites unless employers could more

readily make distinctions among white workers

6 Whether or not statistical discrimination would lead to a lower

average pay for blacks than for whites would vary according to

the circumstances See Aigner-Cain (1977) for a more detailed

discussion of these points

7 The attempt to identify individual worker productivity

sometimes conflicts with civil rights policy. In particular, the use

of employment tests has been challenged as discriminatory, and

their use appears to have declined (see Potter, 1986, p 215) It is a

matter of controversy whether this policy is beneficial to blacks.

It is possible, for example, that the decline in testing actually

increased statistical discrimination.
and meager allocation of school resources to blacks

impeded the acquisition of skills (see chapter 4).

Laws against vagrancy made it a crime to be

unemployed, even if looking for new work, and

other laws limited recruitment of black workers for

jobs in another county.' Furthermore, blacks did

not receive nearly adequate protection from law

enforcement agents for their persons or their property.' The Jim Crow laws that came into effect in the

South around the turn of the century mandated

extreme forms of segregation. Although the North

did not legislate segregation, unions often effectively

kept blacks out of skilled jobs."

The Civil Rights Act of 1964 in effect abolished

the laws and regulations that mandated segregation

and thereby facilitated the elimination of discrimination. In addition, the same forces that led to passage

of the Civil Rights Act may also have raised the

consciousness of Americans and in a more subtle

way contributed to the elimination of discrimination.

On the other hand, wage rigidities, such as the

minimum wage and union wage floors, reduce the

cost of discrimination to employers and may have

facilitated the persistence of discrimination in employment. It is an empirical question whether the

forces reducing discrimination have dominated the

trend.

Measurement of Discrimination

Empirical studies of current labor market discrimination have not developed a way of measuring it

directly. Instead, they typically investigate the factors that appear to be related to skills or productivity, and they then adjust the wage gap for racial

differences in these factors. If all productivity

differences could be measured perfectly, then a good

case could be made that the amount of the wage gap

left unexplained after accounting for these differences reflects current discrimination in the labor

market.

Unfortunately, productivity cannot usually be

measured directly. The best the analyst can do is to

Roback (1984) makes the case that these and other labor laws

served to restrict black mobility, resulting in their exploitation

The extent to which these laws were actually enforced and

effective has been questioned by Higgs (1986).

See Higgs (1986) and Myrdal (1962).

utilize characteristics that are believed to affect

productivity, such as years of schooling or years of

experience, and when availably, the quality of

schooling or family background. The intensity of

effort, actual proficiency, or the difficulty of the

work performed are factors that are seldom controlled for because they are not readily measured.

It should also be recognized that current labor

market discrimination is not the only form of

discrilination. For example, racial differences in

educational attainment among workers today are

likely to have been affected by discriminatory

expenditure policies of State and local governments

in the past. And skills acquired through on-the-job

training over the years can also reflect discrimination if employers are reluctant to offer training to

minorities. Moreover, past discrimination in the

labor market may have reduced the incentive of

blacks to obtain training or schooling. Available data

and empirical estimation procedures are ill-suited to

disentangling these different types of discrimination.

Nonetheless, it is important to make these distinctions because remedies for the effects of past

discrimination (for example, dealing with school

resources) are quite different from remedies for

current labor market discrimination.

Because of the problems involved in measuring

productivity, definitive estimates of current labor

market discrimination probably cannot be obtained.

Despite these difficulties, however, an analysis of the

major factors contributing to the black-white wage

gap can enlighten our understanding of the sources

of the gap and why it narrowed over time, and can

provide boundaries to the possible role of market

and nonmarket discrimination in the overall pattern.

Chapters 4, 5, and 6 investigate the major measurable factors that a:e likel, to affect the black-white

earnings gap: education, work experience, geographic location, industrial sector of employment,

and marital status.

'° DuBois in The Philadelphia Negro (1899) cites examples of the

exclusion of blacks from unions (chap XVI, sect 47) Also see Higgs (1986) and Myrdal (1962). Even if unions had not been

hostile to blacks, they could have effectively excluded them due

to preferential treatment of relatives and friends.

53
Chapter 4

Education and Training

Formal education is a principal means of enhancing labor market productivity, and it has traditionally been the key to economic progress for groups

starting out with disadvantages. Schooling has been

termed an "investment in human capital" because it

is an activity that requires an outlay of money and

time and, in turn, raises an individual's future

productivity or earnings capacity (Shultz, 1961;

Becker, 1964). Empirical research in this area has

generally found a strong positive association between schooling and earnings.

It is likely that differences in educational attainment between blacks and whites can explain some

portion of the earnings gap. Historically, blacks had

extremely limited opportunities for schooling. The

slave codes that were part of the legal structure of

Southern States actually forbade the education of

slaves, although clandestine schooling and training

did occur (Bond, 1966; Bullock, 1967). Moreover,

the concentration of blacks in the impoverished

South during a period of extreme racial hostility was

an impediment to the rapid educational development

of freedmen after the Civil War (Jones, 1917). Over

the decades, however, differences in schooling

between whites and blacks have narrowed considerably, and this trend is expected to have been a force

in narrowing the earnings gap.

This chapter first examines the trend in years of

schooling completed for blacks and whites. As a

proxy for actual skills acquired in school, years of

schooling has obvious drawbacks. Unfortunately,

data that match the earnings of individuals to real

educational attainment are not generally available.

54

In the absence of such data, secondary sources of

information are explored to pro ide some insight

into racial differences in the quality of schooling and

educational achievement. The chapter closes with a

brief discussion of another type of investment in

human capital: training on the job.

Differences in Years of Schooling

Although blacks still complete cewer years of

school than whites, this differential has narrowed

considerably si.ice 1940 (table 4.1). Over the 1940-

1980 period, the mean level of schooling of both

blacks and whites rose steadily, but the increase was

much larger for blacks.

One reason for the educational deficit of blacks is

their concentration in the South where educational

levels historically have been below those of the rest

of the country. Moreover, the black-white differential in schooling has always been larger within the

South than in the non-South. Both the narrowing of

the black-white schooling gap within the South

(from more than 2 years in 1940 to 1 year in 1980)

and the immigration of blacks to the North contributed to the sharp convergence in the racial differential in schooling for the U.S. as a whole.

The basic pattern of convergence in the blackwhite differential in schooling shows no change

between 1940 and 1950 but accelerating improvements in each subsequent decade. The patterns

shown in table 4.1, however, refer to all men in the

working population aged 25-64. These men were

born between 1876 and 1955, and then schooling

took place over the course of a century- -from the
TABLE 4.1

Mean Years of School of Male Wage Earners Ages 25-64 by Region and Race

1940 1950 1960 1970 1980

Total US

White 9.03 9.85 10.65 11.65 12.83

Black 5.78 6.58 7.80 9.35 11.37

Difference' 3.25 3.27 2.85 2.31 1.46

South

White 8.71 9.37 10.13 11.22 12.48

Black 5.13 5.88 6.91 8.53 10.89

Difference' 3.58 3.49 3.22 2.69 1.59

Non-South

White 9.15 10.06 10.83 11.80 12.92

Black 7.31 7.98 8.94 10.20 11.91

Difference' 1.84 2.08 1.89 1.60 1.01

1White mean schooling minus black mean schooling

Source Census of Population, 1940.1980. Public Use Sample

TABLE 4.2

Years in Which Successive Birth Cohorts Reach Different Stages in the Life Cycle

Years cohort reaches ages:

Birth years 5-14 25-34 35-44 45-54 55-64

1876-1885 1890 1910 1920 1930 1940

1886-1895 1900 1920 1930 1940 1950

1896-1905 1910 1930 1940 1950 1960

1906-1915 1920 1940 1950 1960 1970

1916-1925 1930 1950 1960 1970 1980

1926-1935 1940 1960 1970 1980

1936-1945 1950 1970 1980

1946-1955 1960 1980

55

6 4
TABLE 4.3

Mean Years of School Completed by Race and Age (male civilian population)

1940 1950 1960 1970 1980

White

25-34 9.95 10.87 11.55 12.48 13.40

35-44 9.02 10.06 11.05 11.85 12.96

45-54 8.11 9.13 10.05 11.24 12.14

5E-64 7.61 8.18 8.96 10.16 11.41

Black

25-34 6.12 7.77 9.17 10.74 12.25

35-44 5.49 6.61 8.05 9.65 11.50

45-54 4.98 5.66 6.69 8.34 10.12

55-64 4.43 4.88 5.67 6.85 8.60

Differential (white minus black)

25-34 3.83 3.10 2.38 1.74 1.15

35-44 3.53 3.45 3.00 2.20 1.45

45-54 3.13 3.47 3.36 2.90 2.03

55-64 3.18 3.30 3.29 3.32 2.81

Source* Census of Population. 1940-1980. Public Use Sample

1880s to the 1970s. This is made clear in table 4.2,

which traces each group in the census data back to

the approximate dates when they were in primary

school. Thus, the educational attainment of older

members of the labor force reflects changing patterns of school attendance only with a long lag.

To have a clearer understanding of these pattern.,

a detailed historical examination folk-A-vs vi trends in

educational attainment and enrollment rates and of

the factors related to these trends. In addition,

problems of measurement that are believed to bias

the reported attainment of older age groups in the

1940-1960 censuses are examined.

Convergence in Scheoling Across Cohorts

Starting in 1940, each census has requested information on the educational attainment of the population. Thus it is possible to compare the highest grade

completed by black and white men in the same age

group and to examine the progress of successive

cohorts (table 4.3). It is immediately apparent that

for the age group 25-34, a steady and substantial

decline in the black-white schooling differential has

occurred over the period 1940-1980-from 3.8 years

to 1.2 years. At older ages, however, little or no

convergence in years of schooling occurred until

56

1980; in fact the gap widens between 1940 and 1950

for the age groups 45-54 and 55-64. It is this patter a

for the older groups that retards convergence in the

schooling gap for all ages combined (as shown in

table 4.1).

The widening in the schooling gap and the slow

rate of change for older age groups is puzzling. Two

explanations have been given. James Smith (1984)

maintains that it reflects a period of reduced governmental spending on black schools, a consequence of

disfranchisement in the South around the turn of the

century. Robert Margo (1986 a,b) suggests that the

widening in the differential results from an upward

bias in reporting of highest grade completed in the

census, particularly by blacks, for those who completed their schooling before 1910. Corrected data,

according to Margo, would show a continuous

narrowing in the black-white schooling differential

over time.

The implications of these two explanations are

radically different. If schooling is misreported, as

Margo claims, then comparisons of earnings by

education would be misleading for all groups aged

45 and over in 1940, and aged 55 and over in 1950.

Each explanation is considered in the next section,

65
which examines the historical forces underlying the

rise in schooling of blacks.

Disfranchisement and Black Enrollment in the

South

Starting in the 1880s, the Southern States moved

to disfranchise blacks through a series of laws and

regulations prescribing various kinds of voting requirements.1 Several authors have linked this loss of

voting rights to a relative decline in various measures of the quality of schooling available to southern blacks.' The available evidence from this period

is highly fragmentary. A sharp increase in blackwhite differences in teachers' pay and in the length

of the school term has been indicated for certain

counties and States in the South during the period.'

A new look at the historical documentation, however, suggests that some of the examples cited have

exaggerated the facts.' It has also been noted that

another indicator of school qualitythe pupil-teacher ratioappears to have grown somewhat more

equal between the races during this period.3

To put these pieces of evidence in perspective, it is

important to recognize that public schools had not

been well established in the South before the Civil

War (Bond, 1966). After the war the South was a

devastated and still largely rural area. In this setting,

the problems associated with the development of a

universal public school system were enormous. The

U.S. Commissioner of Education in 1887-1888, in

' Bullock (1967) notes sever: types of voting restrictions that

were adopted in the Southern States State laws included a tax

test whereby iva,ent of a poll tax was required to vote Some

States imposed a properly test Georgia, for example, required

voters to own 40 acres of :and or $500 worth of property

Education tests were also imposed. requiring skills such as ability

to read or write. or a knowledge of the Constitution. Such

requirements, Bullock maintains, Wert not impartially enforced,

and as a result blacks were virtually disfranchised See Kousser

(1974) for an extensive discussion

See Bond (1966), Du Bois (1911), Welch (1973), and Margo

(1985). 3 Ibid.

' Take the frequently noted example concerning teachers' pay in

Mississippi. Horace Mann Bond in his seminal work on the

education of blacks in the South (first published in 1934 and

reprinted in 1966) cites data showing identical pay for black and

white teachers in Mississippi from 1877-85 followed by a sharp

break in equality in 1886 and thereafter Bond relates the change

to legislation enabling diversion of funds from black to white

schools The incident has been cited by Welch (1973) and

repeated by Smith (1984), who attributes it to disfranchisement.

Kind's source is a study by Noble (1918) The economic historian

Robert Margo investigated Noble's sources, which were the

reports of the State education commissioners of Mississippi, and

found that teachers' pay in fact was not reported separately for

blacks and whites for the years 1877-'5 Noble simply listed the

comparing the educational situations of the South

and the North, noted that the South was burdened

with: (I) a relatively high ratio of school age

children to adults; (2) a relatively low tax base due

to its relatively low level of wealth per capita; and

(3) a relatively sparsely settled population.' As a

result, school expenditures per capita were much

lower in the South than in the North.' Moreover,

given the scattered rural population, southern

schools were smaller and less cost effective than

northern schools, where economies of scale could be

realized. The one-room schoolhouse was often the

rule, and many children lived too far from school to

attend on a regular basis.

The situation for black children in the South was

particularly desperate. Whites in the South were

themselves poor and resented paying for the schooling of black children. During the period 1865-1870,

the Freedmen's Bureau had financed the establishment of many schools for black children, and

through its efforts about 6 percent of black children

were enabled to attend school each year (Welch,

1973). After the period of disfranchisement, the

funding of schools for black children in many

Southern States appears to have reverted largely to

whatever the black community could provide from

its own tax dollars' For example, J.Y. Joyner, the

State superintendent of public schools in North

Carolina in 1909, calculated that little transfer of

State average pay for both black and white teachers, which

accounts for the coincidence of identical salaries (to the penny) in

each of the 9 years Starring in 1886. separate salaries are given m

the State statistics for black and white teachers, and they are not

equal. It is likely they were never equal It does appear. however.

that the black white lain) of teachers' pay declined in the State

after 1886

5 See Welch (1973) who shows a decline in class size in black

schools both absolutely and relative to whites from 1870 to 1890. 6 Based on data from the 1880 census. 40 schoolage children:

could be gathered into 1 square mile in Rhode Island, while thc

came number were scattered over 40 square miles in The

average number of children (aged 6-13) per square mile was 15 2

in the Northeastern States. compared to 5 6 in the Southeastern

States and 3I in the South Central States In addition, net

regional wealth per minor was 52,634 in the Northeast. compared

to $851 in the Southeast and South Central States combined

(Education Report, 1887-88 p 21-28)

' Total school expenditures per capita of the population in the

South Atlantic di% ision were 20 percent of those in the North

Atlantic in 1870 and rose to 35 percent in the 1880s (Report of the

Commissioner of Edu,ation. 1889-1990, p 37) flit ConIMISSIOners reports noted, however, that southern statistics likely widerestimated expenditures due to pri%.atc pa,nients and supplements

that were not counted in the data

" See Kousser (1980)

57
funds was made from the v. hite community to

provide for the schooling of black children, noting:

This report shows that the Negroes paid for schools in

taxes on their own property and polls about $163,417.89.

or nearly one-half of all that they received for school

purposes. Add to this their just share of fines, forfeitures

and penalties and their share of the large school tax paid

by corporations to which they are entitled under the

Constitution by every dictate of reason and justice, and it

will be apparent that the part of the taxes actually paid by

individual white men for the education of the Negro is so

small that the man that would begrudge it or complain

about it ought to be ashamed of himself. In the face of

these facts, any unprejudiced man must see that we are in

no danger of giving the Negroes more than they are

entitled to by every dictate of justice, right, wisdom,

humanity and Christianity'

Despite these obstacles, education did spread in

the black community. Historical data reveal an

impressive increase in school enrollment rates

among successive cohorts of blacks in the period

after emancipation and a convergence in black-white

enrollment differences. According to the decennial

censuses, in 1860 only 2 percent of black youth (ages

5-19) were enrolled in school; by 1880 the proportion enrolled had increased to one-third (table 4.4).

During the next 20-year period, black enrollment

rates appear to have declined slightly, although this

decline may be the result of definitional changes

rather than a real phenomenon.'° However, since

white enrollments showed an even sharpt r decline,

the racial differential in school attendance continued

Superintendent of Pubhc Instruction (1910), p. 54.

'° Differences in the age groups Included in the enrollment and

population data probably explain some of the decline in enrollment rates for whites and most of the decline for blacks Thus, all

enrolled persons, regardless of age. were Included in the numerator, but only those aged 5-19 were incl acted in the denominator in

calculating the enrollment rates for 1850-1880. In 1890 only

persons aged 5-19 were included in the numerator, which would

lower the rates somewhat. In 1900 enrollment and population

were expanded to Include all persons aged 5-20. Since few are

enrolled at age 20, this would further lower the enrollment rate.

Data from a special census report (Department of Commerce.

Bureau of the Census, 1918) show that for the fixed age group 10-

14, the black enrollment rate increased each decade from 1890 to

1910 (from 51.7 to 53.8 to 68.6 percent), while the rate for whites

declined slightly from 1890 to 1910 (from 84 6 to 84 percent) and

increased between 1903 and 1910 to 91 1 percent The large

increase in new immigrants may have depressed enrollment rates

among whites in the North.

" See preceding footnote.

" Private philanthrope efforts such as the Peabody. Slater and

Jeanes Funds, the General Education Board, and the Rosenwald

Funds also provided funds for enhancing the educational facilities

for black children in the South, but the total amounts wcre laxly

to have been relatively small See Bond (1966)

58

to narrow during this period." After 1900 cornment rates of both races increased steadily, but the

growth among blacks was more rapid, and as a

result the differential fell below 5 percent by 1950.

How were blacks able to make these remIrkable

gains amidst the poverty and hostility of the postReconstruction South? One likely contributing factor was a relative rise in black wealth, as black farm

ownership and land holdings grew (Higgs, 1982;

Margo, 1984). Since black taxes seem to have been

the primary source of support for black schools, the

rise in wealth would have enhanced the resources

available for black schools.'2 In addition, blacks

could, and there is some evidence they did, migrate

to areas with better schooling opportunities, even

within the South." It is also noteworthy that family

demand for children's schooling likely increased as

parental incomes and literacy rose."' Finally, the

development of the South itself probably boosted

black opportunities. Enrollment rates in the South,

which had been considerably below those in the

North in 1880, rose rapidly and reached northern

levels by 1920.'5 Even had blacks not made

educational gains on whites in the South, black

school participation nationally would have likely

increased relative to that of whites because a

disporportionate share of black youth (ages 5-20)

lived in the South (92 percent in 1910 versus 28

'" Enrollment rates among black :hildren were considerably

higher ill urban areas In 1910 the enrollment rate for black

children aged 10 14 was 77 percent in urban areas and 66 percent

in rural areas in the South (NationvvIde these figures were 81

percent and 66 percent ) Between 1890 and 1910. the proportion

of the black population in urban areas increased from 15 percent

to 21 percent in the South. and nationwide from 20 to 27 percent

Also, Margo (November 1985) discusses how blacks "voting with

their feet" put pressure on white property Owners to impiove

black school faulntcti, which they would do to present migration

of black workers to other areas

'4 In a statistical analysis of the determinants of rectal differences

in school enrollment in four Southern States in 1900. Margo

(March. 1986) finds that school sharastertstics (school density,

length of the school seer) could account for only one-third of the

attendance gap l'areiv al literacy, occupational status. and wealth

accounted for more 'hen half of the gap Losation in a cotton

farm area also played a role (Cotton was the due( crop for which

children could be productively employed fly contrast. children

in urban areas had few employment opportunities )

15 Enrollment data from both the census and the annual reports

of the U S Commission of Idusation show little change in

enrollment rates in the North betsse..31 1890 and 1920 and

substantial insrsases in the South Within th. South. both sources

show somewhat more rapid Increases for blacks than for whites.
TABLE 4.4

Enrollment Per 100 Males of School Age by Race

White Black' Difterence2 Ratio3

1850 56.2 1.8 54.4 .032

1860 59.6 1.9 57.7 .032

1870 54.4 9.9 44.5 .182

1880 62.0 33.8 28.2 .545

1890 57.9 32.9 25.0 .568

1900 53.6 31.1 22.5 .580

1910 61.3 44.8 16.5 .731

1920 65.7 53.5 12.2 .814

1930 71.2 60.3 10.9 .847

1940 75.6 68.4 7.2 .905

1950 79.3 74.8 4.5 .943

1960 84.8 81.5 3.3 .961

1970 88.3 85.3 3.0 .966

Note The ages included in the enrolled and sChoolage populations differ as follows

1850.1880 Er.rotanent includes all persons er.rone regardless of ago, the schoolage population is 5.19 years

1890 and 1940.1970 Enrollment an/ population include persons 5.19 years old

1900.1930 Enrollment and population include persons 5.20 years old

'Includes ot:ter nonwhite races 2White rate minus black rate

3Black rate divided by white rate

Source U S Bureau of the Census, Ht.toncal Statistics of the United States Colonial Times to 1970, table H 433.441

1. 3 59
percent of whites) which was making gains on the

rest of the Nation."

The enrollment data show a constant narrowing

of the racial gap in schooling participation between

blacks and whites. Enrollment rates, however, do

not provide full information on the amount of

schooling attained, since attendance during the year

and promotion rates can vary. The data on years of

school completed reported in each decennial census

starting in 194.0 are intended to reflect the actual

number of grades completed. As Smith (1984) has

emphasized, the census data on educational attainment show a widening in the black-white schooling

gap for the cohorts born 1886-1890 to 1901-1905,

which is contrary to the findings on enrollment rates

reviewed above. Smith's data are reproduced in

table 4.5, arrayed according to the year the cohort

reached age 10.17

Margo (1986a, 1986b) has suggested that the

increase in the racial schooling gap is spurious and

can be attributed to the inability of census enumera

tors to determine accurately the highest grade of

school completed by persons attending 'ngraded

schools. As Margo notes, the 1940 census 'iced for

highest grade completed, but for those who had

attended ungraded schools, the census enumerators

recorded the "number of years the person attended

school." Two factors make this issue of particular

importance to blacks. One is that blacks educated at

the turn of the century were likely to have attended

an ungraded school. Margo notes, for example, that

in Texas 89 percent of black schools were ungraded

in 1900. Whites, on the other hand, most of whom

lived outside the South, were much less likely to

have attended ungraded schools. The second factor

is that the number of years attended is likely to

exceed the number of grades completed by a wide

margin for blacks because southern black schools

were typically kept open only a few months during

the year. The average black student would have had

to attend school for more than 1 year to complete a

grade-2 years, in fact, according to Finis Welch

(1973). Thus, a black reporting 6 years of school

16 The data on the regional distribution of the population are

from U.S. Department of Commerce, Bureau of the Census, 1918 " Note that data such as those presented in table 4 3, which

provides years of school by age, were used by Smith to construct

his cohort achievement measures Schooling for cohorts horn in

the past century !s based on the schooling of older persons

reported in the 1940 and 1950 censuses The widening in the

schooling gap is also shown in table 4 3 as noted above.

" The census reports enrollment rates by age starting in 1890,

from which Margo estimated how many years of school would be

60

attended may have actually completed the equivalent of only three or four grades. As graded schools

replaced ungraded ones, the reporting of actual

grades completed no doubt improved. And as the

length of the school term increased, years of school

completed increasingly corresponded to actual

grades completed. Since grades completed was a

lower number than years attended, real increases in

schooling would be obscured during the transition

period.

Using data on school attendance by age reported

in censuses starting with 1890, Margo has constr zted two alternative measures of average years of

schooling, and these are also shown in table 4.5.18

The first measure simply reports the estimated

number of years of school attended (whether or not a

grade was completed). The second measure is an

estimate of highest grade completed based on the

actual number of months of school attended by the

cohort each year and on the estimated number of

months it would take to complete a grade."' The

second estimate is available only for cohorts born

between 1886 and 1890. Margo's estimates of the

number of years attended, as expected, exceeds the

census attainment measures. For whites, the difference in the two measures remains constant over the

period considered. For blacks, however, the "years

attended" measure rises more rapidly and, therefore,

becomes increasingly highe- than the "grades completed" measure, As a result le racial gap in "years

attended" converges steadily during the period.

There is no mysterious widening as shown in the

reported census data on years of school completed.

Margo argues persuasively that these discrepancies are the result of bias in the census data on grades

completed for those attending ungraded schools.

Using the number of months of school required to

complete a grade, he estimates that the actual

number of grad's completed for the cohort reaching

age 10 in 1896-1900 was 6.9 years for whites and 2.9

years for blacks. This leaves a racial gap of 4 years, 1

year larger than that obtained from the census

attainment data reported in the 1940 census.

attended for the aserage person between ages 5 and 20 Since the

census reports Ps ery 10 year, interpolation was (IS mcluired to make

the calculations The censuses of 1890 and 1900 also provided

information on the number of months school was attended, which

enabled a calculation to he made of lifetime months attended

" Mat go divides by 7 2 months (which was the average school

term in the Nation) to obtain the highest grade completed 1 he

U S Commissioner of Education in 1890 used 200 days (based on

the best northern records) to make a similar calcu!..tion

1) 0
TABLE 4.5

Highest Grade Completed and Years of School Attended by Race for Cohorts Born

Pre-1885 to 1961-64

Year cohort

reaches

age 10

Pre-1875

1875-80

1881-85

1886-90

1891-95

1896-1900

1901-05

1906-10

1911-15

1916-20

1921-25

1926-30

1931-35

1936-40

1941-45

1946-50

1951-55

1956-60

1961-64

Census attainment

measure of highest

grade, unadjusted'

White Black Diff.

6.8 2.4 4.4

7.1 3.1 4.0

7.2 3.6 3.7

7.4 4.1 3.3

7.6 4.4 3.2

7.7 4.7 3.0

8.2 5.0 3.2

8.7 5.4 3.3

9.1 5.7 3.5

9.7 6.3 3.5

10.2 6.8 3.4

10.7 7.7 3.1

11.1 8.4 2.7

11.4 9.1 2.3

11.7 9.8 1.9

12.0 10.5 1.5

12.3 11.3 1.1

13.7 11.9 0.8

12.5 11.8 0.8

Estimated years

attended2

White Black Diff.

8.7 4.9 3.8

9.0 5.5 3.5

9.5 6.4 3.1

9.9 7.2 2.7

10.5 8.0 2.5

Estimated highest

grade adjusted3

White Black Diff.

6.9 2.9 4.0

1Taken from Smith (1984). tables 3 and 4. rearranged to correspond with year cohort reached age 10 rather than year of birth

2From Margo (1988a). table 1 Estimated from census enrollment data

3From Margo (1986b). Estimated from census data on number of months of school attended and the number of months neededto complete a grade

61
TABLE 4.6

Percentage Distribution of Years of School Completed by Race for Cohorts of Men

Reaching Ages 25-29 Between 1940 and 1980

Cohort

reaching

ages 25-29

White

Years of school

Black

Years of school

in: 0-7 8-11 12-15 16+ 0-7 8-11 12-15 16+

1940 17.1 41.3 32.3 9.1 59.3 27.3 11.1 2.4

1950 11.1 31.3 43.5 14.2 38.4 36.1 21.8 3.8

1960 8.2 24.0 48.4 19.4 22.9 36.3 34.7 6.1

1965 6.1 19.5 52.6 22.0 13.5 34.0 45.0 7.5

1970 4.5 16.5 53.2 24.5 9.5 30.3 51.6 8.9

1975 3.6 10.2 55.1 31.2 5.2 21.4 60.3 13.2

1980 2.8 11.1 61.0 25.3 3.5 21.2 64.2 11.2

Note Cohortspecific averages taxen across relevant censuses Source 1940-1980 Censuses. Public Use Nes

In sum, considerable doubt has been cast on the

measure of yeats of school completed reported in

the census for persons born before 1900 The

reported measure is a hybrid of actual grades

completed and of years literally attended, e en if for

a few weeks per year This problem is more serious

for blacks than for whites. The implication of this

finding is that analysis of schooling differentials or of

earnings by education for these earlier cohorts is

likely to be seriously biased, since reported schooling overstates actual grades completed. In the census

data set used in this report, the groups primarily

affected would be black men reaching ages 45-64 in

1940 and ages 45-64 in 1950. By 1960 most age

groups are likely to have received their education in

graded schools and would have been able to report

on their highest grade completed. This still does not

remove all upward bias in highest grade completed

"oecause grades were not adjusted for the length of

the school term. A black attending a graded school

in Alabama in the 1920s would oxerstate his educational achievement in the 1940 census because the

length of the school term was so short This source

of bias was not omitted until the 1940s, as discussed

below.

The overall picture presented by this review of

the trend in the quantity of schooling obtained by

62

blacks and whites is one of substantial convergence.

Despite the enormous obstacles inherent in their

situation as former slaves, isolated in a poor rural

resion, black parents managed to send their children

to school in increasing numbers. By 1980 the blackhite differential in years of school completed had

narrowed to less than a year for young adults. In

1940 only 13.5 percent of young black men (aged

25-29) had completed 4 years of high school or

more, one-third the percentage attained by whites;

but in 1980, 75 percent of young blacks achieved

high school graduation or more, and this was close

to 90 percent of the white percentage (table 4.6).

Differences in School Quality and

Educational Achievement

The number of years attended or ex en the highest

grade completed do not adequately convey what a

person has learned in school This section reviews

axailable irforrnation on the quality or produ_tivity

of schooling. Two types of data are examined One

ty pe focuses on school resources, which are inputs

to the education process. Another data source

involves measures of educational performance or

outcomes. Both types of data are intended to be

merely suggestixe, gnen the conceptual difficulties

7i
involved in measuring sclluol quality or educational

achievement.

School Inputs

It is generally believed that the benefits from a

year of schooling are affected by the resources

devoted to it." As discussed above, Horace Bond

(1966), Margo (1985), and others have documented

the low level of schooling resources made available

to blacks in the post-Civil War South. Welch (1973)

has associated the meager school resources allocated

to blacks with the low black-white earnings ratios of

earlier cohorts and has related the subsequent

increase in the ratio with relative improvements in

school quality for blacks

Three measures of school resources or inputs are

shown in table 4.7: average days of school attended

per pupil during the year, the number of pupils per

teacher, and teacher salaries per school day. These

data are shown by region, and for the South by race.

They vividly illustrate the large disparity in resources between black and white schools in tile

South and the even greater disparity compared to

schools outside the South.

Early in the century, the school year was Shorter,

particularly r. -.1 places, to accommodate the

farmwot k do. by children. This helps explain why

schools w open fewer days in the South, which

was heavily rural. The differences in 1920 by region

and race were enormous. Students in the South

attended school 24 percent fewer days than students

outside the South, and black students in the South

attended school 24 percent fewer days than their

white counterparts.

These differences in the length of the school year

must certainly have affected what could be learned

in a school grade if grades simply corresponded to

the length of the school term On the other hand, if

students were not promoted until they mastered a

certain amount of material, it would simply take

more years to complete a grade when schools were

kept open fewer days. Some el. idence suggests that

youi.g people remained in the lower grades at older

20 There 1., a large literature on educational "production

functions" relating mea,ure. of schooling input ith educational

outcomes, usually measured by test scores See, for example.

Hanushek (1972), Coleman et al (1966). Bowles and 1,Am

(1968), and Michelson (1970)

" There is also some evidence that black teachers ware poorly

prepared Thomas Jones, a specialist m the education of raual

groups in the Federal Bureau of Education reported in 1916 that

"In view of the small remuneration and the lack of training

ages. Thomas Jones (1917, p. 33) notes that in 1910,

90 percent of black students aged 15-19 years were

enrolled at the elementary school level. Welch

(1973) estimates the average black took 2 years to

complete the first grade in the early 20th century

South. Thus, the dramatically shorter school term

available to black children in the South was likely to

have affected their schooling in two ways. One was

to reduce the amount learned in a school grade; the

other was to reduce the number of grades ever

completed.

Other resources devoted to black and white pupils

in the South also differed substantially early in the

century. Black students on average attended classes

with more than 38 students, a pupil-teacher ratio 46

percent larger than that found in southern white

schools and 54 percent larger than in northern

schools. Teacher salaries varied even more by race

and region. In 1920, for example, teachers in black

southern schools received 55 percent as much per

school day as teachers in white southern schools and

40 percent as much as teachers in nonsouthern

It is difficult to determine how much these

differences in school resources reflect differences in

the quality of a given number of grades completed.

Differences in cost of living may account for some

of the regional differences in teachers' pay. Moreover, black-white comparisons in pay may well

reflect discriminatory pay-setting practices." Some

of the differences in school resources may also be

due to compositional factors, since blaci. students

were heavily concentrated in the lowest grades

where costs are typically lower. In addition, school

quality differences may have varied by grade level,

with smaller differentials at the secondary level.

Jones (1917) writes that in the period around 1916

them were only 64 public high schools for blacks in

the Southern States, and these were mainly located

in the large cities of the Border States. The high

schools of Washington, D.C., and St. Louis were

noted as particularly outstanding. In the Deep

South, secondary educatioa for blacks was largely

(aunties. it is little wonder that the majority of the public-school

teachers are very poorly prepared In Georgia and Alabama, for

example, 70 percent of the colored teachers have temporary or

emergency certificates representing a schooling of less than eight

elementary grades (See Jones. 1917 ) However. Margo (1984).

in a study of black -white differentials in the pay of teachers

mound 1910. found a substantial unexplained residual after

accounting fur differences in teacher qualifications He notes.

however. that F measures of qualifications may he inadequate

4

63
TABLE 4.7

Measures of School Resources in Public Elementary and Secondary Schools by Race

Days of attendance'

Non-South

All

South

Black White

Ratio of

southern black to:

Southern

white Non-South

1920 146.8 86.0 112.8 .76 .59

1935 156.8 111.0 134.0 .83 .71

1940 156.0 127.9 143.4 .89 .82

1951 158.3 149.6 153.2 .98 .95

1953 160.9 151.2 156.7 .96 .94

Student-teacher ratio2

1920 25.0 38.6 26.4 1.46 1.54

1935 . 32.3 44.8 33.5 1.34 i .39

1940 23.9 30.5 25.3 1.21 1.28

1951 25.3 31.7 27.6 1.15 1.25

1953 25.4 27.7 27.6 1.00 1.09

Teacher salary per school day3

1920 7.82 3.10 5.60 .55 .40

1935 8.60 2.94 5.35 .55 .34

1940 10.10 4.07 6.42 .63 .40

1951 20.47 13.22 16.70 .79 .65

1953 22.25 15.83 17.59 .90 .71

'Average days of attendance per enrolled student In public schools

2Ratio of student enrollment to number of publIc school teachers weighted by the attendance rate The attendance rate is the proportion of total school termdays attended by the

average student

3Average annual teachers salary per day of school term

Sources These data were obtainev primarily from various issues of the Bennie! Survey of Education. supplemented by other sources oted in the bibliography

64
private. Thest. public and private high schools

appear to have provided adequate schooling.22

Thus, the few blacks who graduated from high

school, or even the eighth grade, may have attended

schools that were more nearly comparable to the

schools of whites completing these levels.

The three indices of school resources shown in

table 4.7 improved markedly for blacks in the

decades after 1920, and in most cases the black-white

gap narrowed as well. For example, the length of

the school term for blacks rose from 0.76 of that of

whites in 1920, to 0.89 in 1940, and to 0.96 in 1953.

By 1954, the year in which the Supreme Court ruled

that segregated schools are inherently inferior,

differences in resources between black and white

schools in the South had narrowed considerably.

Data on school resources by race are less readily

available after 1954. Brown v. Board of Education

made it illegal for public schr ' systems to maintain

segregated schools for black nd white children,

with the result that separate statistics ceased to be

collected. The Coleman Report (1966), however,

provides detailed information on the schools, the

teachers, and the students at schools attended by

"typical" white and black students. These data were

collected in 1965 and thus characterize the educational experience of the most recent birth cohorts

studied in this reportindividuals reaching their

twenties in 1980.

Comparing the Coleman results on teacher salaries and student-teacher ratios with the data for

earlier periods reported in table 4.7 suggests there

was continued Improvement in resources devoted to

black education between the mid-1950s and mid2 2 Jones reports on all the school systems for blacks in the South

and provides details on each of the secondary schools Two

samples of the Jrnculum offered at the secondary level follow.

In Louisiana no public high schools were provided for blacks

Nonetheless, the few private high schools seem quite good New

Orleans College, a private elementary and secondary school for

blacks in New Orleans provided the following program, as

reported by Jones.

The secondar, work is divided into two courses, the

"college-preparatory" course with 41 pupils and the "normal" course with 84 pupils The "college-preparatory"

course includes. Latin, 4 years, French, 2, mathematics, 3,

English, 31/2, elementary science, 2'/2, history, 11/2, Bible, 1/2,

and civics, V, The "normal" course comprises. Latin. 2

years, English, 3, mathematics, 3, elemeatary science, 21/2,

history. I; psychology and education. 2. A small amount of

time is given to practice teaching, music, physiology.

agriculture, manual training. cooking, and sewing

The one public high school for black students in Georgia (located

in Athens) was described as follows

In accordance with the Georgia public school plan, the

1960s. In fact, teacher salaries and class size had

become roughly equal for black and white children,

except in the nonmetropolitan South, where small

discrepancies lingered. However, the Coleman results also indicate that significant differences remained in other dimensions such as verbal test scores

for teachers, availaoility of certain facilities, and

special program availability.23

This discussion of school inputs has concentrated

so far on primary and secondary education. The

emergence of a substantial college-educated "elite"

among blacks is a relatively recent phenomenon."

In 1940 only 2.5 percent of black males 25-34 years

old had completed 4 years of college or more, in

contrast to about 9 percent of white males. By 1980,

12 percent of young black males and over 30 percent

of white males in this age group had completed

college.

It is difficult to determine if the growth in college

attendance was accompanied by an upward trend in

the quality of higher education for blacks. Jones

(1917) in his 1916 study of black education in the

United States found only 1,643 black students at the

college level in the South and about 500 in the

North. Half of the students in the South were

attending three well-regarded black institutions

Howard University, Fisk University, and Meharry

Medical College. Possibly the rare few who reached

college received relatively high quality educations.25

In more recent times, however, several factors

would seem to have worked towards improving the

quality of higher education available to the increasing numbers of black youth. These include: the shift

grades above the seventh are considered as the high school

These grades are well taught The subjects are the same as

those in the corresponding grades of the white high school

Latin, Greek, history, literature. mathematics, English, physics, and chemistry Little departure is made from the college

preparatory type of studies (Jones, 1917)

23 The Coleman Report found that the average verbal test scores

of teachers of black pupils was 87 percent the level of teachers of

white pupils at the elementary level (91 percent at the secondary

level) See the discussion in Welch (1973)

24 See Freeman (1976) for a thorough treatment of this issue

22 1 he rare few, whether due to their own exceptional talents or

to their schools, often made outstanding records Amherst, for

example, admitted 34 graduates of Dunbar High Srbool (an

outstanding black school in Washington, D C ) between 1892 and

1954, and one-fourth of these graduates became Phi Beta Kappas

(See Sowell, 1974) Also the Negro Year Book cites 40 black

college gra ivates who made Phi Beta Kappa between 1900 and

1921, most graduating from leading schools, such as Yale,

Williams, Dartmouth, Oberlin, Harvard, and the Unicersity of

Chicago

''1 A I Li

65
TABLE 4.8

Male Illiteracy Rate by Cohort and Race

Birth

year

Cohort

Year

reached

age 10

Year

reached

age 40 Blacks

Percentage illiterate

Whites Difference

1840 1850 1880 74.8 8.0 66.8

1850 1860 1890 60.6 7.7 52.9

1860 1870 1900 43.0 6.3 36.7

1870 1880 1910 27.7 5.5 22.2

1880 1890 1920 22.0 5.3 16.7

1890 1900 1930 17.3 3.4 13.9

1900 1910 1940 14.1 2.0 12.1

1910 1920 1950 7.5 1.2 6.3

1920 1930 1960 6.1 0.7 5.4

1930 1940 1970 3.4 0.5 2.9

1940 1950 1980 1.7 0.4 1.3

1950 1960 1990 0.8 0.3 0.5

1960 1970 2000 0.4 0.3 0.1

Source Smith (1984)

of blacks from the South to the North and West

where access to high quality schools was less

restricted, the integration of formerly all-white

schools in the South, and the establishment of GI

education bendits and then Federal grants and loans

to low-income students, which eased financial obstacles to attending higher quality institutions. The

extent to .which these changes improved access for a

larger proportion of the population as opposed to

improving the quality of schooling received by those

who attended is an open question.

In sum, the educational resources available to

blacks increased enormously over the century, both

in absolute terms and relative to white resources.

Some portion of the increase in resources went

towards increasing the number of grades completed

by the average black person. But surely some

portion also resulted in real improvements in school

quality, at least during the period 1920 to 1953.

Measures of Educational Outcomes

The measures of schooling quality considered

above refer to inputs to the educational process and

not to educational outcomes-the kills attained in

school. Several direct measures of educational output have been utilized to evaluate the effectiveness

66

of education in enhancing skills. Two widely used

measures are considered here: illiteracy rates and

test scores.

Illiteracy Rates

The ability to read and write is primarily acquired

in school and is basic to the performance of all but

the least skilled jobs. Illiteracy rates are especially

useful for evaluating black-white differences in skill

among individuals in the earlier birth cohorts in the

census data.

Table 4.8 is taken from Smith (1984) and reports

illiteracy rates for individuals born in each decade

since 1840. The table shows that Illiteracy was still

common among black men born in 1880 who, at age

60, were among the older members of the work

force in 1940. Of this group, 22 percent were

illiterate. This, however, represents a dramatic

intergenerational gain, since more than 60 percent of

the fathers of these men would have been illiterate.

The fathers, born approximately in 1850 (most into

slavery), were largely deprived of formal schooling

as children. In contrast, illiteracy was fairly rare

among whites born in 1880. It was similarly rare
among blacks of the same cohort living in the North

and West.26

Illiteracy among blacks born between 1880 and

1910 was cut by a factor of threefrom 22 percent

to 7.5 percent. The rate continued to decline over

the next 50 years, steadily eliminating the difference

between whites and blacks. This pattern of convergence is consistent with the increasing school attendance of blacks reported above.

During the period of agrarian predominance, raw

physical ability and basic skills acquired on the job

were adequate to earn at least a subsistence level of

income. However, as the Nation advanced industrially and technologically, demand increased for

people to fill jobs requiring skills learned in school

reading, writing, and mathematical skills in particular. Today, a young illiterate person faces extremely

limited employment opportunities. Given the general increase in schooling levels, illiteracy is now

comparatively rare. Thus, for recent periods, the

illiteracy rate is less useful for discerning racial

differences in school-related skills, prompting a look

at test scores for additional inform:tion.

Test Scores

In recent years, achievement testing has become

widely used to evaluate the productivity of education as well as to assess the potential success of

applicants for schools and jobs. As stated in th.1

Coleman Report:

These tests do not measure intelligence, nor attitudes, nor

qualities of character. Furthermore, they are not, nor are

they intended to be "culture free " Quite the reverse: they

are culture-bound. What they measure are the skills whtch

are among the most important in our society for getttng a

good job and moving up to a better one, and for full

participation in an increasingly technical world. Consequently, a pupil's test results at the end of public school

provide a good measure of the range of opportunities open

to him as he finishes schoola wtde range of choice of

jobs u. colleges if these skills are very high, a very narrow

" The census of 1910 shows an illiteracy rate of 5 4 percent for

blacks born in 1880 and living in the North (3 7 percent for those

in the West) Although these rates are higher than those obsersed

for native whites of the same cohort living in the North and West.

they are substantially below the illiteracy rates of the foreign burn

of the same age, and are also lower than rates for name whites

living in the South (see Department of Commerce. Bureau of he

Census, 1918. chap. XVI)

27 For example, see Coleman (1966) and the Plom.den Report.

similar to the Coleman Report, for Great Britain (Plowden, 1967)

Bond discusses evidence from an earlier period (primarily the

1920:4 showing a strong relation between parental economic

status and student achievement. For example, in New Orleans.

range that includes only the most menial jobs if these skills

are very low. [Coleman, 1966, p. 20]

Achievement test scores, of course, reflect more

than schooling. In fact, one prominent finding of the

Coleman Report, as well as of many other studies of

the determinants of achievement, is that the socioeconomic status of the parents, and other aspects of

the student's environment outside of school, have a

major influence on test performance." On the other

hand, measured school characteristicssuch as the

teacher's score on a verbal achievement testhave

also been found to have important effects on student

achievement, particularly for blacks." Moreover,

for purposes of assessing worker characteristics, it is

useful to have a measure that captures cognitive

skills, whether acquired at home, at school, or

elsewhere. Such skills are by no means the only ones

that influence earnings. Managerial skills, artistic

ability, and physical dexterity are among the important skills that may affect earnings and typically are

not measured well by achievement tests.

A series of nationwide tests has been administered

to schoolchildren throughout the years. Table 4.9

summarizes the black-white gap in achievement test

scores for several major nationwide tests given to

students at different grade levels over the period

1960-1982.29 There is no truly correct way to

compare results of different tests given at different

times. The test score gap in table 4.9 is expressed in

terms of the standard deviation, which allows for a

rough comparison. The overall impression from

table 4.9 is that black children score about one

standard deviation below white children over the

entire period.

These results are not strictly relevant for interpreting earnings differences in our sample of dpta

from the 1940-1980 censuses because results from

tests administered in the 1960s are applicable only to

the younger workers in the 1980 census data. For

results applicable to older workers in 1980 and to

Negro Lhildren from professional famil.es scored much higher

than other children (Bond. 1966. pp 352-56)

2" Direct pleasures of teacher quail y, such as teacher's stores on

a verbal test, have been shown by Hanushek (1972) to have a

significant effect on student achievement The teacher's advanced

degrees, Yeats of experience, and pay have had mixed results,

some showing effects and others not However, the ariation in

pay and degrees is much smaller in the econometric studies

(which refer to recent times) i:ian the large differences in the

South early in the century " Witli the exception of scares on the Graduate Record

Lxaminatitai, the reported gaps in standard deviations are taken

from a study by Olncck (1985)

I 0

67
TABLE 4.9

White-Black Gap in Standardized Test Scores (in terms of total standard deviation)

Year Sample Grade Test Gap

(standard

deviation)

1960 Project TALENT 9 Composite 1.28

1965 EEOR 6 Verbal 1.00

(Coleman Report) 9 Verbal 1.00

12 Verbal 1.01

1972 National Longitudinal 12 CGTIposite 1.10

Survey 1972

1980 High School and 10 Composite 0.96

Beyond 12 Composite 0.82

1980 SAT ii & 12 Verbal 1.04

Math 1.05

1980 Graduate Record 16 Verbal 1.28

Exam (GRE) Quantitative 1.28

1982 High School and 12 Composite 0.96

Beyond 12 plus

dropouts

Composite 0.93

Source All entries except the Graduate Record Examination (GRE) score results are from data assembled by Michael Olneck (see Olneck, 1985) The GRE 'mutts are calculated

from mean scores and standard deviations reported by race in Cheryl L WI le, A Summary of Data Collected fro,, Graduate Record Examinations Test-Taxers During1979.80,

Data Summary Raport II it ovember 1981, Educational Testing Service)

68
those in earlier censuses, unfortunately, little information is available. Bond reports on a survey of the

achievement of black children conducted by the

Julius Rosenwald Fund in 1929-1931.3° This survey

covered third and sixth grade children in urban and

rural counties in Alabama, Louisiana, and North

Carolina. The average black student in these counties scored 0.75 years behind the national average in

the third grade and 1.8 years behind in the sixth

grade. Welch notes that the Coleman Report found

southern black sixth graders to be 2.1 years behind

the norm and estimates that third graders in the

Coleman data were 0.9 yean; behind." These

comparisons do not suggest any narrowing in the

achievement gap over this period.

Recent data, however, indicate a convergence in

test scores. The National Assessment of Educational

Progress evaluates the extent to which students have

learned commonly taught material. The assessment

shows that black youths made gains in reading and

mathematics performance at mo;t age levels in the

period between 1972 and 1981. Whites progressed

little and in some cases declined, and as a result the

gap narrowed." Since 1975 black students have also

gained relative to white students on the Scholastic

Aptitude Test (SAT). (White SAT scores have been

declining for several years.) Nonetheless, in 1984 the

average black score was, on both the verbal and

quantitative pats of the SAT, approximately at the

16th percentile in the white distribution of scores,

leaving a substantial differentia1.33

The achievement tests reviewed above are given

to children midway in their schooling. Students

drop out, however, at different stages, and black

students drop out earlier than white students. Since

those with lower scores are more likely to drop out,

the pattern of scores by race among adults who have

completed different levels of schooling is likely to

differ from what is observed amon ; children in a

given grade.

More relevant, therefore, is the Armed Forces

Qualification Test (AFQT), which has been used by

the armed services for many years to test individuals

for the purposes of induction and placement. Those

taking the test have usually completed their school-

" See Bond (1966), pp 337-51 The test administer-d was the

Stanford Achievement Test.

See Welch (1973) p. 71. 32 See Congressional Budget Office. Trends in Educational

Achievement (April 1986), app E "

34 For a discussion of this test, sec Office of the Assistant

ing (although some return with the G.I. Bill). Table

4.10 shows mean scores on the AFQT by race and

by years of education for men ages 19-21 at two

periods in timethe middle 1950s and 1980. Data

for the 1950s were obtained from a 50 percent

sample of the records of all individuals (0.75 million

men) who were called up for the draft or attempted

to enlist during the period January 1953 to July

1958.

The Department of Defense contracted with the

National Opinion Research Center to administer the

AFQT in 1980 to a nationally representative sample

(close to 12,000 men and women)." The results of

this test were tabulated for men at the same age and

educational levels as shown for the 1950s data. The

two tests are comparable, although the contents

have changed somewhat over time.

The AFQT is an achievement test, and like other

such tests, it reflects the quality of schooling

received as well as family socioeconomic status and

other factors. Bond reported, in discussing results by

race for a forerunner of the AFQTthe Army

Alpha test given to World War I recruitsthat

black soldiers from the North made higher scores

than the white soldiers from certain Southern States,

suggesting the significant effect of school quality

and economic status."

As is evident in the table, AFQT scores are highly

correlated with schooling for both black and white

men. But the test scores of black men are lower than

those of white men at each schooling level. Moreover, the results are remarkably similar for the two

points in time. Although a narrowing in black-white

gap is evident for groups with less than 3 years of

high school, there has been no narrowing for those 3

years or more of high school. The vast majority of

both black and white young men are now at these

higher levels. Studies by the Defense Department

have also examined changes in AFQT test scores

over time and have also found that the black-white

differential in test sco-es has remained approximately the same since the end of the Korean war."

Secretary of Defense. Profile of American Youth 1980 Nationwide

Administration of the Armed Services Vocational Aptitude Battery.

(March 1982)

" Sec Bond (1966) " See Office of the Assistant Secretary of Defense, 1982, in

particular. pp 34-35. Eitclhcrg. 1981

69
TABLE 4.10

Mean AFQT Percentile Test Scores of Men Ages 19-21 by Race and Education

`itArs of school

completeci

1953-58

Black White

1980

Black White

Difference

1953-58 1980

Elementary

5-6 7.7 15.4 4.5 7.3 7.7 2.8

7-8 12.4 28.1 9.4 14.9 15.7 5.5

High school

1-2 19.1 40.4 14.0 30.4 21.3 16.4

3-4 32.2 57.2 19.4 46.5 25.0 27.1

College

1-2 46.3 70.9 39.2 65.8 24.6 26.6

3-4 50.6 76.9 49.7 80.2 26.3 30.5

Note Mean percentile soores on the Armed Forces Qualification Test (AFQT) for 1953-58 are basedon data obtained from a 50 percent sample (0 75 million men) of the records of all individuals called up for the draft or attempting to enlist between 1953 and 1958 Scores for 1980 are based on the results of the AFOT administered by the Defense Department to a rational sample of youth

Sources 1953-58, D O'Neill (1970) 1980. data tabulated by USCCR staff from the U S Department ofLabor's National Lonoitudinal Survey cf Youth

70
miation Between School Achievement and

Earnings

Theis is reason to believe that the differences in

scores a.-e capturing, to some extent, real differences

in market oroductivity. Economists have investigated the effect of adjusting for differences in ability

on estimates a the rate of return on schooling. The

studies find a trong correlation between test scores

(usually the A,.'QT) and later earnings for individuals with the same schooling level. The results,

however, are sensitive to the method used to adjust

for differences in schooling, region of residence, and

family background. Zvi Griliches and William Mason (1977) estimate that a 30 percentile increase in

AFQT score increases weekly earnings by 4.6

percent, adjusting for education, age, and amount of

milithry service. Adjusting only for schooling obtainer after the tests were administered doubles the

estimeed effect. Adjusting for father's education

and occupat:3:. reduces the effect by as much as a

third. Accounting iz-n. the "noisiness" of test scores

can increase the effect of ability by a ;actor of three

or more." John Hause (1972) investigates the

interaction of ability, schooling, and experience as

they influence earnings. After adjusting for earnings

differences due to father's education, religion, marital status, and region, he estimates that a one

standard deviation on an aptitude test score increases

earnings 3.9 percent for high school graduates and

6.6 percent for college graduates.38 39 40

The reason for the sensitivity of the results is that

background characteristics such as father's occupation and education affect the acquisition of those

skills the AFQT is designed to measure. If the effects

of background characteristics on skill are taken into

" The sample Griliches and Mason (1972) use is quite small and

has a small representation of blat ks It consists of 1,454 postWorld War 11 veterans of whom only 4 percent arc black

However, in their sample, the black -white earnings differential .

essentially eliminated after adjusting for ability purged of its

noise, schooling obtained liter the ability tests were administered,

age, and amount of military service.

" A one standard deviation difference in test score doe not

represent a constant difference in percentiles For instance, for an

individual at the 50th rerventile, a one standard deviation higher

test score would increase his rank to the 85th percentile, a 35

percentile increase. However, fur an individual at the 70th

percentile, a one standard deviation increase would increase his

rank to the 92nd percentile, 22 percentile increase This makes it

difficult to compare results from studies that measure test scores

in standard deviation units. such as Hause (1972), to those that use

percentile units, such as Griliches and Mason (1972) Intelligence

or IQ test scores are generally reported in standard deviation

units-15 points is one standard deviation and the AFOT is

reported in percentile unitsone point is one percentile.

account, the estimated effect of AFQT score will be

muted because the effect of skill differences is then

shared between AFQT and the background characteristics. For this reason, the estimates reported

above understate the extent to which AFQT accounts for racial differences in earnings when only

standard variables, such as schooling, are held

constant.

Social. scientists do not agree on how those skills

reflected in aptitude and achievement test scores are

later reflected in increased job productivity and

earnings, and further investigation beyond the scope

of this report is warranted. Two points do recur

frequently. First, test scores reflect the quality of

earlier educational experiences both in school and at

home. Second, the skills reflected in test scores do

not substitute for, but complement later formal

education and training. The research of Hause

(1972) suggests that individuals who have achieved

more in their early schooling benefit more in

earnings from continuing formal education and from

on-the-job training. The importance of the first point

is that it suggests that racial differences in years of

schooling are likely to understate racial differences

in skills acquired both at home and in school. The

importance of the second point is that the effect on

earnings of racial differences in the quality of

schooling and family background is likely to grow

over an individual's working life. Blacks and whites

who do not acquire learning skills in their early

education will find it difficult to benefit from higher

levels of education and on-the-job training. For

example, a recent study by the Congressional Budget Office finds those who score more highly on the

AFQT are more likely to pass qualifications tests for

" Hanushek (1973) estimates within regions that a 30 percentile

Increase in AFQT score increases earnings by 3 6 percent after

adjusting for schooling Kiker and Liles (1974) estimate that the

same change Increases earnings approximately 54 80 per week in a

sample of individuals whose average weekly earnings were $135

in 1970 D O'Neill (1977) estimates the same change would

increase the weekly earnings by 57 50 and 51.75 in 1974 and 1969,

respectively, in two sample of veterans participating in vocational

training He also shows that the same change increases the growth

in earnings by about SI 25 per week per year D O'Neill finds

that within AFQT categories blacks are more likely than whites

to participate in vocational training, and they benefit from it more

than whites

" There is little evidence on ritual differences in the relationship

between test scores and earnings Hanushek (1973) estimates that

a 30 percentile increase in AFQT score would increase the

weekly earnings of blacks by only 1 5 percent as opposed to 3 6

percent for whites On the other hand, Kiker and Liles (1977)

report results that indicate that the relationship for blacks is very

similar to the one among whites

71
various occupations (particularly higher skill occupations) and are promoted -nore quickly.

Limitations in each of the studies of the relationship of test scores and schooling to earnings,

however, make it difficult to assess the actual

magnitude of the effect." The finding that the

differential in achievement scores for a given level

of schooling has not changed between the mid-1950s

and 1980 suggests that either the differential quality

of schooling remained roughly constant over the

period or that other factors offset any improvement.

Hoitever, the data on school resources reviewed

above suggest that prior to the 1950s, and therefore

for older cohorts, there was a convergence in school

quality."

Summary of Racial Differences in

Educational Attainment

The discussion abov" has described the important

changes in educational attainment of black and

white males from the late 1.9th century to the

present. The principal finding is that blacks have

made enormous gains in educational attainment,

sharply narrowing the gap with whites in years of

school completed. These achievements are even

more remarkable given the large proportion of black

Americans living in the impoverished rural South

during the post-Civil War era and given their lack of

political power during disfranchisement when State

and local governments denied blacks adequate

schooling. Despite these bleak origins, the incrL,:ise

in schooling early in the cf:iitury succeeded in

sharply reducing illiteracy among blacks.

It is clear that public resources allocated to the

schooling of black children increased substantially

over time and that a significant narrowing in the

black-white gap in school resources occurred during

the 1920-1953 period. Some of the relative increase

in school resources for blacks went towards increasing the number of months and years of school

attended (as reflected in grades completed), and

some led to improvements in the quality of a given

number of grades completed. There is no reliable

" Congress of the United States, Congressional I3udget Office,

Quality Soldiers' Costs of Manning the Active Army (June 1986)

" All studies of the relationship bctwer a test scores. schooling,

and earnings are plagued by the lack Jr data The samples are

generally nonrandom For instance, the Thorndike-NBER sample

used by liause (1972) and [Allard (1977) is a sample of individuals

of high ability and good health. The samples ate often small. The

1964 CPS sample used by OnliLhes and Mato!) consisted of only

1.454 men of 11 hum only 4 percent were black The earnings data

arc often inadequate The samples used by Kiker and Liles (1974)

72

way to determine whether the 1 vergence in racial

differences in school inputs over the 1920-1953

period was in fact matched by a comparable con ergence in the knowledge and skills schools are

supposed to provide. No series of national level test

score results is available to make such an assessment.

The differentials in resources in earlier years, however, were so large that it is hard to believe that

differences in school effectiveness did not narrow

along with the sharp convergence in school resources.

Although school quality differences as measured

by test score results may not have narrowed significantly since 1960, it should be noted that all of the

age groups in our data sample, with the exception of

those aged 25-34 in 1980, would have completed the

bulk of their schooling prior to 1960. Thus, successive cohorts in this study would have received their

schooling over the period of convergence in school

resources and, probably, convergence in quality. As

a result years of schooling likely understates true

gains in education, since this measure does not

incorporate the change in school quality.

In evaluating the effect of education on earnings,

two key questions are raised. Can the lower educational attainment of blacks account for mum of the

racial difference in earnings? And, do the trends in

educational attainment account for much of the

convergence in the black-white earnings gap since

1940? We now turn to census data to provide a

preliminary assessment of the effect of years of

school on earnings.

The Effect of Racial Differences in

Schooling on Racial Differences in

Earnings

Differences in education have been identified as a

possible reason why black men earn less than white

men. Therefore, earnings ratios for black ar.cl white

men with the same level of schooling should

generally be higher than the earnings ratio computed for all levels of schooling combined. The presumption is confirmed in table 4.11, which shows

and by tlanusliek (1973) had earnings information at a point only

10 months after the individuals separated from the Army It

should be noted that. considering the large differences in the type

of samples used. the estimated effects of ability on earning are

remarkably similar

" The Comparison between the Rosenwald and the Coleman

data casts some doubt on si.Lh a Lh.nugi. but the Rosenwald data

are quite limited in sLops and are not really Lomparable vtith the

'arge.scale Coleman results

81
black-white ratios of weekly earnings by schooling

level, for selected age groups in each year. Within

each age group, these ratios are generally higher

than the ratios calculated for the larger group of all

schooling levels combined. For instance, the earnings ratio for all men ages 25-34 was 79.4 percent in

1980 while the ratios at specific schooling levels

ranged from 80.5 to 91.5 percent. Because the

quality of schooling as reflected in achievement

levels has been lower for blacks than for whites,

years of schooling alone do not fully capture

educational differences. Thus, the wage gap that

remains after adjusting for schooling is likely to be

partly attributable to qualitative differences.

Although the ratios are higher within schooling

levels, the basic trends in these ratics are usually

close to the year to year pattern observed in the

aggregate ratios. Thus, the convergence in years of

schooling alone does not appear to explain a larg:-

amount of the observed narrowin4 in the earnings

differential from 1940 to 19r.

What, then, does account for the trend in the

earnings ratios, which rose substantially over time

even within dei:ziled schooling and age categories?

One explanation is that real educational gains are not

fully captured by years of school completed.

Schooling levels were not accurately reported in the

earlier decades by blacks because they attended

ungraded schools. As a result, grades of school

completed are likely overstated among blacks, particularly those born before 1910, and the gains in

schooling over time are thus understated. Similarly,

the likely rise in school quality among blacks, at least

up until the 1950s, leads to a further understatement

of the true gain in education. Of course, factors

other than education probably contributed to the

rise in black-white earnings ratios. Various possibilities are considered in subsequent chapters.

A final point pertains to the level of the earnings

ratio itself and the extent to which it can be

44 Kiker and Liles (1974) employ a large sample of men who left

the Army in fiscal year 1969. In this sample blacks earn 11 3

percent less than whites. Adjusting for differences in years of

school reduces difference by only 09 percentage points

However, adjusting by AFQT score (in addaion to schooling)

reduces this difference by an additional 6 8 percentage points. or

more than half of the wage gap

44 Hanushek (1973) does not separate AFQT scores from other

determinants of earningsschooling. experience. and region Hc

also calculates that 72 percent can be accounted fur by racial

differences m the payments recoved for these characteristics

44 Also see D. O'Neill (1970, 1977) and Masters (1975) 4' In addition. it is not dear how the results were affected by

attributed to discrimination. The discussion of differences in the qualitative aspects of schooling suggested that years of schooling alone may not be

sufficient to adjust for racial differences in skills

learned in school. Studies that have attempted to

adjust black-white earnings ratios for differences in

achievement have concluded that a significant part

of the wage gap within schooling groups can be

attributed to such achievement. B.F. Kiker and W.

Pierce Liles (1974) estimate that more than half of

the gap can be accounted for by adjusting for

differences in schooling and AFQT scores." Eric

Hanushek (1973) uses similar data but calculates that

within 26 urban regions, only 17 percent of the wage

gap can be accounted for by differences in schooling, work experience, and AFQT scores between

blacks and whites.45 46 Both of these studies are

marred by the availability of earnings data only 10

months after the individuals separated from the

military. The relationship of AFQT scores to earnings is most evident many years after the tests were

taken.°

Work Experience and On-the-Job

Training

After the completion of formal schooling an

individual's skills continue to develop through training obtained on the job. Training may take any

number of forms, ranging from organized programs

to informal training, or "learning from experience"

(Mincer, 1962). On-the-job training, like schooling,

is an investment in "human capital" that develops

skills and enhances earnings. The worker often pays

for this training in the form of lower wages during

the training period." After the training period,

earnings are expected to rise, reflecting the increase

in productivity.

Black-white differences in on-the-job training, just

as differences in schooling, are expected to affect the

earnings gap. A black-white differential in training

excluding those who returned to &Imol after leaving the military

The average AFQT score is almost certainly higher for students

than workers The earnings of the stc.!e'fi had they chosen to

work. may have been 1111,11er, as they had achieved greater skills

in the past. or may have been lower. as they found It worthwhile

to return to school 44 When on.thejob training produces skills that are specific to

the employer and have no market % aluc elsewhere. the employer

is more likely to pay for the training The worker's earoings.

thereit,re. would not rise as much after the training period They

would rise enough to keep the worker from leaving so the

employer would not lose the investment See Hecker (1975) for a

more complete dtscussion of sp= 1ic .. ,d.c, a: training

C.

73
TABLE 4.11

Black-White Ratios of Weekly Wage and Salary Earnings by Age and Education

Age and

years of school 1940 1950 1960 1970 1980

25-34

0-7 yrs. 59.0 72.3 69.5 75.2 91.5

8-11 62.3 75.1 71.6 75.9 81.6

12 , 61.9 74.2 69.8 77.4 80.5 16+ 61.2 73.0a 69.9 82.0 87.0 Total' 48.9 66.4 63.7 71.7 79.4

35-44

0-7 56.2 69.5 69.6 74.7 83.3

8-11 58.1 74.7 72.9 72.7 77.5 12 50.9 72.4 67.8 73.7 78.5 16+ 34.4a 61.5a 61.4 70.4 74.2 Total' 43.0 60.6 59.5 63.3 70.8

45-54

0-7 51.9 65.6 68.6 73.9 83.9

8-11 56.4 67.4 69.1 74.8 79.1 12 42.4 63.3a 63.7 70.4 78.5 16+ 26.4a 44.0° 52.8 65.3 70.1 Total' 40.2 56.1 56.2 60.5 68.2

'Total includbs those with 13.15 years of schooling, not shown separately

°Sample of fewer than 100 persons

°Sample of fewer than 50 persons and is not a reliableestimate Source' Census of Population. 1940.1980. Public Use Sample

74

83
could arise because of differences in schooling:

evidence suggests that those with more edi cation

also tend to obtain more training." Discrim,natior.,

however, may also limit blacks' access to training.

On-the-job training typically involves the participation of the employer who, because of prejudice, may

deny blacks entry to occupations and activities that

promote skill accumulation. The belief that blacks

are relegated to "dead-end" jobs is, in effect, a

statement that blacks are barred from jobs with a

high component of training that increases skills and

earnings.

Data reporting on-thc-job training directly are

seldom collected. Economists, howel. ,r, have inferred the extent of these training investmeats by

reference to the rise in a worker's earnings as years

of work experience increase. It is expected that the

greater the investment in training, the greater the

rise in earnings.5°

Using Is a rough proxy for work experience,

censu. da, an be examined to determine whether

the earnings of black men increase with work

experience at tic same rate as the earnings of white

men. There are two ways to observe the effect of

age on black-white earnings ratios. One is to follow

black-white ea; ings ratios across age groups in a

given year; the second is to folio .he same cohort

as it ages from one decade to the next. Both methods

can be applied to the data in table 4.12.

The first or "cross-section" method compares

black-white earnings ratios within an education

group for a g:ven year. Moving down ... olum.i in

table 4.12 shows the change in weekly earnings

ratios when younger workers are compared with

older, more experienced workers. Proceeding in this

way generally reveals a pattern of declining relative

earnings for more highly educated blacks as they

age. This effect. however, is only apparent among

high school and college graduates and is minimal

among those with 8-11 years of school. For example, in 1970, among college graduates, the blackwhite earnings ratio falls from 82.0 percent to 58.5

percent over the 30-year span between ages 25-34

and ages 55-64. The decline in ratios for high school " See the theoretical treatmult b'' Becker (1964) and the

estimates by Mincer (1962) showing a positive correlation

between schooling and on-the-job training Other direct evidence

of such an effect comes from a study by D O'Neill (1977)

showing that those who took additional training under the G I

Bill were likely to have more prior schooling than those who did

not. J O'Neill (1983), using the National Longitudinal Survey of

Young Men, finds a positive relationship between education and

graduates over the same ages was 77.4 percent to

68.4 percent, while for those completing 8-11 years

of school, the decline went from only 75.9 percent to

74.9 percent.

These declines may be interpreted as evidence

that discrimination dampens ir.ve-Anent in training

over a worker's life cycle. One problem with this

conclusion, however, is that it relies on a comparison across different cohorts of workers, born in

different periods and each having unique histories.

Thus, the lower earnings ratio of men aged 55-64 in

1960 (among those with 12 years of school) may

simply reflect the overstatement of years of school

of blacks born at the turn of the century who

attended largely ungraded schools (see above) as

well as lower quality schooling or other factors

specific to the cohort.

For this reason several analysts have suggested

that a more appropriate way to examine the effect of

age or work experience on the earnings of blacks

and whites is to trace a cohort as it ages (Council c

Economic Advisers, 1974; Smith and Welch, 1977).

This can be done by reading across the diagonals in

table 4.12.

This procedure reveals a strikingly different pattern, as the black-white earnings ratios usually rise

between census years, except between 1950 and 1960

when the ratio falls for all birth cohorts in all

schooling groups. (The other exception is found for

the cohort of college graduates aged 25-34 in 1970.)

These results show that blacks typically we experienced as great an earnings gain as whites over the

life cycle. But one cannot conclude that blacks and

whites receive the same amount of training, because

the gains made by a cohort as it ages are affected by

temporal forces in the economy and in the legal

environment as well as by work experience.

Some supplementary information provides additional insight into training and skill building. A study

1), Mary Corcoran and Greg Duncan (1978) used

the Panel Study of Income Dynamics to estimate the

effect of work experience on the earnings of black

and white men. Their data contained detailed measures of actual work e.p.trience divided into specific

the months of ,pecific voc'aional training required for current

job. " Th.; steeper ise of earnings with work experience when

training is involved results from the presumption that earnings are

depressed during; the initial period of investment and then rise dt.e

to the enhanced productivity after the training (Becker, 1957)

6 .4

75
TABLE 4.12

Black-White Ratios of Weekly Wage and Salary Earnings by Education and Age

Education and age 1940 1950 1960 1970 1980

8-11 yrs. of school

25-34 62.3 75.1 71.6 75.9 81.6

35-44 58.1 74.7 72.9 72.7 77.5

e 5-54 56.4 67.4 69.1 74.8 79.1

55-64 56.3 69.3 66.3 . 74.9 79.6

12 yrs. of school

25-34 61.9 74.2 69.8 77.4 80.5

35-44 50.9 72.4 67.8 73.7 78.5

45-54 42.4 63.38 63.7 70.4 78.5

55-64 34.38 46.88 56.1 68.4 75.8

16+ yrs. of school

25-34 61.2 73.08 69.9 82.0 87.0

35-44 34.4a 61.58 61.4 70.4 74.2

45-54 26.4a 44.0a 52.8 65.3 70.1

55-64 24.8b 59.8a 46.08 58.5 67.0

'Sample of fewer than 100 persons

bSample of fewer than 50 persons and is not a reliable estimate

Source. Census of Population. 19401980, Public Use Sample.

76

Fi5
segments such as years of training and post-training

experience on the current job. Blacks in the sample

rece!ved lc s on-the-job training than whites. Hoy -

ever, they avt.raged 1.9 less years of formal schooling than whites. i3ecause on-the-job training increases with schooling, it is likely that schooling

differences account for some portion of this training

differential, although clearly discrimination in terms

of access to training may also play a role.

The Corcoran-Duncan study also estimated the

payoff from an additional year of work experience

or training and found that the reward from training

time is no lower for blacks than for whites. These

results suggest that discrimination may not affect the

return from additional on-the-job training although

it could impede the acquisition of skills. The implications of the Corcoran - Duncan study for the relation

between age and earnings are that the earnings of

blacks would not rise as fast with age as those of

si Classifying professional, technical, managerial, and craft

workers as skilled, in 1980, among 35-44 year olds, 60 percent of

white workers and 36 percent of black workers were skilled.

whites because blacks receive less "total" training

(years of training times the return from training).

Concluding Comments

There is evidence that blacks hold less skilled jobs

than whites." Part of this difference is undoubtedly

linked to the lower educational attainment of blacks,

which not only affects skills directly but also does so

indirectly by affecting the amount of training provided on the job. But training differences may also

arise due to other factors, including discriminatory

treatment.

Racial differences in skills developed on the job

have likely ntrrowed, which may account for some

of the convergence in the earnings gap. Educational

gains no doubt have enhanced blacks' opportunities

for training, but declining discrimination may also

have contributed.

These data are based on tabulations from the microdata file of the

1980 census.

6

77
Chapter 5

Geographic Migration and Other Sources of

the Wage Gap

This chapter discusses the effect of geographic

region and migration, of industrial sector, and of

marital status on the earnings of black and white

men and on the trend ;n the earnings differential.

Geographic Location and Migration

The fact that a disproportionate share of the blacx

population lives in the South, where wages have

historically been low, accounts for some of the gap

in earnings between black and white men. Furthermore, the large-scale migration of blacks from the

low-wage South to the high-wage North, which

lasted through the 1960s, raised average black wages

and contributed to narrowing the wage gap. This

section examines these assertions.

The concentration of blacks in the South is

apparent from the regional distributions of white and

black populations presented in table 5.1. In 1940

more than three-fourths of the black population

lived in the South, and even in 1980, despite decades

of outmigration, more than half still were found in

the South. The fraction of whites in the South, in

contrast, grew from roughly 25 percent in 1940 to 31

percent in 1980.

i The higher incomes obtained from industrialization in the

North predate the exodus of blacks from the South that occurred

after 1940 an raise the question of why stronger migration was

not observed earlier The high rate of illiteracy in the post-Civil

War period, the isolation of blacks in rural areas, and the lack of

information and finances needed to move are obvious factors. In

addition, until the outbreak of World War 1, the inflow of foreign

Immigrants may have been an impediment to black migration to

northern urban centers However, during the war foreign imini78

Differences in earnings between the South and

non-south for men ages 25-34 are presented in table

5.2. Earnings are lower in the South at all educational levels, but the difference is generally much larger

among workers with fewer than 12 years of school

and is much larger for blacks than whites. It is also

apparent that regional earnings differences have

narrowed over time. By 1980 between-region differences were no longer as important a factor in

explaining black-white differences in earnings as

they had once been.

The migration of blacks from the rural South to

the industrial centers of the North is one of the most

important demog-aphic phenomenons of this century. Between 1910 and 1970, the fraction of blacks

who lived in the North quadrupled from roughly 10

percent to nearly 40 percent (see table 5.1).1 This

shift, together with migration to the West, reduced

the proportion of biacks living in the South from 89

percent in 1910, to 77 percent in 1940, and to 53

percent by 1970. In comparison, the regional distribution of whites changed more modestly over this

period as the North lost population and the West

gained.

gration slowed sharply, and after the war legal barriers to

immigration were erected. Thus between 1914 and 1929, with

blacks having attained much more schooling and resources,

improving job opportunities attracted significant numbers to the

North Between 1910 and 1930, the share of blacks living in the

North doubled from 10.4 percent to 20 3 percent This flow was

suspended during the Great Depression, which hit manufacturing

especially hard.
TABLE 5.1

Regional Distribution of Racial Groups

Year NE

Black

NC South West NE

White

NC South West

1890 3.6 5.7 90.3 0.4 31.1 39.8 23.9 5.2

1900 4.4 5.6 89.7 0.3 30.9 38.6 24.7 5.8

1910 4.9 5.5 89.0 0.5 31.0 35.8 25.1 8.0

1920 6.5 7.6 85.2 0.8 30.5 35.0 25.5 9.0

1930 9.7 10.6 78.7 1.0 30.1 33.7 25.1 9.8

1940 10.7 11.0 77.0 1.3 29.2 32.7 26.8 11.3

1950 13.4 14.8 68.0 3.8 27.7 31.2 27.3 13.8

1960* 16.1 18.8 59.9 5.8 26.1 30.2 27.4 16.3

1970 19.2 20.3 52.0 7.5 24.9 29.1 28.4 17.6

1980 18.3 20.1 53.0 8.5 22.3 27.1 31.3 19.3

'First year to include Alaska and Hawaii

Sources U S Bureau of the Censis Historical Statistics of the U S Colonial Times to 1970, Series A172-194, p 22, Statistical Abstract 1982-83

TABLE 5.2

Rates of Net Migration from the South for Men Ages 20-24

Black White

1940-50 26.3% 1.8%

1950-60 24.5 8.4

1960-70 19.3 3.3

1970-80 2.1 -1.3

Note These rates were calculated by comparing the share of males ages 20-24 y ?R... old living in the South inyear t to the share of males ages 30-34 years old living the South in

year t+ 10

Zt 3

79
Migrants typically are young.2 Net migration

rates from the South (see table 5.2) for the particularly mobile group of young men ages 20-24

illustrate more clearly the exodus that took place

among blacks from the 1940s through the 1960s. On

balance there was net loss of about 25 percent of

black men in the South in each of the decades

between 1940 and 1960 and an additional 19 percent

drop during the 1960s. These figures also show that

net losses of blacks in the South came to a virtual

halt during the 1970s. It was the first decade of the

century, in fact, that the share of blacks living in the

South did not decline. In contrast, while many

whites left the South, even more came in. Net

changes in the white population during this entire

period were modest, underscoring the point that

large net outflows from the South were a distinctly

black phenomenon.

The reasons for the substantial South-North flow

of blacks are readily surmised. First, the pecuniary

gain from migration was undoubtedly large. According to table 5.3, a black male (aged 25-34) with

0-11 years of school in 1940 might increase his

income by 66 percent if he moved from South to

North.' A white male of the same age and with the

same schooling could increase his earnings by half

that amount. The larger regional differentials in

earnings for blacks than for whites may reflect

greater discrimination in the South with respect to

both pay and opportunities for occupational advancement. It may also reflect the relatively higher

wages for unskilled labor in the North than in the

South, since blacks were in less skilled jobs within a

schooling level.

Aside from monetary reasons, a second factor

motivating blacks to leave the South is likely to have

been tht .videspread legal discrimination in all areas

of life that existed for blacks in the decades before

the Civil Rights Act of 1964. Unequal access to

schooling and other governmentally provided services as well as the strict segregation of public

Older workers arc less likely to migrate because the payoff

from gec aphi migration falls with age Accumulated work

experience typically generates a payoff that is specific to a

worker's firm or locality and is not easily transferred from one

pla le to another Moreover, older workers have fewer years left

in the work force than the younger ones and thus accrue smaller

lifetime benefits from moving to a better job In addition, the cost

of migration rises with age Older workers have established close

bonds o their communities, creating a psychic cost to moving,

and they ;Ind to be tied to larger families, which imposes a higher

monetary cost to moving

80

facilities undoubtedly provided an added impetus for

blacks to move northwards.

Migration of blacks to high-wage areas in the

North is expected to have raised black earnings

relativz to white earnings. On the other hand,

several factors were at work that generated faster

improvement in the relative position of blacks in the

South than in other regions. Among these are

relative gains in educational attainment and school

quality in the South, and a decline in legal segregation. In addition, the large outflow of blacks reduced

the supply of labor to occupations and industries

that blacks had filled, and this would have put

upward pressure on wage rates. Table 5.4 shows that

black-white earnings ratios, although still somewhat

lower, hake grown much more rapidly in the South

than in other regions. Between 1970 and 1980, for

example, relative earnings grew by more than 9

percentage points in the South but less than 4

percentage points outside the South. As a result,

differences in the earnings gap between the South

and the rest of the country have narrowed considerably over the years.

Summary

Historically, an important reason for low relative

earnings among black males has been the disproportionately heavy concentration of the black population in the South whe:e wages are low in comparison with other areas. Net migration of blacks from

the South to the high-wage urban areas of the North

between 1940 and 1970 is believed to have reduced

the earnings gap. Net migration flows during the

1970s were essentially zero. Moreover, the more

rapid economic growth in the South relative to

other regions has gradually nat.-owed the NorthSouth earnings gap, especially among blacks. Consequently, the effect of southern location on both the

earnings gap and trends in the gap was considerably

less important after 1970.

This is likely to overstate the gain The cost of living may have

been lower in the South. Agricultural workers. who were more

concentrateo in the South, received income in kind (such as food

or housing), which would not be reflected in the incomes

reported. Differences in skill between northern and southern

workers (for example, due to differences in school quality) may

further account for some of the differential Nonetheless, given

the substantial differential observed, it is probable that blacks

could increase their incomes significantly by moving from the

South to the North.
TABLE 5.3

Annual Wage and Salary Earnings of Men Ages 25-34 by Race, Region, and Education

Year and

education

1940

South

White

Non-South

NorthSouth

gap' South

Black

Non-South

NorthSouth

gap'

0-11 788 1,033 31.1 433 717 65.6

12-15 1,309 1,362 4.0 647 896 38.5

16+ 1,819 1,866 2.6 906 1,2C3 40.1

1950

0-11 2,192 2,597 18.4 1,338 2,073 54.9

12-15 2,925 3,007 2 8 1,785 2,220 24.4

16+ 3,202 3,355 4.8 2,255 2,414 7.1

1960

0-11 3,614 4,476 23.9 2,163 3,398 57.1

12-15 4,727 5,310 12.3 2,832 3,787 33.7

16+ 5,912 6,352 7.4 3,678 4,631 25.9

19711

0-11 5,953 7,201 21.0 4,151 6,031 45.3

12-15 7,703 8,536 10.8 5,432 6,916 27.4

16+ 9,813 10,120 3.1 7,064 8,838 25.1

1980

0-11 11,100 11,529 3.9 8,759 9,585 9.4

12-15 14,354 15,298 6.6 10,989 12,486 13.6

16+ 17,778 17,788 0.1 14,398 15,699 9.0

'Percentage by which earnings in non South exceed earrogs in the South

Source Census of Population 1940430. Public Use Sample

81

90
TABLE 5.4

Black-White Weekly Wage and Salary Ratios by Region and Age

1940 1950 1960 1970 1980

South

25-34 47.4 59.4 57.6 65.6 77.1

35-44 40.9 54.5 52.2 57.8 67.9

45-54 36.5 50.6 50.2 53.7 63.4

55-64 34.9 53., 46.5 53.6 59.2

Non-South

25-34 66.9 79.4 74.0 80.2 84.9

35-44 55.4 73.8 70.0 71.0 76.1

45-54 51.9 66.8 68.1 70.1 75.1

55-64 53.1 67.5 68.2 70.8 74.1

Note Tabulations based on wages and salanes of individuals who worked in the preceding calendar year Self-employed and unpaid family workers are excluded

Source. Census of Population le40-1980. Public Use Sample

Industrial Sector

This section examines trends in employment

across the three broad industriai sectors-agriculture, private nonagriculture, and government-and

trends in earnings and racial differences in earnings

within and between these sectors. It is well known

that agricultural employment, as a fraction of the

total, has been falling since the 19th century, and

precipitousl., during the early decades of this century. Since blacks were largely located in the rural

South, this change in agricultural employment plays

a particular!, important role in their economic

history.

Among whites, the proportion in agriculture fell

from 20 percent to 4 percent between 1940 and 1980,

with most of the decline coming in the first half of

this period (table 5.5). Among blacks, the decline in

agricultural employment was an exodus (table 5.6).

In 1940 about 38 percent of all black males were

employed in agriculture; by 1980 less than 3 percent

were so employed. C / ( i

82

In discussing migration, it was noted that older

individuals are generally less mobil( than the young.

mhe same basic arguments apply to industrial mobility. Workers typically accumulate skills and employment ties that are specific to their occupation and

industry, if not their employer, which means that

experienced workers will generally require a stronger incentive to move into a new industry than

recent entrants. In this light, the forces that caused

the decline in agricultural employment were indeed

powerful. Not only did a greater fracL'on of young

workers enter nonagricultural employment, but older workers made midcareer switches into nonagricultural jobs. This point can be demonstrated by

tracking the agricultural employment of experienced

workers over time. For example, the share of 35-44

year old workers employed in agriculture in 1940

can be compared with the share of this cohort

remaining in agriculture 10 years later when they

were 45-54 years old. Table 5.7, using 35-4 year

olds as the base group in each year between 1940
TABLE 5.5

Distribution of White Male Labor Force by Sector and Age

1940 1950 1960 1970 1980

Agriculture

25-34 15.1 10.8 5.6 3.3 3.3

35 44 16.1 11.9 6.6 4.2 3.6

45-54 19.4 13.6 8.6 5.2 4.2

55-64 25.4 16.3 10.4 7.7 5.3

Total 19.5 13.5 7.9 5.1 4.3

Private nonagriculture

25-34 75.3 79.7 83.4 82.9 82.6

35-44 74.4 79.3 82.1 81.7 81.3

45-54 71.6 77.2 80.3 79.5 79.7

55-64 66.5 74.4 78.4 78.0 78.6

Total 71.9 77.9 81.6 81.3 82.1

Government

25-34 8.6 9.5 11.C, 13.8 14.1

35-44 9.5 8.8 11.3 14.1 15.1

45-54 8.9 9.2 11.1 15.4 16.2

55-64 8.1 9.3 11.2 14.3 16.1

Total . . . 8.6 8.6 10.5 13.6 13.5

Source Census of Popu.ation. 1940.1980 Public Use Sample

,Ind 1970, shows the percentages cf agricultural

workers leaving agricultural employment over the

next decade.

As agricultiira! employment declined, jobs increased in private nonagricultural industry and

substantially in government (defined as Federal,

State, and local employment). Moreover, growth in

government employment has been considerably

more rapid among black men than among white

men. In 1940, for example, only 6 percent of black

and 9 percent of white men were employed in the

government sector. By 1980 the, percentages 'lad

increased to about 23 percent for blacks and 14

percent for whites. All other workers are included it

the private nonagricultural sector. Of all the sectors,

the private nonagricultural sector is the largest, and

its relative size has generally increased over time

with the expansion of services and industrial production and the contraction of demand for agricultural

labor.

The relatively large concentration of black workers in low-paying agricultural jobs accounts for

some of the black-white differential in earnings,

especially before the 1960s. Moreover, shifts in

employment away from agriculture have apparently

moved woriters, particularly blacks, into higher

paying jobs in government and industry, and this

accounts for some of the observed narrowing in

earnings differences. These trends appear to have

run their course, however. Industrial patterns of

employment were important for explaining racial

differences in earnings as long as blacks were

disproportionately employed in low-wage industries.

The restructuring of employment during the 1940-

1980 period, most of which occurred before 1970,

weakened this relationship considerably and hence

the importance of any remaining employment differences in explaining the black-white earnings gap.

83
TABLE 5.6

Distribution of Black Male Labor Force by Sector and Age

1940 1950 1960 1970 1980

Agriculture

25-34 32.5 16.6 8.2 4.0 1.9

35-44 29.3 17.3 9.0 4.4 2.3

45-54 36.0 19.7 12.2 5.9 3.3

55-64 48.2 27.2 15.7 9.8 4.7

Total 37.6 21.0 12.0 5.8 2.8

Private nonagriculture

24-34 61.8 73.0 78.0 78.9 76.5

35-44 63.7 73.8 -, 6.4 75.9 75.9

45-54 57.1 71.9 76.9 74.0 71.3

55-64 45.4 66.1 74.3 73.9 69.8

Total 56.5 70.9 76.1 75.8 74.7

Government

25-34 5.7 10.4 13.8 17.1 21.6

35-44 7.0 8.9 14.6 19.7 21.8

45-54 6.9 8.4 11.9 20.1 25.3

55-64 6.5 6.7 10.0 16.4 25.5

Total 5.9 8.1 11.9 18.4 22.5

Source: Census of Population. 1940-1980; Public Use Sample.

TABLE 5.7

Male Workers Ages 35-44 Leaving Agriculture Over the Decade

Black White

1940-50 33% 16%

1950-60 29 28

1960-70 34 21

1970-80 25 0

Note These rates were calculated by subtraCting the share of males ages 45-54 in the agricultural labor force ,n year 1+10 from the shale of males ages 35-44 in the agncultural

labor force in year t and dividing the remainder by the share in year t

84 kit)
TABLE 5.8

Percentage by which Weekly Earnings of Married Men Exceed Weekly Earnings of

Unmarried Men

Age group

and race 1940 1950 1960 1970 1980

25-34

Black 6.7 6.4 16.2 12.7 16.8

White 23.0 21.2 21.7 20.3 21.3

35-44

Black 10.7 8.2 12.6 14.5 15.9

White 32.9 26.5 28.3 24.9 19.4

45-54

Black 15.0 16.2 13.3 21.4 20.6

White 40.7 31.3 32.1 31.2 22.2

55-64

Black 16.8 11.5 13.8 20.5 19.3

White 42.3 30.0 30.3 29.5 22.0

Nets, Data for 1940 based on an °shan't. of hourly earnings, Annual earnings are divided by "fulltime equivalent" weeks times 40 hours, assumed to bea f ull.time week Source: Census of Population, 1940-1990; Public Use Sample.

Marital Status

Married men earn more than unmarried men. One

possible reason for lower relative earnings of black

men is that, in comparison with white men, they

have a lower marriage rate.' The underlying source

of the higher earnings of married men is believed to

be the traditional division of labor within the family

in which the husband has primary responsibility for

earning an income while the wife attends to child

rearing and other household chores. Married men

are known to work longer hours and may increase

the intensity of work in other ways as wel1.5 (The

causality may also run the other way if single men

are simply low earners whom women will not

marry.)

The earnings advantage associated with marriage

is shown, by race, age, and year, in table 5.8.

Historically, the differential has been greater among

The term "married," as used here, refers only to a married

individual whose wife is present. All other persons are "unmarried." In 1940 the "married" group includes some married men

whose spouses ate absent for reasons other than separation The

frequency of such "other" absences among men is likely to be

low.

whites than blacks, but the difference between them

has narrowed considerably over ..zne. For example,

among 25-34 year olds in 1940, married white men

earned 23 percent more than unma ried men

whereas the premium was only 7 percent for black

men. By 1980 the black rate had jumped to 17

percent, in comparison to a relatively stable rate of

21 percent for whites.

Table 5.9 displays the corresponding proportions

of married men with spouse present. It is evident

that white men are generally more likely to be

married than are black men and that this difference,

small or negative in 1940, has increased steadily over

time. Another striking fact is that the proportion of

married men, both white and black, has been falling

since 1960, especially after 1970, and for 25-34 year

olds.'

See Bernard (1972) for a more thorough discussion of the

relationship between male earnings and marriage.

Census enumeration undercounts blacks relative to whites and

i4

85
TABLE 5.9

Proportion of Men Married with Wife Present by Age and Race

Age group

and race 1940 1950 1960 1970 1980

25-34

Black .740 .724 .740 .737 .563

White .717 .803 .828 .822 .692

35-44

Black .819 .794 .789 .764 .704

White .844 .870 .895 .887 .837

45-54,

Black .799 .767 .789 .767 .719

White .843 .852 .886 .892 .864

55-64

Black .765 .721 .757 .756 .742

White .803 .809 .856 .874 .881

Source Census of Population. 1940-1980 Public Use Sample

86

5S
TABLE 5.10

Black-White Ratios of Weekly Earnings by Marital Status and Age

Marital status

and age 1940 1950 1960 1970 1980

Married

25-34 47.2 65.3 64.1 71.7 80.2

35-44 42.2 59.9 59.5 63.8 71.9

45-54 39.6 56.1 56.1 61.4 69.8

55-64 39.6 54.9 54.9 60.6 67.0

Unmarried

25-34 54.4 74.4 67.2 76.5 83.2

35-44 50.6 70.1 67.8 69.5 74.0

45-54 48.5 63.4 65.4 66.4 70.7

55-64 48.3 64.0 62.9 65.1 68.5

Source Census of Population. 1940.1980. Public Use Sample

87
These data ,uggest the possibility that the lower

propensity of blacks to be married may have

dampened their earnings. If so, relative 1...qa,:k-white

earnings should be higher within marital groups than

overall.' Table 5.10 presents black-white ratios of

weekly earnings by marital status, region, age, and

is more likely to miss single men As a result. the figures reported

in table 5.9 probably overestimate the true proportions of married

men and understate the black-white difference.

88

year, which generally are higher than ratios not

stratified by marital status (table 1.3 in chapter 1).

The apparent effect is quite modest, however,

suggesting that marital status, while an important

correlate of earnings, does not play a large role in

explaining racial differences in earnings.

' In the limit the ratios Mould be one if marital status were the

only reason for earnings differences
Chapter 6

A Multivariate Analysis

Previous chapters suggest that racial differences

in earnings partly result from racial differences in

education, region of residence, work experience,

industry of employment, Ind marital status. Those

chapters, however, considered the relation between

earnings and each factor separately from the others.

The primary task of this chapter is to measure the

joint effect of all these factors on the black-white

earnings gap and how they have influenced the gap

over time.

Two key questions are addressed:

What percentage of the black-white earnings

gap in each year (1940-1980) can be attributed to

racial differences in worker characteristics?

What portion of the change in the gap from

decade to decade is due to changes associated

with these factors?

The specific statistical technique used to address

these questions is multiple regression, which simultaneously evaluates the effects of several factors on

earnings. In so doing, it permits us to assess how

racial differences in these factors individually and

collectively affect the earnings gap and the trend in

the gap over time. The factors used in the analysis

have all been discussed at length in previous chapters. They are known to be important determinants

of earnings and, important to a historical analysis,

are defined consistently in all of the censuses of the

population between 1940 and 1980. Defined precisely, these factors are:

' A two-segment linear spline function is used to capture the

differential effects on earnings of an additional )....ir of schooling

for 0-12 years of school and for 13 and over years of school 2 Notable determinants of earnings omitted include direct

measures of skills derived from formal schooling mid on-the-job

training, and other characteristics that relate directly to job

performance or ability to learn new skills, such as family

background.

For example, the coefficient associated with schooling measures the percentage gain in earnings for each additional year of

school. Suppose each year is estimated to yield a return of 8

percent. Then 12 years of education would provide an increase in

earnings equal to 8 percent compounded over 12 years. or

roughly P/2 times what earnings would be without any education.

A similar example would apply to experience.

Years of schooling completed (separate effects are

measured fcr years 0-12 and 13 and over)'

Potential years of work experience (the number of

years since leaving school: person's age years of

schooling 6)

Region of residence (whether worker lives in the

Northeast, North Central, West, or South.)

Industrial sector of employment (whether worker

is employed in private nonagricultural industries,

civilian government, agriculture, or the armed

forces)

Marital status (whether a person is married,

spouse present.)2

Using the regression technique, each characteristic is linked to weekly earnings by a coefficient

which measures the change in earnings that, on

average, results from a change in the level of the

characteristic.' That is, coefficients provide a

measure of the gain in weekly earnings associated

with an increase in the characteristic. Separate

estimates of each characteristic's coefficient are

made for each census year, for black and white men,

and for 10-year age groups. Since coefficients are

tied to earnings, differences in estimated coefficients

between black and white men can help to account

for differences in their average earnings. Coefficient

differences, however, can arise for several reasons,

including omission or mismeasurement of important

determinants of earnings, labor market conditions,

and labor marki:t discrimination. Although inferRegion, industry. and marital status. however. are somewhat

different. The term "level" refers to a category of the characteristic in which an individual may ye observed For example. region

has four categories or "levels" corresponding to four regions A

change in levels. then, means a switch from one category, c g,

region. to another and the (percentage) difference m earnings is

associated with being in one category versus another

Some determinants of earnings could not be explicitly included m

the analysis The effects of some of these may be reflected in

estimates of the coefficients of included characteristics School

quality. for example. will influence the coefficient on years of

school

89
ences can sometimes be made as to why coefficients

differ, such explanations are speculative and must be

treated as such.

Thus, two groups of workers may earn different

incomes if they possess different characteristics or if

the coefficients differ. Formally, the difference in

their earnings is the sum effect of the two sources:

differences in average characteristics and differences

in coefficients. This basic dichotomy is used in

performing the analysis.'

A major reason for doing this analysis is to

provide insight into the extent to which the racial

gap in earnings can be attributed to current labor

market discrimination. The five explanatory variables defined above are believed to be reasonably

free of such labor market discrimination although

schooling clearly has been affected by the past

discrimination of State and local governments in the

allocation of school resources. Variables such as

occupation have been excluded from the analysis

because it is ambiguous whether they reflect skill or

reflect discrimination in job entry or promotion. To

the extent current labor market discrimination is

reflected in the analysis, it must be a factor contributing to racial differences in coefficients. Since

coefficients can vary for reasons other than discrimination, the collective effect of differences in estimated coefficients can only be used to establish an

approximate upper bound on the effect of labor

market discrimination on the earnings gap.5

The analysis is discussed in the following sequence. The first section looks at the sources of the

earnings gap in each census year from 1940 to 1980.

The portion of the gap due to racial differences in

worker characteristics is estimated for various age

groups and each census year. This procedure is

applied to all characteristics collectively and then

individually. In the second section, a similar procedure is used to assess how much of the decade to

decade change in the earnings gap reflects changes

in the characteristics of black and white workers.

Accounting for the Earnings Gap

Differences in worker characteristics may account

for part of the earnings gap. The extent of the effect

can be estimated by calculating the change that

4 The specific technique used to answer these questions is called

regression decomposition (Blinder, 1973, Oaxaca, 1973) and is

described in further detail in app. C.

Rosen's work (1978) demonstrates, however, that the payoff

rate for particular skills may not be ecual for workers who apply

90

would occur in the earnings gap if the average black

worker were to possess the same characteristics as

the average white worker. In this way the part of

the earnings gap attributable to racial differences in

characteristics would be eliminated. Any gap remaining after characteristics are equalized must be

due to differences in coefficients.

Table 6.1 shows three ways of measuring the

results of applying this procedure: (1) as an adjusted

ratio of earnings (column 2); (2) as a percentage

increase in black earnings when white characteristics are assigned (column 3); and (3) as the percentage of the earnings gap eliminated (column 4). The

discussion focuses on young men 25-34, but the

observations noted usually apply to the other age

groups as well.

Between 1940 and 1980, the unadjusted earnings

ratio for young men (column 1) increased from 4-7

to 78.8 percent. However, after adjusting for racial

differences in schooling, regional and industrial

distributions, etc., the earnings ratio is 70 percent in

1940 and increases to 87.4 percent by 1980. Thus

racial differences in the five characteristics included

in the analysis are an important reason for the low

relative earnings of blacks. For example, the earnings of black workers aged 25-34 would have

increased by nearly 44 percent in 1940 had their

characteristics been the same as those of whites (see

column 3). By 1980 the adjustment for racial

differences in characteristics raises earnings for this

group by only 11 percent. The main reason for this

smaller effect is that racial differences in most

characteristics have narrowed. Consequently, there

are simply fewer gains to be squeezed from remaining differences.

The share of the earnings gap (column 4) due to

the effect of racial differences in characteristics has

been substantial and roughly constant over time,

generally around 40 percent for men 25-34. (The

same is true for the older cohorts, but the share is

somewhat smaller, roughly one-third.) The remaining earnings differential can be attributed to racial

differences in coefficients which, as noted, reflect

unmeasured factors that were necessarily omitted

from the analysis.8

them to different kinds of jobs, e g., physical sire; gth may not

have the same payoff in sedentary jobs as it does in jobs requiring

significant physical effort. Also see the discussion in chap. 3 of

empirical issues in measuring discrimination.

(Ci 9
Individual characteristics can be examined in

much the same way as the collective effect of all

differences in characteristics. In each case the

earnings of an average black male are recalculated

assuming that he possesses the average white male's

level of the particular characteristic. For example,

for schooling we calculate what the average black

worker would earn if he had completed the same

years of schooling as the average white worker

without changing any other characteristic. This

procedure is repeated for each characteristic. The

influence of each characteristic on the black-white

earnings gap is presented in table 6.2 for two age

groups.'

The most important racial differences appear in

schooling and regional patterns of residence.

Schooling differences among young men alone

account for over a quarter of the earnings gap in

1970 and 1980, and a smaller share in earlier years.

Despite the somewhat smaller proportional effect on

the earnings gapbefore 1970, schooling differences,

nevertheless, account for significant absolute differences in earnings.

Among mature men, ages 45-54, schooling differences tend to explain less of the earnings differential.

However, this does not indicate smaller black-white

schooling differences in comparison to young men

but rather that schooling appears to contribute less

to the earnings of older men.8

The heavy concentration of blacks in the South is

also confirmed to be an important reason for the

earnings gap, but the regional effect has abated over

the decades. In 1940, at a time when a disproportionate share of blacks lived in the low-wage South, 19

percent of the earnings gap among men 25-34 would

have been eliminated by redistributing the black

population to match the location of whites.9 During

the next 40 years, however, a large number of blacks

migrated out of the South, causing black and white

6 An alternative approach is to ask how white earnings would

change if white men possessed the same characteristics as the average black man. The first way is reported here because It

seems more natural to inquire how much blacks would benefit if

they had the typically greater endowments of schooling and other

factors of whites. When the second approach is followed (see

tattle C.2, app. C), differences in charactenstics generally "explain" more of the earnings gap-40-50 percentthan the first

approach. Thus, the estimated effects of differences in characteristics reported in table 6.1 are likely to be on the low side. The

disparity between the two approaches stems from raual differences in estimated regression coefficients

7 Table 6.2 corresponds to column 4 of table 6.1

Among older cohorts in earlier decades, mismeasurement of

schooling completed may account for the apparent low value of

schooling and, hence, small effect of schooling differences Low

school quality for older blacks is another possible explanation

population distributions to bt come more alike.

Moreover, wages in the South began to catch up to

northern level?, mg this period due to outmigration of workers and strong economic growth in the

South, among other reasons. Both population and

wage trends diminished the role of remaining regional differences in explaining the gap: by 1980

regional differences accounted for less than 11

percent of the gap among young workers.

Racial differences in industrial employment patterns were relatively significant in 1940, when many

blacks were still agricultural workers, but explained

only a modest 8 percent of the gap among young

men. In terms of the broad sectors defined in this

study, massive flight of black labor out of agriculture during the 1940s sharply reduced racial differences in industrial patterns and, hence, reduced the

effect on the black-white earnings differential.

Lower marriage rates among blacks appear to

explain little of the earnings gap. It is worth noting,

however, that their effect increased fairly sharply

between 1970 and 1980, from 2.7 to 7.5 percent of

the gap among young men. This upward trend

appears to be due largely to a relative increase in the

"marriage premium" among black men compounded

by a decline in their propensity to marry. As

indicated in chapter 5, causality between earnings

and marriage can run both ways, so the increasing

size of the marital premium potentially can stem

from several different sources.

On the whole, racial differences in the few

measurable characteristics available in census data

explain a substantial share of the earnings differentialroughly 30-40 percent. This leaves an "unexplained" earnings differential that corresponds to an

earnings gap of 12.6 percentage points (for 25-34

year-olds) in 1980.10

9 This experiment is somewhat arbitrary because if the population were actually redistributed, corresponding changes would

occur in the structure of payoffs among regions if not other

characteristics As discussed in chap 5. moreover, the NorthSouth earnings differential may reflect unmeasured regional

differences in skill levels of workers.

'° Studies using more detailed data with superior measures of

worker characteristics have been able to attribute 50-70 percent

of the gap to differences in characteristics See. for example,

Corcoran and Duncan (1979). who use the Panel Study of Income

Dynamics to investigate black-white differences in earnings and

explain about 50 percent of the gap Analysis using the NV" nal

Longitudinal Survey Young Men's Panel (for men aged 25-34 in

1976). explains 70 percent of the gap (O'Neill. 1983)

100

91
TABLE 6(.1

Effects of Differences in Characteristics of the Wage Gap

Increase in

Black-white earnings ratio: .-tamings ratio Percent of gap

adjusting for due to differences

Unadjusted Adjusted° characteristicsb in characteristicsb

1940

Ages:

25-34 48.7 70.0 43.7 41.5

35-44 . 44.9 60.6 35.0 28.5

45-54 42.7 58.4 36.8 27.4

55-64 42.6 57.7 35.4 26.3

1950

Ages:

25-34 64.9 79.2 22.0 40.7

35-44 59.3 74.5 25.6 37.3

45-54 56.3 67.7 20.2 26.1

55-64 54.2 69.0 27.3 32.3

1960

Ages:

25-34 62.3 75.1 20.5 34.0

35-44 58.4 72.7 24.5 34.4

45-54 55.7 71.1 27.6 34.8

55-64 53.2 68.3 28.4 32.3

1970

Ages:

25-34 70.3 81.5 15.9 37.7

35-44 62.8 74.9 19.3 32.5

45-54 59.5 73.9 24.2 35.6

55-64 58.9 74.4 26.3 37.7

1980

Ages:

25-34 78.8 87.4 10.9 40.6

35-44 70.5 80.9 14.8 35.3

45-54 67.5 77.9 15.4 32.0

55-64 65.0 75.7 16.5 30.6

eASsumes that black males have the average charactenstics of white workers These charactenstics consist of ,ears nt schooling completed, years of potential work since

school, region of residence, industry of employment, and mantel status

bill's Is the percentage increase in the earnings ratio when white charactenstics are assigned

c[Column #2 - Column #11/(100 - Column #1) X 100

92

101
TABLE 6.2

Effect of Differences in Individual Characteristics on the Black-White Differential by

Selected Age Groups

Percentage of earnings differential explained

1940 1950 1960 1970 1980

Ages 25-34

Schooling 17.2 17.7 17.8 26.9 27.4

Region 18.9 19.4 14.1 11.8 10.8

Industry 7.8 to 3.7 2.0 2.4

Marital status -0.2 1.7 2.4 2.7 7.5

Ages 45.54

Schooling 3.5 3.2 7.2 14.1 15.7

Region 13.3 14.6 15.6 11.1 8.3

Industry 7.0 3.0 5.9 2.5 0.9

Marital status 0.3 1.8 1.8 4.0 6.2

Note Figures express the percentage contribution of each characteristic to the earnings gap that would be expected if black men had the white mean level of the indicated

charactenstic Racial Differences in Coefficients

Sixty to seventy percent of the earnings differen

tial cannot be explained by black-white differences

in census-measured characteristics. Formally, this

residual is attributed to racial differences in the

coefficients that link earnings to the characteristics.

This section examines estimates of coefficients for

black and white men ages 25-34 (see table 6.3;

appendix C presents coefficients for other age

groups). The coefficients associated with schooling

and potential experience measure the percentage

gain in earnings, or return, associated with a year of

school and experience, respectively. Region, industry, and marital status are categorical variables,

meaning they classify individuals into categories and

have coefficients that are interpreted somewhat

differently from the continuous schooling and experience variables. Region, for example, classifies

people according to whether they live in the

Northeast, North Central, South, or West. The

coefficient associated with living in a particular

region is the percentage difference (i.e., change) in

earnings between that region and another selected to

be a reference group. Industry and marital status

coefficients, similarly, measure differences between

each category (e.g., agriculture, government) and

the reference group (e.g., private nonagriculture).

Schooling

Because the monetary return from completing a

year of school is believed to vary with grade, two

separate coefficients are estimated: one for 0-12

years of school completed and one for years beyond

12. Generally blacks receive a lower return on

schooling than whites, particularly ir, the 0-12 years

range (table 6.3, panel A). These differences lessened

significantly, however, over the 1940-80 period. For

example, estimates indicate that among individuals

ages 25-34 in 1960, whites' earnings increased 3.9

percent more per year of school than those of their

black counterparts (i.e., 8.0 minus 4.1) for the first 12

years of school. By 1980 differences in coefficients

had narrowed for this age group to 2.3 percent in the

first 12 years while years of college apparently

rewarded blacks slightly better than whites.

These coefficient differences are large and suggest

the potential importance of the monetary return on

schooling in explaining why blacks earn less than

whites. Similarly, it is apparent that the earnings gap

has narrowed over time, in part, because racial

differences in schooling coefficients have narrowed.

102

93
TABLE 6.3

Estimated Effects of Worker Characteristics on Weekly Earnings of Men Ages 25-34 by

Race (in percentages)

1940 1950 1960 1970 1980

Panel A: Years of schooling'

0-12 years

Black 4.2 2.9 4.1 5.6 7.0

White 8.3 5.9 8.0 7.6 9.3

13+ years

Black 7.7 3.8 5.2 7.3 7.1

White 9.9 4.8 6.9 7.8 6.9

Panel B: Years of potential work experience2

Black 1.7 0.8 1.5 1.7 2.5

White 3.2 2.3 3.0 2.9 3.5

Panel C: Region (reference = Northeast)3

North Central

Black 2.3 5.7 6.5 5.0 15.4

White 6.3 2.0 2.6 - 0.3 6.0

West

Black 0.6 9.5 1.0 3.9 5.3

White - 1.7 7.8 6.1 0.8 5.1

South

Black -32.2 -25.2 -26.9 -22.1 5.1

White -17.4 6.9 -10.0 -10.4 1.6

94

1 r, 3
TABLE 6.3 (Cont'd.)

Estimated Effects of Worker Characteristics on Weekly Earnings of Men Ages 25-34 by

Race (in percentages)

Panel D: Industrial sector (reference = private nonagriculture)4

Agriculture

Black -49.6 -48.6 -47.1 -41.4 -34.8

White -52.4 -49.4 -45.1 -32.3 -26.8

Government

Black 8.2 6.8 6.6 1.4 3.3

White 7.8 7.0 -13.5 -10.2 -13.6

Panel E: Marital status (reference = nonmarried)5

Black 9.3 12.7 18.3 15.0 16.9

White 19.6 19.5 22.9 20.4 20.0

Note Each estimated coefficient, or "return," is denved from a multiple regression of weekly earnings on the five variables in the table Separate estimates are made by age group.

race, and census year. They are interpreted as percentage changes in earnings due to a change in the characteristic

'The return on schooling is estimated separately for years 0-12 and for years 13 and over It measures the percentage increase in earnings associated witha year of schooling

2This is the return from one year of potential work expenence.

3Each estimate indicates the (percentage) earnings difference associated with living in the particular region in contrast to limo in the Northeast region

Each estimate indicates the (percentage) earnings difference associated with working in the particular sector in contrast to working in a private nonagi 'cultural industry A

residual category of "other industries" was also included but is not reported to save space

s Each estimate indicates how muchmore a married man eams than an unmarned man (in percentage terms)

In fact, the combined effect of convergence in

returns and levels of schooling ranks education as

one of the most important factors underlying the

narrowing of the earnings gap between 1940 and

1980.11

Education may translate into lower earnings for

blacks than whites because the education received

by blacks may be of lower quality than the education

received by the average white. Racial differences in

parental education, income, and other family background factors may also affect how much children

gain from schoo1.12 Improvements in these areas

over time, therefore, may account for the convergence in returns on schooling.

Discriminatory practices may also be responsible

for the lower monetary gains from schooling for

blacks. For this to be true, however, such practices

" Increases in the monetary returns on schooling do not automatically lead to higher absolute levels of earnings Higher

returns indicate that the more highly educated are earning more

relative to the less educated. But this can occur even though

everyone experiences lower earnings as long as the less educated

workers lose more. It turns out, however, that black-white

earnings ratios have been rising for most loweducation cohorts,

defined by industry, region, and marital status, thus supporting

the assertion that earnings of blacks across all education levels

have been rising relative to the earnings of whites.

must have a greater effect on the work opportunities

of educated blacks relative to less educated blacks. If

so, the convergence in returns over time could

reflect legal and judicial action to block discriminatory practices or may indicate changing attitudes.

Potential Work Experience

Estimates of the return on potential work experience for 25-34 year-old men (table 6.3, panel B)

indicate That earnings of blacks grow with age at a

slower rate than those of whites and that the

difference in returns has tended to narrow over time.

These results suggest that blacks have tenc'ed to

accumulate skill at a slower rate than their white

counterparts, perhaps because of discrimination in

training and advancement or for other reasons. The

convergence in returns may mean that blacks are

" Chiswick (1986) suggests that differences in the number of

children in the family and in the labor force participation of

mothers may help to account for differences in the return on

schooling amoog ethnic and racial groups Black women have

more children and, historically. have worked more in the market.

Both factors are found to reduce the time spent v, ith a child and,

therefore, affect further educational gains

104

95
increasingly entering career paths that are more

similar to those of whites and that offer, or demand,

more intensive training.I3

Region

Estimated earnings differences between regions

(panel C, table 6.3) confirm that earnings are lower

in the South than any other region. In 1940, for

example, black males in the South earned 32.2

percent less than blacks in the Northeast. The

comparable figure for white males was 17.4 percent.

This difference was basically maintained until the

1970s when earnings of both black and white males

in the South rose relative to other regions.

These estimates do not show precisely how much

more people from the South and their descendants

earned as a result of relocation. It is clear from the

sheer magnitude of the North-South differences,

however, that the realized gains were fairly substantial through 1970. During the 1970s, southern wage

levels rose dramatically in comparison to other

regions. Even if these gains were equal for southern

blacks and whites, the predominance of blacks in the

South would mean that average black earnings grew

reiative to average white earnings. In fact, the wages

of southern blacks appear to have grown faster than

those of southern whites, thus compounding the

positive effect of general southern growth on relative earnings.

Industry

Estimates of earnings differences among industrial

sectors (table 6.3, panel D), confirm that earnings in

agriculture are generally lower than in private

nonagricultural industries and government. For example, blacks who were employed in agriculture in

1980 earned 34.8 percent less than blacks in private

nonagricultural jobs, and whites earned 26.8 percent

less. These results strongly '.upport the view that the

shift of blacks from agriculture into private nonagricultural and government jobs had a positive effect

on average black earnings. Recall, however, that

most of this movement had run its course by 1960

If the estimates of the returns on years of work were derived

by actually tracking workers over their careers, this interpretation

could be more certain. Unfortunately, they are derived by

comparing individuals of differing ages, which raises the alternative possibility, discussed in chap. 5, that the estimates reflect

"cohort" effects, not purely "life cycle" effects. Improvements in

black earnings that are due, for example, to diminution of the

effects of labor tnaiket discrimination may accrue disproportionately to labor force entrants. If so, the true growth rate of

96

115

and subsequently had very little influence on relative

earnings.

Marital Status

The differences in earnings between married and

unmarried men (table 6.3, panel E) are similar to the

cruder estimates c the marriage premium presented

in chapter 5. They support the contention that lower

marriage rates among blacks may be a reason for the

low relative earnings of black males.

Changes in the Earnings Ratio Over

Time

In analyzing why black and white men have

different earnings, several factors were identified as

contributing to the narrowing of this differential

over time. On the whole, blacks and whites have

become more alike in terms of certain key characteristics. Thus, differences in geographic and industrial

distributions of workers and years of schooling all

narrowed during the 1940-80 period. There have

also been important changes in the coefficients

linking earnings to certain characteristics, notably

the narrowing differences in schooling and work

experience coefficients and the general narrowing of

North-South differences in earnings. Although

changes in coefficients have been somewhat erratic

and are not very well understood, they are, nonetheless, a major source of the narrowing in the blackwhite earnings differential.

The purpose of this section is to evaluate the

collective effect on the black-white earnings ratio of

trends in characteristics over the 1940-1980 period.

What cannot be explained by changes in racial

differences in characteristics implicitly reflects

changes in coefficients. The procedure estimates

what change would have occurred in the ratio if only

characteristics had changed between census years,

with coefficients remaining the same. Table 6.4

reports, by age group and year, unadjusted earnings

ratios and adjusted ratios calculated with 1980 (racespecific) coefficients.13

The results indicate that increasing similarity in

the characteristics of black and white men accounts

earnings for blacks is un&restimated, because the earnings of

older workers will remain under a greater influence from past or

present disc, immation.

" The estimates in table 6.3 are net of the possible influences of

regional differences in education and Industry, whereas table 3 above provided only partial control for educational differences

The choice of a reference year, t e , 1980, is arbitrary but does

not significantly alter the conclusions
TABLE 6.4

Unadjusted Ratios of Black-White Earnings Compared to Ratios Adjusted to Reflect

1980 Coefficients

1940 1950 1960 1970 1980

Ages 25-34

Unadjusted ratio 48.7 64.9 62.3 70.3 78.8

Adjusted ratio 67.4 71.9 74.0 77.5 78.8

Ages 35-44

Unadjusted ratio 44.9 59.3 58.4 62.8 70.5

Adjusted ratio 65.0 65.2 66.4 68.4 70.5

Ages 45-54

Unadjusted ratio 42.7 56.3 55.7 59.5 67.5

Adjusted ratio 68.2 69.4 67.5 67.1 67.5

Ages 55-64

Unadjusted ratio 42.6 54.2 53.2 58.9 65.0

Adjusted ratio 70.2 69.0 68.4 66.3 65.0

Note The adjusted ratios are derived by using 1980 coefficients to evaluate the charactenstics - schooling, experience, region, industry and marital stMus - in each year between 1940 and 1980

for a larger share of the rise in the relative earnings

of black men among younger groups than among

older groups. Between 1940 and 1980, earnings of

young blacks grew 62 percent faster than the

earnings of whites; of this relative gain, close to 40

percent can be attributed to convergence in characteristics. Among men ages 35-44, the relative earnings gain for blacks was 57 percent, of which 21

percent can be attributed to convergence in characteristics; and among 45-54 year-old men, characteristics apparently played no role in the increase.

Based on the discussion in earlier chapters, at least

part of the gains made by blacks since 1940 is due to

improvements in their skill levels (and regions of

residence) relative to whites. The five characteristics

included in this analysis, however, do not measure

all of the determinants of skill. Moreover, in the case

of schooling, grades completed are poorly measured

for the early cohorts. In addition, some gains, such

as imorovements in school quality and in the

knowledge imparted by parents at home, as well as

more detailed regional changes, are reflected in

changes in the estimated coefficients. Consequently,

the general upward trend in the adjusted ratios

probably understates the full gains made by blacks

through accumulation of skill. These unmeasured

gains in skill are part of the balance of the change in

the unadjusted ratios, i.e., change in the unadjusted

minus change in the adjusted ratios.

Summary

The analysis in this chapter is based on the

premise that earnings are determined by certain

characteristics of the individual in combination with

the coefficients that link these characteristics to

earnings. Therefore, earnings differences between

blacks and whites can be viewed as composed of

two parts, differences in characteristics and differences in coefficients.

The influence of current labor market discrimination in this analysis would be confined to an effect

on racial differences in coefficients, since the explanatory variables used in the analysis are believed to be

largely free from the influence of current labor

166

97
market discrimination. (Schooling, however, reflects

the effects of past discrimination in resource allocation.) Therefore, netting out the effects of racial

differences in these characteristics isolates a portion

of the earnings gap that contains virtually all of the

effects of current labor -iarket discrimination. Unfortunately, such effects are not fully isolated because this portion of the gap also reflects racial

differences in several important but unobserved

determinants of earnings such as school quality,

skills imparted by parents, and a host of other factors

that shape individual productivity and earnings.

Nevertheless, rough upper limits are established

within which the effects of current labor market

discrimination are believed to fall.

The analysis of earnings differences over the

1940-1980 period indicates that racial differences in

the five characteristics included in the analysis can

account for 30 to 40 percent of the wage gap,

depending on the age group and the year examined.

The remaining, or unexplained, gap also varies by

age group, but for all age groups the gap narrowed

dramatically over time. After adjusting for differences in the five characteristics, black workers aged

25-34 would earn 30 percent less than whites in 1940

and 12.6 percent less in 1980. At ages 45-54, this

unexplained residual would have been 41.6 percent

in 1940 and 22.1 percent in 1980. These unexplained

residuals reflect the upper boundary of the effect of

labor market discrimination on the earnings of black men. Examining the effects of each characteristic reveals that differences in years of school play the

largest role, accounting for up to 27 percent of the

gap among young men in 1970 and 1980. Moreover,

this share has generally increased over time as the

98

influence of other characteristics has abated. The

effect of lower schooling levels has been compounded by the fact that blacks apparently receive a lower

return on an additional year of school than whites.

Over time, however, there has been a substantial

convergence in returns on schooling.

The concentration of the black population in the

South also explains a significant part of the earnings

gap, though its importance has diminished over time

largely because of migration and southern economic

development. Finally, the combined effect of differences in industrial employment patterns and inarital

status accounts for less than 10 percent of the

earnings gap in any year and age group.

The second part of this chapter evaluates the

collective effect on relative earnings of changes in

worker characteristics and changes in the coefficients associated with these characteristics. Although gains by blacks in the measured characteristics, such as schooling, generally have had a significant effect on raising their earnings relative to

whites, the convergence in coefficients or returns

seems to have been more important. Chan3es in

coefficients, however, do not provide really concrete explanations, since they can reflect any number

of unmeasured factors, including gains in the quality

of schooling, improvements in parental contributions to skill development, migration to higher

paying areas within the broad regions, and the

effects of antidiscrimination laws and policies.

These factors cannot be easily quantified, but their

possible contributions can be evaluated qualitatively.

The next part of the report investigates the role of

antidiscrimination policies and of other factors in

this more elusive category of forces affecting the

racial gap in earnings.

i 6 7
PART III

Why the Wage Gap Narrowed: Alternative

Hypotheses

It has been well documented that the earnings of

black men rose substantially more than the earnings

of white men over the 1940-1980 period. Only part

of the rise in the relative earnings of blacks,

howo;er, could be tied statistically to a narrowing in

racial differences in schooling, geographic region,

age, industrial sector, and marital status. At younger

ages about 40 percent of the rise could be explained

by these factors, but at older ages very little of the

rise could be explained this way.

What factors, then, do account for the bulk of

convergence in black-white wage differences? One

possibility is that differences in skills or in other

factors affecting earnings narrowed in ways that

were not measured by the five characteristics included in the statistical analysis. Another possibility is

that labor market discrimination against blacks

declined, either as a result of general forces in

society that affected racial attitudes or as a direct

result of Federal civil rights legislation and regulation.

This section explores these unresolved issues as

well as the related question concerning the current

wage gap and the role of discrimination in accounting for it. Chapter 7 focuses on the role of civil

rights programs and policies; chapter 8 assesses the

effects of all of the broad factors.
Chapter 7

Labor Market Effects of Civil Rights

Policy

Between 1940 and 1980, &overnment increasingly

developed and implemented policies aimed specifically at improving the labor market status of

minorities and women. This chapter investigates the

link between these policies and the substantial

improvement in the relative earnings of black men

during the same period. The chapter provides a brief

description of the more important civil rights programs, analyzes the possible effects of these programs from the standpoint of economic theory, and

reviews several prominent studies of their effects.

Background

Some of the earliest efforts to penalize labor

market discrimination were made by State governments. Between 1945 and 1959, 13 States (all outside

the South) enacted legislation prohibiting employment discrimination and established commissions

with powers to enforce these laws. Before. 1960,

however, the resources allocated to most of these

commissions were generally meager. During the

1960s and 1970s, the enforcement effort greatly

expanded, and the number of States with antidiscrimination laws and effective monitoring mechanisms

substantially increased.

Executive Order 11246 is the most recent in a series of

Executive orders dating back to 1941. Norgren and Hill (1964)

describe these earlier orders and examine their effect on reducing

discrimination. They conclude that "the twenty years [1941-1961]

of intermittent activity by presidential committees [established by

100

The first significant action by the Federal Government to attack labor market discrimination was

passage of the Civil Rights Act of 1964. Title VII of

this law prohibits discrimination in all aspects of

employment and compensation based on race, color,

religion, sex, or national origin. The Equal Employment Opportunity Commission (EEOC) was established to investigate complaints of such discrimination. The provisions of Title VII, as amended, cover

the employment activities of private employers with

15 or more employees, as well as the activities of

labor unions, employment agencies, State and local

governments, and educational institutions.

The next significant action by the Federal Government aimed at eliminating the effects of discrimination was the issuance of Executive Order 11246 in

1965.1 This order. as amended, goes beyond the

nondiscrimination provision of Title VII and requires that Federal contractors, subcontractors, and

federally assisted construction contractors take "affirmative action' to ensure that employees and

applicants are treated without regard to their race,

sex, creed, color, or national origin. In 1980 Federal

contractors employed roughly 30 percent of the

nongovernmental, noneducational work force and

were awarded $110 billion in Federal contracts.'

the Executive orders] has had little effect on traditional patterns

of Negro employment" (p. 165). 2 The percentage of workers in Federal contractor firms was

obtained from unpublished tabulations provided by the EEOC
Responsibility for administering Executive Order

11246 is delegated to the Office of Federal Contract

Compliance Programs (OFCCP) in the Department

of Labor. Regulations implementing the order require all contractors with $50,000 or more in Federal

contracts and 50 or more employees to maintain

written affirmative action plans. These plans are

"results oriented" and require the contractor to

detail occupations in which the contractor is deficient in the utilization of minority groups and

women, and to develop targets ("goals and timetables") to correct such deficiencies. Failure of

contractors to comply with the order can ultimately

result in contract cancellation and debarment from

future contracts. In practice, noncompliance typically results in conciliation agreements and written

commitments to correct deficiencies.

Issues in Enforcement

Empirical difficulties in detecting discriminatory

behavior pose potentially serious problems for the

enforcement of civil rights programs. In the past,

discrimination was legal and overt. Employers could

maintain dual pay scales by race or could blatantly

post "help-wanted" advertisements barring blacks or

other minorities from applying. Nowadays, discrimination in employment is illegal and therefore likely

to operate in more subtle ways. Such subtle forms of

discrimination may not be readily detected by

outside observers and may never come to light

unless employees or rejected applicants bring suit.

Even if a particular business practice is detected as

having possible discriminatory effects, honest differences of opinion may easily arise as to whether it

reflects discrimination. Productivity differences between workers often cannot be measured very well,

possibly resulting in incorrect judgments about the

extent to which racial disparity s in pay, hiring, and

promotion result from discrimination. Given the

problems of detecting or establishing the presence of

discrimination, it is probably unavoidable that some

benign business practices will be interpreted as

discriminatory in nature, while some discriminatory

behavior goes entirely undetect-.1.

Difficulties in detection suggest that remedies for

possible discriminatory behavior may create new

problems. Discrimination is a multidimensional conand Bureau of Labor Statistics. The dollar volume of Federal

contracts was obtained from unpublished figures provided by the

Office of Federal Procurement Policy:"

Lerner (1977, 1980) examines how the judicial system has

interpreted adverse impact.

cept and may affect many different aspects of the

employment relationincluding recruitment, hiring,

firing, pay, and promotion. Even if a particular type

of discrimination is correctly identified, its remedy

may simply result in the substitution of another type

of discrimination. The following example provides

an illustration.

Between 1966 and 1978, the EEOC issued increasingly detailed rules (commonly known as the Guidelines) focusing on the use of employee selection

procedures that have an "adverse impact" on the

employment opportunities of minorities and women.

Written tests, educational requirements, and personal interviews are examples of selection procedures

that are covered by the Guidelines. As currently

implemented, the Guidelines state that an employer's

selection procedures generally will be found to have

an adverse impact if the acceptance rate for any

particular group is less than four-fifths the acceptance rate for the highest group. For example, if an

employer hires 5 out of every 10 white applicants

but only 3 out of every 10 minority applicants, then

the selection procedure generally will be found to

have an adverse impact on minority hiring. An

employer with a procedure resulting in adverse

impact becomes subject to a wide range of potentially costly and time-consuming requirements to prove

that it is nondiscriminatory. If unable to do sr the

employer may be found to have violated Title VII

and penalized accordingly.'

Although the clear intent of the Guidelines is to

reduce the use of discriminatory practices directed

at minorities and women, in practice the Guidelines

may have the unintended effect of limiting employment opportunities for minorities and women. For

example, to avoid a determination of adverse impact,

employers might narrow their applicant pool and

recruit only those minorities who have a high

probability of meeting the employers' selection

criteria.* In this way the Guidelines might benefit

more highly skilled minorities but actually restrict

opportunities for less skilled minorities. The net

outcome could be that the acceptance rate of

minorities rises, while the actual number of minority

hires falls.

In sum, empirical difficulties in detecting and

remedying discriminatory behavior pose complex

4 Lerner (1977, 1980) provides a more detailed discussion of how

ite definition of adverse impact used in the Guidelines may

inhibit recruitment of minorities.

101
problems for the enforcement of civil rights programs. As a consequence, remedies for possible

discrimination may have unintended effects that

could actually lower the overall economic status of

ome minorities, while helping others. It is ultimately an empirical question whether policies to reduce

iiscrimination have succeeded.

Econometric Studies

This section reviews the empirical evidence regarding the effects of governmental civil rights

programs on the relative labor market status of

blacks. Two basic types of studies are reviewed:

time series and cross sectional. The times-series

studies are best viewed as attempts to measure the

combined effect of all civil rights activity occurring

after 1964. The cross-sectional studies attempt to

measure the individual program effects of the

OFCCP and State fah employment practices commissions. Though intended to be more illustrative

than exhaustive, the review includes most of the best

known studies. The chapter concludes with an

overall assessment of the quality of evidence contained in these studies.6

From the outset, it should be emphasized that it is

difficult to evaluate the labor market effects of

governmental civil rights programs. The 1960s and

1970s, decades in which civil rights activity greatly

expanded, were a time of rapid socioeconomic

change, marked by the expansion of governmental

programs designed to reduce poverty, improve

educational opportunity, and eliminate the labor

market effects of discrimination. Attempting to

isolate these various effects places an extreme

burden both on the data and on the empirical

estimation procedure.

Time-Series Studies

Post-World War II trends in black-white earnings

ratios have been the subject of a number of empirical

studies. Viewing figure 7.1, relative black earnings

appear to have improved noticeably after 1964.6

Since this period coincides with a greatly expanded

level of civil rights activity, the natural temptation is

to attach causal significance to the role of government in improving the labor market status of blacks.

3 Other reviews of the econometric evidence are Butler-Heckman (1977), and Drown (1984a). This section partly draws on

observations made in these other reviews

6 "Black" and "nonwhite" arc used interchangeably Brown

(1984b) reports that blacks were 85 percent of nonwhite wage and

salary workers in 1978.

102

111

It is possible, however, that other factors may have

caused or contributed to this pattern, and it is

precisely the treatment of these other factors that

has generated a heated debate concerning the labor

market effects of governmental civil rights activity.

Richard Freeman did the first systematic timeseries analysis of the effects of civil rights activity on

the labor market status o" acks.7 Factors considered by Freeman to be potentially important determinants of relative earnings were: (1) business

cycles; (2) growth in gross national product; (3)

relative education of blacks to whites; (4) a "time"

effect (measuring changes in attitudes and/or structural shifts in the economy over time); and (5)

governmental civil rights activity, represented by

cumulative EEOC expenditure per nonwhite worker.

After adjusting for factors 1 through 4, Freeman

found that governmental civil rights activity had a

significant positive effect on relative black income.

Freeman tentatively concluded that the increase in

relative income was attributable to the governmentinduced increase in demand for black labor.

Richard Butler and James Heckman argued that

Freeman's results were flawed because of an incomplete specification of the determinants of wages!'

They reasoned that a relative increase in demand for

black labor should increase the relative employment

of blacks as well as their relative income. Yet, the

relative labor force participation of blacks to whites

declined after 1964.

To account for the actual pattern of the timeseries data, Butler and Heckman emphasized the

importance of factors that affect the supply of labor.

In particular, they cited the expansion of transfer

programs, such as disability and welfare programs,

that coincided with the civil rights activities of the

1960s and 1970s. These programs, by reducing

incentives to work, tend to reduce labor force

participation.' They argued that low-wage earners

were more likely to participate in such programs

than high-wage earners and that, since blacks tend to

earn less than whites, the decline in labor force

participation should have been relatively greater for

blacks This downward trend in relative black labor

force participation has two implications for black

R Freeman ( I97;)

R Butler and J Heckman (1977)

Sec the discussion in chap 2 for a detailed explanation
FIGURE 7.1

Nonwhite-White Earnings Ratios,* 1953-14,14

80

75

70

i

65

0

2

la 60

55

50

1950 1955 1960

VVAGE AND SALARY INCOME OF WAGE AND SALARY WORKERS.

Source: Current Population Survey Data.

1965 1970 !975

YEAR

112
relptive to white earnings. First, a decline in the

supply of black workers relative to white workers

will tend to increase the relative wages of blacks.

Second, since published earnings series include only

persons who work, the possible "siphoning off" of

low-wage earners by transfer programs may impose

an upwards bias on the earnings levels observed in

published data. These two implications of the decline in relative black labor force participation

suggest that part of the increase in relative black

earnings occurring after 1964 may be illusory and

cast doubt on Freeman's conclusion regarding the

beneficial effect of governmental civil rights activity.

Charles Brown has empirically tested the validity

c f the Butler-Heckman argument by making several

modifications to the basic Freeman model.'° First he

adjusted the published earnings data to account for

the possible bias resulting from changes in relative

labor force participation described above. His adjustment rested on the assumption that all changes in

labor force participation involved persons with low

wages. Brown's other modifications consisted of

adding: (1) a relative labor supply variable, designed

to measure the effect of changing aggregate supplies

of labor on relative wages; and (2) a post-1964 time

trend, designed to capture the effect of civil rights

activity occurring after passage of the Civil Rights

Act of 1964. (This replaced Freeman's EEOC

variable.)

With these modifications in place, Brown then

reestimated the basic Freeman model. His empirical

results suggest that the relative decline in black labor

force participation has exaggerated the improvement

in black earnings, but that the decline in labor force

participation cannot explain the entire improvement.

Further, changes in relative levels of education, in

the relative supply of labor, and business cycle

effects do not appear capable of producing the entire

increase in relative black earnings occurring after

1964. Brown interprets this unexplained post-1964

improvement in relative earnings as evidence that

Federal civil rights policies have had a positive

effect on the earnings of black males."

zo C. Brown (1984b). " Brown's results show that about one-half of the post-1964

trend survives the adjustment for selectivity. It is also important

to note that his method for correcting for selectivity will tend to

overstate the role played by labor market dropouts, since it

assumes all dropouts previously had low earnings. Brown's

results, therefore, suggest that less than one-half of the post1964

trend in relative earnings can be explained by labor market

104

1 t t.)`)

The Freeman and Brown studies of the time-series

data suggest that governmental civil rights activities

are likely to have had a beneficial effect on increasing relative black earnings, but their results should

not be overstated.

First and most important, the tests of the effectiveness of civil rights activity are far from ideal. All

time-series studies essentially attribute any unexplained post 1964 change in relative earnings to the

influence of Federal civil rights programs. The

problem in doing this type of test is that it ignores

the possible influence of other factors that are not

explicitly included in the analysis. For instance, the

post-1964 upward trend in relative black earnings

may, in part, be due to the effect of the civil rights

movement and to improved public attitudes about

race. Table 7.1 reveals a remarkable decline between

1958-1980 in the percentage of white parents objecting to desegregated schools. and the change is

especially large in the South. This improvement in

stated attitudes undoubtedly was affected by the

Civil Rights Act (as the sharp change in attitudes

from 1963 to 1965 suggests). On the other hand,

passage of the Civil Rights Act may itself have been

spurred by the change in attitudes (as the change in

attitudes from 1959 to 1963 suggests). Irrespective of

the source, the change in attitudes may have broken

down barriers for many blacks and also have

reduced the degree of prejudice among employers

and white coworkers.

Second, chapter 1 documents that relative black

earnings increased substaially during the 1940s,

more moderately during the 1960 and 1970s, and

actually declined slightly during the 1950s.'2 Thus,

relative earnings have grown in three out of the four

decades for which data are available, and this

growth occurred both before (the 1940s) awl after

(the 1970s) the implementation and expansion of the

major civil rights programs. By focusing on the

postwar period (i.e., after 1948), however, the timeseries studies primarily compare the earnings trends

during tile 1950s with those after 1964. To the extent

that the 1950s may be an exception to the pre-1964

trends in relative earnings, the findings of the timedropouts Note, however, Vroman's (1986) analysis, which

suggests that labor market dropouts may not be much below the

average. 12 In absolute terms black male earnings grew at a rapid rate

during the 1950s-3.4 percent a year in real terms However,

white male income also grew rapidly, in fact, at a higher rate than

in any other decade. See chap 1 for details
TABLE 7.1

White Parents Objecting to Desegregated Schools (percentage answering "yes")

Year South Non-South

1958 72 13

1959 72 7

1963 61 10

195 37 7

1966 24 6

1969 21 7

1970 16 6

1973 16 6

1975 15 3

1978 7 4

1980 5 5

Source The Gallup Report. No 185 (February 1981) p 30

series studies may be biased towards finding an

"unexplained" post-1964 increase in relative black

earnings.'3

Cross-Sectional Studies

An unfortunate drawback of the time-series studies is that they cannot identify the possible contribution of specific civil rights programs. Time-series

studies are, therefore, incapable of disentangling the

labor market effects of affirmative action from those

of laws that generally prohibit discrimination. From

a policy perspective, however, it is important to

evaluate the effects of specific programs; if a

program is found to be ineffective, society may be

better off redirecting resources to other, more

effective ones.

The advantage of cross-sectional studies is precisely that they are designed to measure the effects

of specific programs. The basic methodology of

these studies compares those sectors of the economy

that should be more responsive to governmental

pressures with sectors of the economy that should be

less responsive. A finding that a program has a

positive effect on minority labor market status

" The published time-Series analyses use earnings data up to the

year 1978. However, the black-white earnings ratio has been

nearly constant since 1975. An update of the studies, extending

the samples to the present, could possibly show weaker effects of

Federal civil rights activity.

simply means that the program has affected certain

sectors of the economy more than others. An

unfortunate limitation of this approach is that a

program may affect all sectors uniformly. For

example, Executive Order 11246 may induce firms

with Federal contracts to alter their employment

behavior. But if noncontracto: firms aLticipate

holding Federal contracts in the future, they also

may alter their current employment practices, and

there may be no observed difference between

contractor and noncontractor firms. Properly interpreted, then, cross-sectional studies do not measure

the full effect of a particular program, only the

differential effect between sectors of the economy

covered and not covered by the program."

Office of Federal Contract Compliance Programs

With its ultimate threat of contract cancellation

and debarment from future Federal contracts, the

OFCCP is one of the major regulatory bodies

through which governmental civil rights policy may

affect the employment practices of private firms. In

fact, existing empirical studies of the OFCCP are

generally consistent with the view that the program

" For just such reasons, cross-sectional studies of Title VP

which covers almost all sectors of economy, are of questionable

value. For examples of such studies that arrive at different

conclusions, see Beller (1978) and Leonard (1984)

1 A -i'''

105
has increased the employment of blacks in firms with

Federal contracts. The studies, however, do not

provide strong evidence that the OFCCP has reduced black unemployment or increased black

wages in the general economy.

All studies examining the effect of the OFCCP use

the same basic statistical f amework. This framework compares the employment percentages of

various demographic groups within an employer's

work force at two different points in time. These

points are chosen to correspond to the employment

situation before and after a change in the size or

scope of the OFCCP's enforcement effort. A finding

that Federal contractors increased their share of

black workers at a faster rate than non-Federal

contractors is taken as evidence that the program

has benefited blacks.

The basic source of data is the EEO -1 data file.

All private employers employing 100 or more

employees, or employing 50 or more employees and

having Federal contracts totaling $50,000 or more,

are required to file EEO-1 forms with the OFCCP

and EEOC on an annual basis. The EEO-1 form

includes information on the location, industry, and

Federal contractor status of the firm, and classifies

its employment by race and sex within nine broad

occupational groupings. A serious limitation of the

EEO-1 form is that it does not include information

on the wages, education. age, or prior work experience of the employer's work force. Thus, the studies

of the OFCCP cannot be used to determine directly

the OFCCP's effect on black wages or black

unemployment.

Basic results from four representative studies of

the OFCCP are presented in table 7.2. All '7 the

studies find that the OFCCP has a positive effect on

the employment of blacks relative to whites in firms

with Federal contracts. The estimated magnitudes,

however, vary widely from study to study. Jonathan

Leonard (1984b) has found that Federal contractors

increased the. relative employment of black males at

an average rate per year of 1.01 percent more than

non-Federal contractors between 1974 and 1980.

Morris Goldstein and Robert Smith, on the other

hand, found an effect of only 0.04 percent per year

between 1970 and 1972. Estimates of the effect of the

OFCCP on the relative occupational status of blacks

In his 1983 Department of Labor study, Leonard uses many

different specifications and reports a much wider range of

estimates.

106

1 7

are also mixed. Of the three studies that investigate

this issue, only Leonard (1984a), for the 1974-80

period, has found a strong positive association

between contractor status and the occupational

upgrading of blacks relative to whites.

One possible reason for the different estimates of

the effect of the OFCCP involves the different time

periods used in the different studies. Unfortunately,

it appears that differences in statistical methodology

also contribute to the differences in the estimated

effect of the OFCCP. Using the same data but a

different estimation method, Leonard (1984b) found

the effect of the OFCCP on relative black employment to be almost twice as large as in his earlier

study (1984a).'s Even more disturbing, Goldstein

and Smith found that not only the magnitude, but

also the direction of the estimated effect of the

OFCCP is sensitive to how the model is specified

and estimated. In particular, using the estimation

procedure of Orley Ashenfelter and James Heckman, Goldstein and Smith found that the effect of

Federal contractor status was to reduce the employment of black males relative to white males between

1970 and 1972.

The sensitivity of estimates to the way the model

is specified raises an obvious question: which is the

correct specification? Regrettably, no study of the

OFCCP has seriously addressed this issue.'6 In the

absence of theoretical reasons for preferring one

specification to another, all of the estimates in table

7.2 should, therefore, be viewed cautiously; different

researchers examining the same data may arrive at

different conclusions regarding the effect of the

OFCCP.

Although partly clouded by sensitivity to model

specification, the evidence in table 7.2 suggests that

the CH-CCP has increased the employment of blocks

in firms with Federal contracts. The important

policy question, however, is whether the OFCCP

has actually improved overall employment opportunitie° for blacks. Specifically, has the OFCCP

benefited blacks by reducing their incidence of

unemployment and/or increasing their wages?

On theory alone, the increase in the demand for

black tabor in the Federal contractor sector should

be expected to have at least slightly increased black

'ages. As previously noted, because of data limita-

" Goldstein-Smith and Leonard (1983) briefly discuss why the

estimates may differ according to the estimation procedure, but

they do not state which is the preferred procedure
TABLE 7.2

Effect of the OFCCP on the Employment of Black Men Relative to White Men

AshenfelterHeckman

GoldsteinSmith Leonard Leonard

Study: (1976) (1976) (1984a) (1984b)

Time period: 1966-70 1970-72 1974-80 1974-80

Sample size

(establishments): 40,445 74,563 68,690 68,690

% change in relative employment 0.82 0.04 0.58 1.01

(annualized)' (-0.49)2

BM/WM occupational upgrading: Very minor Insignificant Strong

upgrading

Note Estates in this table are not exactly comparable because of differences in model specification and time periods o note the differences in model sr ecification, the

indivieJal studies must be consulted

/ Effect of contractor status on black male relative to white male employment. for all the studies except Ashenfelter-Hecl man, the figure in the table is the combined effect of Federal contractor status and compliance reviews (see Goldstein-Smith for a description of the methodolot,y used to de we this effect) Ashenfelter-Heckman do not explicitly

include a compliance review variable

2GoldsteinS nth estimate when using the AshenfelterHectunan estimation procedure

107
tions, the studies of the OFCCP cannot be used to

determine directly the magnitude of the increase.

Nonetheless, it is helpful to compare the timing of

the growth in relative black earnings with the

patterns of the OFCCP enforcement effort. Figure

7.1 shows that black earnings increased substantially

between 1964-1974 and remained fairly constant

between 1975-1984. Yet, the studies cited in table 7.2

suggest that the 1974-1980 period was marked by an

especially vigorous OFCCP enforcement effort.

Unless some unspecified factor was working to

reduce the earnings of blacks during this period, the

approximate constancy of relative earnings during a

period of strong enforcement casts doubt on the

success of the OFCCP in raising black wages.

The OFCCP's effect on black unemployment also

remains unclear. Theory faggests that the OFCCP

should have reduced at least marginally black

unemployment. Again, however, data limitations

preclude attempts to quantify the magnitude. Since

the rate of unemployment of blacks increased substantially relative to that of whites during the 1970s,

it is possible that black employment gains in contractor firms resulted largely from a reshuffling of black

and white workers between noncontractor and

contractor firms.17 Thus, blacks who otherwise

would have been employed in the noncontractor

sector may have obtained jobs in the contractor

sector (and vice versa for whites), but there is no

evidence that the program increased the employment of blacks as a whole.

State Fair Employment Practices Commissions

In 1945 New York and New Jersey were the first

States to pass legislation prohibiting discrimination

in employment based on race and to establish

commissions (FEPCs) with powers to enforce these

laws. By 1959, 13 States, all nonsouthern, had

enforceable antidiscrimination laws. The resources

allocated to these commissions, however, were quite

limited, and it is doubtful that they could have

substantially affected overall black labor market

status. The 1960s and 1970s saw an expansion not

only in the number of States with such laws, but also

in the level of their enforcement. Thus, the combined budgets of all FEPCs amounted to roughly

" See fig. 1.2 in chap. 1 and the discussion and tables in chap. 2

for evidence on the divergence in black versus white unemployment rates in the 1970s. " Sources are as follows: for 1959, Landes (1968); ter 1968,

Kovarsky and Albrecht (1970); for 1975-76, the Center for Policy

108

$1.7 million 'n 1959, $10 million in 19P8, and $29.5

million in i975 -- 1976.18

Little is known about the actual labor market

effects of FEPCs. Most existing studies are anecdotal in nature and typically focus on the regulatory

process as opposed to measuring actual labor market

outcomes. An exception to this is a study by William

Landes, which examined the effect of FEPCs in

1959.19

The Landes study was notable both for examining

the effects of FEPCs and for investigating possible

unemployment effects resulting from enforcement of

civil rights laws. Landes compared labor market

patterns in States with fair employment laws to

those in States without such laws. After adjusting

for differences among States in years of schooling,

relative numbers of black versus white workers,

degree of urbanization, and geography, Landes

found: (1) relative black wages were approximately

5 percent higher in States with fair employment laws

than in States witho :t such laws; and (2) fair

employment laws did not appear to be systematically related to racial differences in unemployment.

Comparing labor market patterns in States with

and without antidiscrimination laws at a particular

point in time, however, may distort the true effect of

the laws. For example, it is possible that racial

differences in wages were narrower in FEPC States

even before the passage of fair employment laws. To

investigate this possibility, Landes examined relative

wages and employment patterns prior to the passage

of such laws. Using 1949 as a benchmark (9 out of 13

States with such laws in 1959 enacted them after

1949), he found no systematic difference in relative

wages in 1949 between States that, in 1959, did and

did not have fair employment laws. Since in 1959

relative black wages were higher in fair employment

practice States, it thus appears that enactment of fair

employment laws actually did lead to a true increase

in relative black wages. In contrast, differences

between blacks and whites ,n unemployment appear

to have been smaller in 1949 in States that by 1959

had passed fair employment laws. Landes concluded

from this that fair employment laws actually increased the unemployment of blacks relative to

whites.

Review (1977). The figure for 1975-76 refers to a I2-month

period spanning 1975-76. These figures are crude apr-Jximations

and include some expenditure on nonemploymeLt act. ay.

19 W. Landes (1968).
Lancts' stt.dy of FEPCs is suggestive of how

enforcemen of civil rights laws can lead to both

higher relative black wages and higher relative

black unemployment, but its significance should not

be exaggerated. He studied a period when the

enforcement effort of FEPCs was quite limited, and

his results are not necessarily applicable to the post1964 period, when State government civil rights

activity greatly expanded.

Conclusions

Studies reviewed in this chapter suggest that civil

rights policies have contributed to the improvement

in the relative earnings of black m -:n. Studies based

on time-series data have found an upward trend in

relative black earnings after 1964 that cannot be

explained by the 1948-1963 earnings trend or by

changes in variables such as relative black educational attainment. Other studies are based on analysis

of the OFCCP. These studies generally indicate that

Federal contractors have increased their employment of blacks more than non-Federal contractors.

Because of data limitations, the studies do not

provide conclusive evidence about the magnitude of

the effect of civil rights policies. The time-series

analyses do not include many important variables,

such as changes in attitudes or changes in unmeasured skill factors, that may have contributed to the

upward trend in relative black earnings. Because

they are limited to the period after 1948, when

earnings data first become available on an anntil

basis, these studies exclude the 1940s when, according to this report, the relative earnings of blacks

increased faster than in any other single decade

between 1940 and 1980. The omission of the 1940s

from these analyses may result in an overestimate of

the effect of civil rights policies on earnings growth

after 1964. Given these limitations, it has not been

established whether the contribution of civil rights

policy to the growth in relative black earnings is

large or small.

In contrast to time-series studies, which examine

civil rights programs in the aggregate, studies of the

OFCCP focus on a particular kind of affirmative

action program. Although they find that the program is associated with increased black employment

in firms with Federal contracts, they do not provide

strong evidence that the program has reduced black

unemployment or increased black wages in the

general economy. That is, the program may have

largely resulted in the shifting of employed men

from one kind of firm to another. The fact that the

relative employment of blacks declined significantly

during the period under analysis raises a question

whether black male employment was generally

increased by the program. Similarly, the approximate constancy of relative black wages during a

period of vigorous OFCCP enforcement (1974-

1980) casts doubt on the success of the OFCCP in

raising black wages.

In sum, research has not yet determined the

precise role that civil rights policies have played in

improving the labor market status of black men.

Research in this area is complicated by the many

forces, both public and private, that have operated

to improve the economic status of blacks. The same

forces that led to the passage of civil rights legislation by themselves may have broken down discriminatory barriers and influenced pubic attitudes about

race. For example, the civil rights movement

achieved landr..ark judicial and legislative victories,

but the full effect of the movement went farther

generating among the American people a recognition of racial injustice that made additional gains

possible.

It has not proven possible to identify the specific

contributions of the various civil rights programs

and policies. The Civil Rights Act of 1964 repealed

the government-mandated segregation of the South

and made other forms of institutionalized discrimination illegal. This alone likely broke down barriers for

many blacks, and it also may have served as a

catalyst in reducing the degree of prejudice among

employers and white coworkers. In addition, it is

possible that the effects of Title VII litigation and

the pressures of the Federal contract compliance

program may be important factors influencing the

increase in relative black earnings. Unfortunately,

existing empirical studies have not been able to

disentangle the effects of these different types of

civil rights activities.

188

109
Chapter 8

Unexplained Wage Differentials

Previous chapters have shown that a few key

variables explain part of the upward trend in the

relative earnings of black men and part of the

cut rent earnings gap between blacks and whites.

The analysis has not, however, been able to explain

all, or even most, of these patterns. This chapter

provides a qualitative assessment of the various

factors that seem likely to account for the unexplained components.

Factors Underlying the Trend

It was e tablished in chapter 6 that although

changing racial differences in characteristics such as

schooling and geographic region could account for

some of the narrowing in the wage gap between

1940 and 1980, they were not the primary forces

underlying the trend. This same point is made in

table 8.1, which shows changes in black-white

earnings ratios over the 1940-1980 period.

The weekly earnings ratios rise considerably from

cohort to cohort even when the comparison is

confined to population groups narrowly defined by

years of schooling, region, and age; and the rise

within these detailed groups is not so far below the

rise for all workers combined. For example, at ages

25-34, the overall increase in the earnings ratio

between 1940 and 1980 was 30.5 percentage points,

while the increase within schooling-region groupings was always greater than 20 percent in the South

and 14.9 percent in the non-South. At .1ges 45-54,

the overall ris- was 28 percentage points, and thc

' See the detailed discussion of issues concerning the measurement of years of schooling and of quality of schooling in chap 4.

and see Margo (1986).

110

rise within detailed groups was even closer, never

less than 24 perccnt.

In other words, even if racial differences in years

of schooling and region of residence had not

narrowed over the 40-year span, it appears that

much of the observed narrowing of the racial gap in

earnings still would have occurred. This suggests

that other factors such as a broad decline in

discrimination, governmental civil rights policies,

and unmeasured changes in employment skills (due,

for example, to improved school quality) are potentially important explanations for the increase in

relative black earnings.

It is plausible that successive generations of black

workers acquired more marketable skills than their

predecessors and that these increases in skills are not

adequately captured by years of school. The oldest

cohorts of black men (ages 45 and over) observed in

the 1940 census went to chool around or before the

turn of the century, largely in the rural South.

Because the schools they attended were usually

ungraded, it is believed that grades of school

completed were inaccurately reported to the Census, resulting in inflated measures of schooling.' As

graded schools became the norm, reporting of

education improved. The result was an understatement of the true rise in the educational attainment of

those black cohorts educated during the transition to

graded schools.

The relative rise in the real educational attainment

of blacks is also likely to be understated because of

.it

I C1 or
TABLE 8.1

Change in Black-White Weekly Earnings Ratios Between Cohorts by Education, Age,

and Region

All years 0-7 8-11 High

of school years years school College

Ages 25-34

Non-South

1940-1960 + 7.1 + 4.9 +10.7 + 5.0 + 0.5

1960-1980 +10.9 +13.4 + 6.5 + 9.9 +18.1

1940-1980 +18.0 +18.3 +17.2 +14.9 +18.6

South

1940-1960 +10.2 + 4.4 + 4.6 +10.1 +12.7

1960-1980 +19.5 +19.2 +16.0 +16.3 +15.1

1940-1980 +29.7 +23.6 +20.6 +26.4 +27.8

All regions

1940-1960 +14.8 +10.5 + 9.3 + 7.8 + 8.7

1960-1980 +15.7 +22.0 +10.0 +10.7 +17.1

1940-1980 +30.5 +32.5 +19.3 +18.5 +25.8

Ages 45-54b

Non-South

1940-1960 +16.2 +19.0 +14.6 +18.1 +22.5

1960-1980 + 7.0 + 7.3 +10.6 +14.8 +23.5

1940-1980 +23.2 +26.3 +25.2 +32.9 +46.0

South

1940-1960 +13.7 +12.8 +13.0 +22.9 +30.1

1960-1980 +13.2 +18.0 +11.3 +17.0 + 8.2

1940-1980 +26.9 +30.8 +24.3 +39.9 +38.3

All regions

1940-1960 +15.9 +16.7 +12.7 +21.3 +26.4

1960-1980 +12.0 +15.3 +10.0 +14.8 +17.3

1940-1980 +27.9 +32.0 +22.7 +36.1 +43.7

aPercentage point change in blac$<whne ratios for persons ages 25 34 in year t and persons 25.34 in ,aar 14 20, where t 1940. 1960

°Percentage point change in blackwhde ratios for persons ages 45.54 .n year I and persons 45.54 in year t-,20 where t y 1940. 1960

111
TABLE 8.2

Change in Black-White Weekly Earnings Ratios within Cohort by Education and Region

Non-South

All years

of school

0-7

years

8-11

years

High

school College

1940-1960 +1.2 + 4.8 +6.7 -1.2

1960-1980 +1.1 + 7.2 +6.6 +8.6 +1.1

South

1940-1960 +2.8 + 1.2 +1.2 +2.0 +2.9

1960-1980 +5.8 +14.8 +7.9 +8.9 -1.6

All regions

1940-1960 +7.3 + 9.6 +6.8 +1.8 -8.4

1960-1980 +4.5 +14.4 +7.5 +8.7 +0.2

Note Percentage Pr." :=4nge m NaciwNte rata for persons ages 2544 in year t and 4544 in year t + 20. where t 1940. 1960

*Not statistically renabre

the substantial improvement in school resources

allocated to blacks compared to whites. For example, in 1920 the length of the school term for blacks

in the South was 25 percent shorter than the term

for southern white: :.ad 40 percent shorter than the

school term outside the South.' To the extent that a

school grade corresponded to a school term, the

educational value of a grade of school completed

was likely to be lower for a black child than for a

white child. Between 1920 and 1950, the racial gap

in the length of the school term was largely erased,

and there was also a substantial convergence in

other measures of school quality such as the pupilteacher ratio. Although the precise extent to which

the convergence in school resources was tra.islated

into a convergence in academic achievement cannot

be estimated, some such gains probably did occur.'

It is also likely that a narrowing of racial differences

Sec chap. 4. 3 Educational "production function" studies that relate school

inputs, such as pupil.teacher ratios and teacher experience, to

students' scores on achievement tests have found only weak

effects of school inputs on educational "output" (Hanushek,

1986) These studies, however, generally compare schools that

differ in relatively minor ways compared to the huge differences

found between black and white schools early in the century.

112

in P' -sic achievement would have contributed to

;n the wage gap.

).-;41 :s that improved school quality is an

in. .e of the narrowing of the earnings

gap -an b! explored by examining black-white

earnings ratios for a cohort as it ages. Since formal

education is typically completed by the time an

individual enters the labor market, changes in blackwhite earnings ratios for each cohort as it ages

should be largely free from the effects of changes in

school quality and, for that matter, from the effects

of family background and other characteristics fixed

at younger ages. In fact table 8.2 reveals that blackwhite earnings ratios have increased significantly

even within cohorts. This suggests that improved

school quality and other cohort specific characteristics are not the only factors underlying the relative

increase in black male earnings within specific

schooling-region groups.' It does not rule out these

These gains are particularly impressive ,n light of the

expectation that blacks, starting from a lower skill base, would

receive less training and have flatter earnings profiles as they

than would whites (see chap 4) Note also that %Anhui the South

the effect of heavy outmigration might have been to lower the

average skill level, since migration typically selects the most able,

1 1
factors as a part of the explanation because the

within-cohort increases in earnings ratios are usually

less than the increase between successive cohorts.

For example, the within - cohort change between

1960 and 1980 among high school graduates in the

South was 8.9 percentage points (table 8.2), while

the betwecn cohort change from 1960 to 1980 was

16.3 percentage points for the age group 25-34 and

17 percentage points for the 45-54 age group (table

8.1).

Declining labor market discrimination is an obvious candidate for explaining the relative gains in

earnings for black cohorts as they age. It may also

have contributed to the gain observed for successive

generations of blacks entering the labor force. The

1940-1980 period saw a revolution in civil rights as

legally enforced segregation (Jim Crow) was abolished, autidiscrimination policies were put in place,

and racist views, once officially condomti, became

increasingly unacceptable. The civil rights movement, broad legislation like the Civil Rights Act of

1964, specific policies such as affirmative action, and

societal changes in racial attitudes all may have

contributed: but no consensus has been reached on

the specific contributions of each.

Changes in the attitudes of whites also seem to

have been strongest between generations.5 Evidently, increased urbanization, education, and economic

development in the South were conducive to declining support for segregation. These changes in views

have been found to be most evident among successive waves of young white adults, starting in the

1950s.' Changes in discriminatory views among the

mass of white workers would have been particularly

important in enabling unprejudiced employers i zely

to employ blacks to work alongsk ....,hites or to

interact with white consumers."

In sum, t tere is evidence, albeit circumstantial,

that improvements in the quality of schools attended

by blacks and declining discrimination in the labor

market both contributed to the relative gain in

earnings made by blacks during the 1940-1980

period. It has not been possible to say which factor

dominatea the trend.

leaving a lower average behind (see O'Neill, 1970). This, too,

would depress the within cohort gains in the South. The effect of

migrants coming into the North is ambiguous, since the migrants

from the South would likely have attended poorer quality schools

than northerners, which m sht be counterbalan td by ability and

motivational factors.

' See Hyman and Shcatsley (1964); Mathews and Prothro (1966);

and Reed and Black (1933i.

The Current Wage Gap and Unmeasured

Characteristics

Although the wage gap narrowed substantially

over the 1940-80 period, it has not been eliminated.

As shown in chapter 6, after adjusting for years of

school completed, region of residence, and other

measurable characteristics, a weekly earnings gap

remained of 12.6 percent for 25-34 year olds, rising

to 24.3 percent for 55-64 year olds.

These are average differentials for an age group

after adjusting for characteristics. There is considerable variation in the size of the earnings gap among

detailed region-education groups and according to

the earnings measure used (hourly, weekly or

annual). The variation in the earnings gap in 1980 is

shown in table 8.3. The differential is larger in the

South than in the non-South, and :t iF, larger among

45-54 year olds than among 25-34 year olds,

particularly in the South. Racial differences in weeks

and hours worked have a substantial effect on the

earnings gap. For instance, among 25-34 year olds

living outside the South, the gap is relatively small

based on hourly earnings: 3.5 percent for college

graduates, 9 percent for high school graduates, and

5,4 percent for those with 8-11 years of school. The

differential is larger when measured by weekly

earnings (ranging from 8.6 percent to 14.5 percent)

and larger yet when measured by annual earnings

(ranging from 11.7 percent to 20 percent).

ft; is a matter of judgment as to whicl is the

correct measure. 14Jurly earnings reflect compensation for a fixed amount of time worked, and in this

sense it is an appropriate measure for making

comparisons between different groups that may

have different work patterns. In fact, if the number

of hours worked during the year were based entirely

on choice (choice to take a second job, work

overtime, search intensively for work when unemployed), hourly earnings would clearly be the

appropriate measure. Weeks and hours worked are

not wholly voluntary, of course, because of layoffs,

uneven options for overtime work, and forces in the

economy that affect the availability of work.'

Moreover, the strength of these involuntary factors

varies by skill and is affected by discrimination. To

Ibid.

1 See chap 3 for a discussion of the implications of coworker and

consumer discrimination for the labor market situation of blacks, ' See the discussion of raual differences in labor force parmipation, unemployment, and hours worked in chap. 2

1 <,.. 4f)

113
TABLE 8.3

Black-White Earnings Gap in 1980 by Region, Age, and Education

Non-Sogth

25-34 years of age

Annual Weekly Hourly

earnings earnings earnings

45-54 years of age

Annual Weekly Hourly

earnings earnings earnings

8-11 yrs 20.0 12.7 5.4 15.2 12.6 6.9

High school 19.3 14.5 9.0 18.9 15.8 10.7

College 11.7 8.6 3.5 28 26.1 20.4

All levels 20.3 15.1 8.6 2 24.9 19.9

South

8-11 yrs 22.7 19.6 13.2 30.8 27.7 21.3

High school 23.9 20.5 13.6 30.1 27.9 23.5

College 19.0 16.5 9.8 37.3 33.2 28.7

All levels 26.7 22.9 16.2 39.4 36.6 31.2

All regions

8-11 yrs. 22.8 18.4 12.9 23.7 20.9 15.4

High school 23.1 19.5 14.1 24.2 21.5 19.1

College 15.4 13.0 7.8 33.1 29.9 23.2

All levels 24.7 20.6 14.8 34.6 31.8 31.3

Note: The earnings gap is measured as 100 percent minus the black-white earnings ratio

Source Appendix D

114

.L: 3
the extent that involuntary forces dominate, weekly

or annual measures of earnings are more appropriate

measures of the effects of both skill and discrimination on earnings. Thus, all three measures of earnings merit examination.

No conclusion can be drawn from table 8.3 about

the extent to which current labor market discrimination reduces the earnings of black men in 1980. The

various measures of the earnings gap cannot realistically be attributed solely to racial discrimination in

the labor market, but also reflect omissions of data

on worker characteristics, such as the quality of

schooling and family background.°

Achievement tests are often used as a way of

assessing the marketable knowledge and skills acquired in schools. The evidence reviewed in chapter

4 showed large differences in scores between blacks

and whites with the same nominal amount of

schooling.'° These differences have been attributed

to differences in family background (parents' education and occupation and family income) as well as to

differences in the quality of schools attended."

Chapter 4 also reviewed several studies that have

attempted to measure the link between earnings and

the skills measured by test scores. Based on the

findings of these studies, a rough estimate can be

made of the extent to which the black-white earnings gap can be attributed to racial . ifferences in the

factors reflected iii L:st scores. Applying estimates

9 Of course, broadly speaking, racial differences in the quality cf

schooling and parents' income and education may also stem from

discrimination This. however, is past discrimination, taking the

form o:- gv,venimental discrimination that provided a lower

quantity and quality of schooling to blacks as well as labor larket

discrimination affecting parents' opportunities It is to be distinguished fro m current discrimination that affects the earnings and

employment of individuals entering the labor market with a an en

set of skills.

'° Black male scores on the Armed Forces Qualification Test are

close to 30 percentiles below these of white males at the high

school and college levels, the differences are smaller at lower

educational levels See chap 4 for a discussion of differences in

various kinds of tests

" In a preliminary analyos of the determinants of school

achievement, a significant link was found between family hackfrom a study by John Hause, about 20 percent of the

weekly earnings gap for 25-34 year olds could be

explained by score differences at the high school

level and about 40 percent at the college level. Based

on a study by Zvi Griliches and William Mason,

about one-third of the gap for all schooling levels

combined could be explained by differences in

scores.'2

These results should be regarded as conservative

estimates of the proportion of the earnings gap

attributable to racial differences in unmeasured skill

factors. The studies on which the estimates are based

understate the relation between scores and earnings,

perhaps by a significant margin.'3

In summary, the extent to which current discrimination in labor markets reduces the earnings of black

men cannot be answered definitively. Comparing

the earnings of black and white men with the same

schooling, age, and region, a differential still is found

in 1980. There is persuasive evidence that a part of

this "unexplained" gap is attributable to unmeasured

differences in the knowledge and skills gained in

school. These differences, as measured by a large

gap in achievement test scores, potentially reflect

factors such as relatively inferior schooling and a

disadvantaged family background. Persistent racial

discrimination may well account for part of the

differential, but its share cannot be measured with

available data.

ground and scores on the AFQT. For example, parents education

and employment in a white- collar occupation are significantly

positively related to scores, a large number of siblings is

associated with lower scores.

12 See the discussion of these studies in chap. 4

" The similes typically use data sets that contain a much richer

catalogue of variables than are available in the census data

variables such as parental income and education, prior earnings.

military performance, etc The reported relation betweea scores

and earnings typically shows the net effect of scores, holding

constant an array of other factors that affect scores or are colinear with scores. The effect of scores on earnings, holding

constant only schooling, r..gion, and age, would be significantly

larger, and it is this relationship that is needed to adjust our

measure of the earnings gap, which is based on the more limited

census variables. See chap 4 for further discussion.

1 r^ 47

-A. is: ..1

115
Concluding Comments

Changing racial differences in measured characteristics, like years of schooling and geographic

region, account for some of the narrowing in the

wage gap between 1940 and 1980. According to the

data analyzed, however, these changes were not the

primary forces underlying the trend.

Black-white earnings ratios rose considerably

from generation to generation even when the comparison was confined to population groups narrowly

defined by years of schooling, region, and age.

There is evidence that improvements in the quality

of schools attended by blacks and declining discrimination in the labor market both contributed to the

relative gain in earnings made by blacks during the

1940-1980 period.

The decline in labor market discrimination appears to have occurred both before and after the

Civil Rights Act of 1964 was passed. In the earlier

period, the decline in discrimination may have been

prompted by events, such as World War II, which

raised the consciousness of white Americans about

racial prejudice. In the recent period, the civil rights

movement and government antidiscrimination policy undoubtedly have played a positive role.

Although the wage gap narrowed substantially

over the 1940-1980 period, it has not been eliminated. After adjusting for years of school completed,

region of residence, and other measurable characteristics, a gap in weekly earnings of 12.6 percent for

25-34 year olds remains. The remaining gap is in

part attributable to unmeasured differences in worker characteristics that affect productivity. For instance, racial differences in achievement test scores

116

1"4J

suggest that black-white differences still exist in

terms of knowledge and skills acquired in school.

Persistent racial discrimination in labor markets may

well account for part of the current differential in

earnings, but its share cannot be determined with

available data.

What Has Happened Since 1980?

The black-white gap in earnings has remained

roughly constant since 1975. The constancy of the

gap during the 1980s is noteworthy because that

period was characterized by the worst recession

since the 1930s. (The overall male unemployment

rate grew from 5.1 percent in 1979 to 9.9 in 1982 and

1983 and then fell back to 7.0 in 1985.) In view of the

greater cyclical sensitivity of black earnings and

employment, it would not have been surprising to

see the relative earnings and employment status of

blacks deteriorate and then rebound during this

period. Such a pattern seems to appear in annual

earnings data from the Current Population Survey.

However, the black-white ratio of annual earnings

for full-time year-round workers stayed relatively

constant during the periodabout 70 percent. Differences in labor force participation rates have also

remained constant, breaking a decades-long trend of

relative decline in black male labor force participation.

Issues for Future Research

This report has identified several issues that

remain unresolved and warrant additional research.

The following are particularly important:
Existing research has not been able to assess

fully the effects of specific civil rights programs

and policies on the economic status of blacks. For

instance, although studies of affirmative action

have found that Federal contractors increased

their employment of blacks more than noncontractors, it is not known whether the men hired by

contractors would have been employed in good

jobs even without the program or whether the

program resulted in a net increase in black male

employment. More research is needed to determine the full effect of civil rights programs on the

earnings and employment of black men.

This report documents that there is still a

substantial differential b the educational attainment of black and white men in terms of both

years of school completed and scholastic achievement. A considerable body of research, including

this report, has demonstrated the importance of

schooling as a means of upward mobility. Future

research should investigate the various public and

private factors that affect scholastic achievement.

The decline in labor force participation among

younger black men, at a time when other indicators of economic success (i.e., earnings) have been

improving, is not well understood. Several causal

factors were suggested, including worsened employment opportunities, increased involvement in

crime and imprisonment, and declining marriage

rates. These and other possible factors, and their

interactions, should be investigated in greater

depth. Research dealing with effects of diminished

work attachment on the future earnings and

employment of younger men is also needed to

help assess the importance of the recent trends.

Accurate measures are needed of the possible

upward bias in earnings resulting from the decline

in labor force participation. Existing research has

used indirect statistical methods to estimate the

possible effect of "selection bias" on earnings

gains and on the black-white earnings gap. Direct

information on the prior earnings of those who

withdraw from the labor force is needed before

any firm conclusions can be drawn. If the earnings

gains of black men are found to be seriously biased

by labor force withdrawal, then it would be

necessary to reevaluate the extent to which

discrimination has abated and, specifically, the

extent to which civil rights policies have raised

the economic status of black men.

The failure of the black-white gap in unemployment to narrow is puzzling in view of the

convergence in education and occupational status.

Research on this subject is limited, and additional

theoretical and empirical work is needed.

117
Statement of Chairman Clarence M.

Pendleton, Jr.

This report is another top-quality product of the

Civil Rights Commissionan outstanding example

of unbiased and professional research, advanced

methodological techniques, and most important,

commitment to alerting the Nation to the harmful

effects of discrimination and the beneficial effects of

reducing discrimination. I am pleased that this

report has already received wide coverage and wide

praise, and I look forward to future Commission

volumes on the status of other groups in American

life.

But if this report is a tribute to the diligence of our

staff, it stands as a testament to the strugglesand

achievementsof black men in America. Faced

with slave code: that forbade them to read, confronted by a poo: southern agricultural economy,

denied equal opportunity until the passage of the

Civil Rights Act in 1964, black men have nevertheless pushed themselvesclosing the wage gap by

nearly half between 1940 and 1980.

When it comes to education, black men have

overcome enormous hurdles to win opportunities for

themselves. In 1940, for instance, southern black

men had just an average of 5 years of schooling.

Today, the average black man in the South has close

to 11 years of schooling. By 1980 the national

difference in years of schooling between black and

white men was just 1.5 years. No one made these

black men stay in school; they did it themselves.

Some individual achievements elicit amazement

and respect. All-black, segregated Dunbar High

118

School in Washington, D.C., sent 34 of its graduates

to Amherst between 1892 and 1954. One-fourth of

those admitted made Phi Beta Kappa. Young blacks

hitting the books in the face of segregationthat

speaks volumes about their character. It also suggests that a quota is no way to motivate students, for

it only sends the message that they can't make it on

their own.

The massive, arduous migration of blacks northward is one of the inspiring stories in American

history. As the report notes, in 1940 more than

three-fourths of blacks lived in the South. Today, it's

barely half. These days the gains from migration

may be less substantial. But the point remains the

same: when blacks have made the trek to prosperous

areas of the country it has paid off.

The rising income of black men recalls Irving

Kristol's comment: "We know how most people,

most of the time, emerge out of poverty." His

answer is the obvious one: a growing economy and

individual motivation are the springs that have

propelled most groups in American life. Quotas and

special preferences, by contrast, are a dubious

method of promoting economic success.

True, this report acknowledges that civil rights

laws and enforcement have boosted the incomes of

black men in America, but it also suggests that there

is no substitute for self-helpwhether it means

staying in school or migrating to better jobs. This is

what really works. Yes, blacks have traveled the
toughest roads in American history, but the path to

prosperity is the same for all Americans.

119
Statement of Commissioner John H. Bunzel

Joined by Vice Chairman Murray Friedman

and Commissioners Esther G. Buckley and

Robert Destro

This report is the first of several planned volumes

of the Commission's incomes of Americans project.

When the Commission adopted this project in 1984,

at the suggestion of Commissioner John H. Bunzel,

the intention was to examine thoroughly the myriad

of factors, including discrimination, that account for

the differences in incomes between men and women

of different racial and ethnic groups in America. It

soon became clear that an exploration of all the

relevant determinantseducation, region, discrimination, etc.of all the relevant groups would be too

voluminous to be published in a single study. Future

volumes will examine the conditions of many other

racial and ethnic groups in American life, but this

first volume is confined to an exploration of the

economic progress of black men in America.

Unfortunately, the history of discrimination

against black men in America is still being written.

One need only read the newspapers to know that

black men still face violations of our nation's

antidiscrimination laws. And one need only apply a

bit of common sense to recognize that black men still

cope with a legacy of segregationofficially sanctioned until less than 25 years ago.

The great virtue of this report is that it unearths

new facts about black men in America that are not

commonly known and not easily discerned. It is a

thorough analysis of the obstacles black men have

faced and continue to face. And it also illuminates

those factors that have allowed black men to close

120

.15

the earnings gap from 44 percent of white men in

1940 to 72 percent in 1980.

We are gratified that scholars with different views

and interests have commented favorably on this

study, including Reynolds Farley, University of

Michigan; Nathan Glazer, Harvard University;

Glenn C. Loury, Harvard University; Barry Chiswick, University of Illinois-Chicago; Orley Ashenfelter, Princeton University; Robert Margo, Colgate

University; and Stephan Thernstrom, Harvard University.

We are especially impressed by the breadth of the

report. Education, religion, occupation, government

programs, economic growthvirtually every factor

that might account for the rise in the earnings of

black men over the past 40 years is scrutinized,

utilizing sophisticated social science methodologies.

While other studies have focused on a few sources of

black income gains, this study examines the whole

spectrum of factors. No issue is sidestepped.

Furthermore, the report makes use of and examines newly available census tapes from the 1940s, a

decade of enormous significance to the economic

progress of black men. As originally designed, the

study was limited to the period from 1950 to 1980,

but the availability of new data from the 1940s

proved to be an unexpectedly rich resource, offering

a fuller picture of the condition of black, men in

post-World War II America. It showed that the

boost in black earnings caused by the economic
expansion of World War II was not ephemeral.

Black men not only gained ground in the 1940s, but

held it during the 1950s. Indeed, the finding that the

incomes of black men climbed sharply during the

1940s and 1960sboth decades of impressive nationwide economic growthsuggests that blacks, more

than Americans on average, benefit from a robust

economy. One caveat, however: the data presented

here suggests that the efforts of black men themselveswhether spending more years in school or

undertaking difficult migrationsaccount for much

of their progress.

From such a rigorous and wide-ranging study

come difficult and sometimes subtle findings that are

unlikely to serve the interests of those on the left or

the right who regularly look for results to support

their own political agendas. The report underscores,

for instance, the decline in prejudice and discrimination in America that has surely benefited black men,

allowing them to take advantage of employment and

educational opportunities heretofore denied them.

Yet the report does not rush to a definitive or

absolute judgment about the role that civil rights

laws and their enforcement have had in tempering

prejudice. It reaffirms what is not in disputethat

these laws have had a substantial impact. But it also

makes clear that this impact is only one of a cluster

of influential factors that is not readily identifiable,

by itself, in a st.ict cause-and-effect manner. Those

who label affirmative action as completely ineffectual, or even an economic burden for blacks, will not

find political fodder in this study. Nor will the

report satisfy those who insist that affirmative action

is the predominant factor in promoting black economic progress. As is so often the case, the truth that

emerges from scholarly research is more contingent

than final.

Finally, we are pleased with the dispassionate tone

that runs throughout the pages of this report.

Contrary to what some have said (many of whom

have not read the report in its entirety), there are no

villains here. Government programs, for example,

are neither belittled nor dismissed. It is merely

observed that certain Federal transfer payments,

most notably social security, have allowed disabled

black men to leave the labor force at rates higher

than white men. Some have called this conclusion

"diabolical" and "pernicious." That anyone could

subject the data presented here to such verbal abuse

leaves us baffled and disappointed.

It should be emphasized, finally, that this study is

not the last work on the economic progress of black

men. The report itself identifies several unsolved

issues for the research agendas of social scientists.

We believe that more research is needed to examine

and explain the differential in wages of various

groups in American society. We encourage other

scholars to pursue the line of inquiry begun here.

(Some suggestions are offered in the Executive

Summary.) Only by understanding and identifying

the obstacles facing black men can we hope to find

solutions that work. And only then can we build the

equal opportunity society we all want.

-, 1-) -+- ii U

121
Dissenting Statement of Commissioners

Mary Frances Berry, Francis S. Guess, and

Blandina Cardenas Ramirez

In stark contrast to the emphasis of this report,

black male unemployment and underemployment

remain serious problems in our country. The Commission had an opportunity to make a significant

contribution to policymaking designed to alleviate

the problem by analyzing the elements that account

for progress and for its absence. Instead, we are

presented in this report with definitive conclusions

based on an analysis of economic data that most

scholars conclude should not be be the basis for

definitive conclusions and that will not facilitate

solutions to the problem. We are provided with

policy pronouncements that are in most cases no

more than a rehash of a Department of Laborfinanced Rand Corporation study by James Smith

and Finis R. Welch, "Closing the Gap," which was

released to the public in February 1986 and has the

same methodological problems. Mr. Welch is ubiquitous. In addition to being the principal researcher on

the Commission's school desegregation study, he is

also the chairman of the advisory committee responsible for the report approved today.

Today's report concludes essentially that social

security disability retirement for older black men

and AFDC and other transfer payments have

reduced labor participation rates for black men, thus

reducing economic progress. One-sided evidence is

presented for the first proposition, and no evidence

for the second. These conclusions may lead policymakers to believe that black workers who are

seriously disabled should be denied disability payments. Given the high rates of hypertension and

122

other cardiovascular diseases in the black community, as well as the greater likelihood that black men

who have jobs work in hazardous environments,

such a conclusion would be pernicious at best. Also,

scholars have found that while black adult workers

apply for social security disability at a higher rate

than whites, they are less likely to be designated

eligible to receive such benefits.

The emphasis on transfer payments as a cause for

nonparticipation in the labor force unnecessarily

directs attention away from the fact that most

unemployed young black males do not participate in

transfer programs. In addition, the effects of demographic considerations, such as the projected declining numbers of young people available to work, are

not even analyzed.

The report also attempts to undercut previous

scholarly studies that attest to the importance of

civil rights enforcement. This undercutting is

achieved by using as a touchstone whether overall

black employment was enhanced as a result of Title

VII and OFCCP. That is precisely the wrong

question. The purpose of outlawing employment

discrimination and requiring affirmative action was

to increase the opportunities for qualified blacks to

gain better paid employment. The programs have

done that and indirectly have improved the prospects of some blacks. They were not designed with

the idea that all blacks would have their employment thus guaranteed. In addition, available data on

the employment picture for educated blac:.s, given

the decline in Federal emphasis on affirmative action
enforcement since 1980, would provide a much

needed corrective to the analysis in the report.

The most striking failure of the report is to

analyze the demand side of the picture, including

such matters as the economy, trade deficits, bucle-t

deficits, and deindustrialization in "smoke-stack"

industries. There is an assumption that jobs have

been freely available to every person who has

wanted one in every period since 1940. Such a

conclusion is patently false.

A study analyzing how improvements in education and motivation, along with reductions in narcotics selling and addiction and other criminal

activities, and an economy that produced enough

jobs, and strong employment discrimination enforcement could improve the economic progress of black

men would make a major contribution to public

policy. This is not such a study.

1 ' r) -,.. , ) 4

123
Appendix A

Data Development

Background

This appendix documents the construction of files

used to analyze long term trends in earnings and

labor force status. The sources of data are the

decennial Censuses of Population conducted by the

U.S. Bureau of the Census between 1940 and 1980.

These surveys are unique in that they contain

information from a very large number of individuals

over an extended number of years about earnings in

the previous calendar year, weeks and hours

worked, and demographic characteristics.

Several new sources of decennial census data have

become available to researchers recently. Microdata

samples from the 1980 census were released in 1983,

and similar information from the 1940 and 1950

censuses became available in 1984, as a result of a

long term archival project sponsored by the Census

Bureau. Along with similar data from the 1960 and

1970 censuses, which have been available for several

years, these sources of information permit a comprehensive review of long term market. trends.

The task of data development is defined by the

issues to be analyzed. Principally, these topics

include: analysis of labor force status (employment,

unemployment, etc.), and earnings (means and variances for annual, weekly, and hourly earnings). It is

necessary to tabulate the data on the basis of detailed

demographic categories, including age, race, sex,

education, region, etc.

In order to simplify data processing and analysis,

summary (or grouped) data files were designed and

constructed. These files simplify subsequent data

processing by partially aggregating available information into data sets that incorporate similar variables and record formats. Each of the five censuses

have been grouped according to a common format.

124

The constructed files are sufficiently flexible that

tabulations can be generated at both detailed and

higher levels of aggregation. The summary files

greatly reduce the cost of subsequent data processing compared with direct manipulation of the

microdata files. The 1980 census alone, for example,

contains information on more than 2 million individual.. Unstructured processing of this volume of

information (multiplied by the use of several censuses) would be prohibitively expensive.

For each year, the summary files contain information on labor force status and earnings for groups of

individuals cross-classified on the basis of the following "cell-defining characteristics": age (10), race (2),

martial status (2), employment class (3), industry (4),

region (4), weeks and hours worked (8), and years of

schooling completed (6). These dimensions are

generally conformable across censuses, and for each

group a number of summary variables are tabulated.

There have been several conceptual changes with

respect to the measurement of labor force status and

earnings over the past 40 years. To the extent such

changes affect the development of conformable

working files, they are described below. One notable

example is the use of the concept of "full-time

equivalent weeks worked" in 1940 compared to the

enumeration in later censuses of the number of

weeks in which any work was performed. Similarly,

the only earnings information collected in 1940

reflects wages and salariesdata on self-employment income were not collected.

I .3
TABLE A.1

Summary File Characteristics

Census

survey year

Summary

cells'

Individuals

represented

1980 80,208 1,444,000

1970 62,684 1,192,100

1960 52,832 1,043,000

1950 31,136 291,130

1940 27,031 854,380

/Each oat or observation. represents a unglue combination of the ceii-defintng charactenstics, e g , sex, age. race, listed above

Input and Output File Characteristics

Basic Characteristics of Input and Output Files

The summary files have been developed directly

from Census Bureau public use samples. For 194.0

and 1960-1980, the basic public-use samples reflect

1/100 samples of the U.S. population. For 1950,

however, data on labor market variables are available for only "sample line" records that constitute a

1/330 sample of the U.S. population.

In 3 years more than one public-use sample is

available to the researcher. The 1980 data are drawn

from the "C" sample; 1970 data reflect individuals

who answered the "5 percent" questionnaire; and

for 1940, the self-weighting sample is used.

AU summary files incorporate information on

individuals ages 16-64 in the noninstitutional population, including members of the armed forces.

The summary files contain observations defined

by a specific interaction of the cell-defining characteristics described above. The number of nonempty

cells in the constructed files and the number of

individuals reflected in these data sets are described

in table A.1.

The summary files were constructed by Commission staff to be used in a number of studies. Not all of

the variables described below are used in the

analysis of adult black and white men included in

this report.

Cell-Defining Characteristics

As described above, the census summary data files

all utilize the same basic format and variables. Fach

contains information on groups of individuals defined by the interaction of the cell-defining variables.

The definition of selected characteristics and their

comparability across censuses is detailed below.

1. Age

0 = 16-19

1 = 20-24

2 = 25-29

3 = 30-34

4 = 35-39

5 = 40-44

6 = 45-49

7 = 50-54

8 = 55-59

9 = 60-64

2. Region

1 = Northeast

2 = North Central

3 = South

.1 S 4

125
4 = West

Data on Alaska and Hawaii are not available prior

to 1960. For 1960 to the present, these States are

included in the West.

3. Employment Status

1 = Se lf-er. "oyed

2 = Salary workers

3 = Unpaid family workers and others

For the 1970 and 1980 censuses, the self-employed

are defined to include individuals with either incorporated or unincorporated businesses. This maintains consistency with earlier censuses but differs

from current census definitions that include only the

latter as self-employed. For 1940 the self-employed

are defined to include "employers" and "individuals

working on own account."

The "salary workers" category includes both

wage and salary workers and government workers.

Government workers, however, can be identified

through the industrial sector classifier, as described

below. The residual employment class category

includes unpaid family workers and individuals who

have not worked in previous years. Employment

class questions refer to the current or most recently

held job. This job may differ from that held in the

previous year (which would be reflected in reported

earnings).

4. Industry

1 = Agriculture

2 = Private, nonagriculture

3 = Government

4 = Other

Industry categories are defined by a combinatior.

of the industry and employment class variables. All

individuals coded as Federal, State, or local government employees, except members of the armed

forces, are counted as government workers (category 3). Categories 1 and 2 include only private

sector workers and are based on industry codes for

current or most recent job.

For 1950-1980, the "other" category includes

individuals who have not worked in (at least) the

previous 5 years as well as members of the armed

forces. Individuals in the armed forces, however, are

the only members of this group who also report

earnings (the earnings of members of the armed

forces can be identified uniquely). In 1940 the

residual category includes "workers on emergency

public service projects" as well as individuals currently out of the labor force (even if they had

earnings in 1939). Of the individuals included in this

126

1.,5

category, only the "emergency" workers can have

earnings. The armed forces cannot be uniquely

identified from 1940 data.

For the censuses, industry questions refer to the

current or most recently held job. This, again, may

differ from that of a job held in the previous year,

which is reflected in reported earnings.

5. Marital Status

1 = Currently married

2 = Not married

The "currently married" category is defined to

include all individuals who are married with a

spouse either present or absent. The "not married"

category includes individuals who are either separated, widowed, divorced, or never married.

6. Educational Attainment

1 = 0-7 years of schooling completed

2 = 8-11 years of schooling completed

3 = 12 years of schooling completed

4 = 13-15 years of schooling completed

5 = 16-17 years of schooling completed

6 = 18+ years of schooling completed

In 1940 and 1950, the open-ended educational

category reflects 16+ years of schooling completed.

All such individuals are included in category 5.

7. Labor Force Attachment (1950-1980)

1 = Part-year/At work: Nonzero earnings; 1-39

weeks worked last year, positive hours worked in

survey week; not enrolled in school.

2 = Part-year/Not at work Nonzero earnings; 1-39

weeks worked last year, zero hours worked in

survey week; not enrolled in school

3 = Full year/Full time: Nonzero earnings; 50+

weeks worked last year; 35+ hours worked in

survey week; not enrolled in school.

4 = Most year/At work: 40+ weeks worked last

year; positive hours worked in survey week; not

enrolled in school.

5 = Most year/Not at work: 40+ weeks worked last

year; zero hours worked in survey week; not

enrolled in school.

6 = Nonworking students: Currently enrolled in

school, did not work last year.

7 = Working students: Currently enrolled in school,

worked last year.

8 = Nonworkers: Nonstudents, did not work last

year or zero earnings.

The labor force attachment classifier is a key

element in defining applicatim.., of the file. It is based

on (i) the number of weeks in which an individual

worked in the previous calendar year and (ii) the
number of hours an individual worked in the survey

week. The latter represents the only information

available on hours per week that are available before

1980 from the cizcennial censuses.

This classifier can be manipulated in alternative

ways to produce measures of current labor force

status, annual and weekly earnings, and hourly

earnings. To produce measures of labor force status

(unemployment rates, labor force participation rates,

etc.) for various demographic groups, aggregates are

taken over the populationall possible values of the

labor force attachment classifier are included. For

determining annual and weekly earnings measures,

the sample is restricted to individuals who worked in

the previous calendar year (categories 1-5, 7). For

determining hourly earnings, the sample needs to be

restricted to individuals with positive hours in the

survey work (categories 1, 3, 4). This, of course,

excludes individuals who were unemployed or out

of the labor force in the survey week. The impact of

their exclusion on earnings measurement is analyzed

in appendix B.

The 1940 census utilized a different concept for

measuring weeks and hours worked by attempting

to determine "full-time equivalent (FTE) weeks

worked," as opposed to the number of weeks in

which an individual did any work. Full-time equivalent weeks calculations were based on the regional

norm for full-time hours or 40 hours per week. As a

result of this alternative treatment of weeks and

hours worked, labor force attachment classifiers for

the 1940 file are not fully comparable with those for

other years. The 1940 categories are as follows:

1 = Part-year: Nonzero earnings; 1-26 FTE weeks

worked, not enrolled

2 = (not defined)

3 = Full year/Full time: Nonzero earnings; 50 +

FTE weeks, not enrolled

4 = Most year: 27-49 FTE weeks; not enrolled;

5 = (not defined)

6 = Working students: Currently enrolled, worked

last year.

7 = Other students: Currently enrolled, did not

work last year.

8 = Nor.workers Did not work last year; zero

earnings; nonstudents.

Summary Variables

For each of the groups defined by a unique

interaction of the above characteristics, 18 summary

variables are tabulated. These variables are defined

and explained below:

1 - Cell Population Count: Unweighted person

count

2 - Cell Count: Employed

3 - Cell Count: Unemployed

4 - Cell Count: Out of labor force

5 - Cell Count: Armed forces (1950-1980) and

(1940) workers on emergency public projects

6 - Cell Total: Years of schooling completed

This variable is used to calculate mean years of

schooling completed. It is necessary to impute

values for open-ended schooling category. For

1960-1980, individuals with 18+ years completed

were imputed a value of 19. This estimate was

derived from 1980 census data. For 1950 the

cutoff was 16+ years, and a value of 17.0 was

imputed for males, 16.7 for females. For 1940 the

cutoff was 17+ years, and 18.2 was imputed for

males and 11.9 -..as imputed for females. These

latter figures were e.:rived from 1960 census

tablations.

7 - Cell Count, Attending School

8 - (Census) Cell Count, Native Born

9 - Cell Total, Weeks Worked (1950-1980)

This question refers to weeks wor-ed in the

previous calendar year. It is not defined for 1940.

In 1960-1970, only interval measures of weeks

worked were defined. To maintain comparability,

an identical specification was imposed for each

year. The following means were calculated from

1980 census data and imputed for the intervals: (1-

13 weeks: 8.1 weeks imputed; 14-26: 20.8; 27-39:

33.1; 40-47: 42.4; 48-49: 48.3; 50-52: 51.8).

10 - Cell Total, Total Hours Worked (survey

weeks' hours).

For 1950-1980, this variable is constructed as

weeks multiplied by hours in survey week. The

following values were used to recode hours'

intervals: 1-14: 8.8; 15-29: 20.9; 30-34: 31.2; 35-

39: 36.5; 41-48: 45.2; 49-59: 51.9; 60 +: 67.5. For

1940 this variable is calculated as full-time equivalent weeks multiplied by 40.

11 - Cell Total, Total Hours Worked (usual hours)

Available only from 1980 census. Defined as

weeks multiplied by usual hours per week in

previous calendar year.

12 - Cell Total, Wage and Salary Income

This variable (as well as 13 and 14) refers to

earnings in the p-evious calendar year.

13 - Cell Total, Self-Employment Income

127
TABLE A.2

Conditional Means of Earnings for Males at Truncation Limit

Year 1980 1970 1960 1950 1940

Reporting limit ($1,000): 75 50 25 10 5

Sex Race Educ. Age Level (000s)

M White LE 15 LE 34 105 70 35 13.4 7.2

M White LE 15 35+ 110 74 38 14.9 8.3

M White 16+ LE 34 112 74 38 14.5 71

M White 16+ 35+ 136 82 44 18.7 15.2

M Nonwhite LE 15 LE 34 108 86 38 13.1 7.4

M Nonwhite LE 15 35+ 108 71 41* 13.1 7.6

M Nonwhite 16+ LE 34 106 89* 41* 11.6* 8.0*

M Nonwhite 16+ 35+ 143 99 48* 15.0 7.4

*No individuals in this category exceeded reporting limit Values for these cells were assigned by assuming a proportional relationship with other cells

This information was not collected in 1940. For

1950-1970 this includes farm self-employment

income.

14 - Cell Total, Farm Self-Employment Income

This variable is defined for 1980 file only.

15 - Cell Total, Usual Hours per Week (continuous

values)

This variable is defined for 1980 file only and

refers to previous calendar year.

16 - Cell Total, Hours in Survey Week (recoded

values)

This variable is not defined for 1940 file.

17 - Cell Total, Weekly Earnings

18 - Cell Total, Age

Means for Open-ended Earnings Intervals

A final issue that was addressed was the imputation of earnings for individuals with earnings above

the reporting limit. Estimates ( f condi' onal means

were developed using the Pareto - >...siod (see

Technical Documentation, '040 Cen t,f Population, p. 164). Conditional means were es mated for

eight demographic groups. The "preceeding inter128

val" used in construction of these estimates was set

at the 65th percentile of the demographic-groupspecific earnings distribution. As a rough check on

the accuracy of the Pareto method, the mean level

of wages and salaries for individuals with income

above $75,000 (the 1980 census cutoff) was calculated from the microdata used to construct IRS

Statistics of Income, which are not truncated. The

overall conditional mean was $122,000 from the IRS

data, $124,000 using the Pareto technique on census

data. The full set of conditional means for all years is

listed in table A.2.

Conditional means were also imputed for individuals who report the maximum allowable losses. This

is not relevant for 1940, where only wages and

salaries were reported. In 1950 losses were noted,

but values were not reported. Roughly 65 percent of

individuals with losses reported the maximum possible amount: -10,000 in 1960-1980. The following

values were imputed for individuals with losses at

the truncation point: 1950: -6,500; 1960: -10,000;

1970: -15,000; 1980: -20,000.
Appendix B

The Impact of Sample Definition on Relative Earnings

Background and Issues

The analysis of earnings trends requires that the

populations of interest be consistently defined. Operational decisions are required about the treatment of

classes of workers that, for various reasons, present

unique problems with respect to the measurement or

interpretation of earnings. Such groups, for example,

include members of the armed forces, students,

unpaid family workers, and the self-employed. Decisions about the inclusion or exclusion of such groups

affect estimates of relative earnings patterns and

trends. This appendix examines the sensitivity of

earnings measurement to the inclusion or exclusion

of such groups.

Competing goals must be considered when selecting the sample for analysis. First, it is desirable to

utilize as much of the available data as possible. A

second coal is to assess "total" compensation, which

includes nonpecuniary as well as monetary rewards.

Such ideals, however, often conflict with the limitations of available data and the desire to present easily

interpretable results. Examples of special problems

are discussed below:

Armed forces: The distinction between military

and civilian employment has become increasingly

blurred in recent years as the armed forces compete

in the labor market for workers. Historically, however, conscription has permitted the armed forces to

fill certain manpower needs without raising wages.

Military pay thus might not fully reflect workers'

productivity. The uniqueness of the military employment, however, is often overstated. Even at the

height of the Vietnam conflict, for example, only 40

percent of military accessions were draftees. The

military must compete for reenlistments and career

personnel. Nevertheless, measurement of military

compensation is particularly difficult because a large

share of compensation in the armed forces is "in

kind," i.e., food, shelter, clothing.

Unpaid family workers: An extreme example of

problems in measuring compensation is reflected in

the class of "unpaid family workers"individuals

who work without pay in a family farm or business.

Although these individuals produce goods and

services for the marketplace, they are not paid a

regular wage. Instead, their earnings are implicitly

counted with those of other family members. Fortunately, this group makes up a very small share of the

labor force.

Students: Individuals enrolled in school also complicate the interpretation of labor force data. Most

students participate in the labor market at some time

daring a given year, but they differ in some

fundamental ways from other labor market participants. The market work of students, particularly

students in their teens and early twenties, is often not

their principal activity. Students, instead, choose to

forego current earnings in order to gain higher

compensation in later years. For many older students, however, school is only a minor activity and

market work represents their principal focus.

Self-employment: The self-employed present yet

another difficulty for the measurement and interpretation of labor market activity. The returns on

owning and operating a business (measured as "selfemployment earnings" in the census data) surely

reflect, at least in part, the returns on individuals'

financial investments in their businesses. Thus, it is

not possible to separate fully the extent to which

self-employment earnings reflect returns on labor or

capital. As discussed below, the self-employed tend

to have higher earnings than others; there are large

74 ,1 (,).)

-A.

129
racial differences in the extent of self-employment,

and there are important trends in its prevalence over

time. Thus, analysis of relative earnings patterns may

be influenced by the treatment of this group.

Sensitivity Analysis

The census data permit calculations to be made

that either include or exclude any of the "problem"

groups described above. Similarly, earnings can be

defined to include wage and salary income or total

earningsthe sum of wages and salaries and selfemployment income.'

Tables B.1.1-B.1.2 present basic earnings tabulations for students, the self-employed, and the armed

forces in the labor force. The tables report the share

of all individuals with earnings in the previous year

in these sectors as well as mean levels of weekly and

annual earnings for 1950-1980. Data from 1940 are

not utilized in this exercise due to the inability to

identify earnings for the self-employed and members

of the armed forces for that year. Results are first

presented for all workers aged 16-64 (table B.1.1)

and then separately for 20-24 year olds (table B.1.2),

a group particularly affected by treatment of students and the armed forces.

These tables reveal the following, not very surprising, patterns:

Members of the armed forces have lower

money earnings than "other" workers, and the

earnings of blacks relative to whites in this sector

are high (compared to the "other" sector).

In 1980 the share of black employment made

up by the military is greater than among whites.

This is a reversal of the historical pattern.

Students have lower earnings than "others,"

and the relative earnings of blacks in this sector

are high (compared to the "other" sector).

The share of workers who are students is

higher among whites, but has risen over time for

blacks.

More whites than blacks are self-employed.

This difference has grown over time.

The self-employed have high earnings, and

there are large racial differences in earnings

among the self-employed.

The impact of the treatment of these groups on

earnings ratios is reported in table B.2. This exercise

begins with an all-inclusive labor force definition.

' It should be noted that employment class reflects a principal

current job. The nonself-employed can have self-employment

income as a result of a secondary job or self-employment at some

130

Students, unpaid family workers, the self-employed,

and finally members of the armed forces are then

sequentially excluded.

The results indicate that inclusion of students in

earnings tabulations tends to equalize racial differences. For the labor force as a whole (ages 16-64),

however, the total impact is only about one percentage poilit. The exclusion of unpaid family workers

has a trivial impact on earnings ratios due to the fact

that they are a very small share of worker: less

than one-third of 1 percent in 1980.

Exclusion of the self-employed narrows racial

differences in earnings. This is attributable to the

fact that the self-employed are dispropi,rtionately

white, and there exist substantial racial differences in

earnings among the self-employed. The magnitude

of this effect, however, has diminished somewhat

over time.

When the focus is limited to those not self-employed, utilization of data on wages and salaries

(instead of total earnings) raises relative earnings by

less than a percentage point. This is due to the fact

that white wage and salary workers report more

self-employment income than black wage and salary

workers.

Finally, the armed forces historically tended to

narrow earnings differences by something less than a

percentage point, the result of a small earnings gap

in this sector. In 1980, however, this pattern was

reversedinclusion of the armed forces widened the

pay gap. This issue is discussed in more detail below.

Tables B.2.1-B.2.4 present the results of a similar

but more limited exercise that is disaggregated by

age group. The base tabulations utilize total earnings

and exclude only unpaid family workers. In sequence, students, the self-employed, and armed

forces are excluded. ThP latter tabulations, which

exclude the self-employed, are based on wages and

salaries alone. The results indicate, not surprisingly,

that the exclusion of students lowers earnings ratios

substantially for young people but has almost no

impact on older workers. In contrast, exclusion of

the self-employed raises earnings ratios by several

percentage points for older workers and has a small

impact on the relative earnings of the young.

Similarly, exclusion of the armed forces has little

impact on the relative earnings of older workers but

point during the precious calendar year Consersely. the selfemployed can have wage and salary income
plays an important role in assessing earnings of

younger workers.

TABLE B.1.1

Earnings of White and Black Males by Labor Market Group, AU Ages

1980:

White

Students

Selfemployed

Armed

forces Others

% LF 12.5 11.1 1.9 74.5

Annual 6226 23832 10704 16972

Weekly 193 498 224 362

Black

% LF 12.9 3.5 4.0 79.6

Annual 5786 14165 7703 11616

Weekly 190 327 169 26

1970:

White

% LF 11.5 10.9 3.5 74.1

Annual 4868 23276 8878 16203

Weekly 177 477 199 340

Black

% LF 8.3 4.4 3.6 83.7

Annual 4297 11148 7248 9987

Weekly 167 246 162 218

1960:

White

% LF 7.4 13.5 3.6 75 6

Annual 3889 15707 7460 12267

Weekly 140 326 156 260

Black

% LF 4.9 6.2 2.6 86.2

Annual 3047 4838 5688 6676

Weekly 104 111 120 154

1950:

White

% LF 5.4 18.7 3.2 72.6

Annual 2893 9925 6350 8454

Weekly 104 208 133 185

Black

% LF 4.0 13.9 1.9 80.2

Anrual 2202 2722 3916 4841

Weekly 75 64 87 113

Note All earnings figures are presented in 1980 dollars, to adjust for inflation

1

1

131
TABLE B.1.2

Earnings of White and Black Males by Labor Market Group, Ages 20-24

1980:

White

Students

Selfemployed

Armed

forces Others

`)/0 LF 23.3 3.3 4.4 69.0

Annual 5065 13365 6835 9724

Weekly 160 234 144 224

Black

`)/0 LF 19.4 1.0 10.0 69.5

Annual 4636 5888 5935 7176

Weekly 151 149 130 180

1970:

White

% LF 25.3 2.2 12.6 59.8

Annual 4639 10239 5697 9361

Weekly 162 224 124 216

Black

% LF 11.8 1.5 11.2 75.7

Annual , 4338 4928 5096 7284

Weekly 152 120 117 173

1960:

White

% LF 19.1 3.0 12.0 65.8

Annual 4241 7662 4728 7421

Weekly 139 168 99 175

Black

% LF 97 2.8 7.9 79.6

Annual 3581 2605 3957 4541

Weekly 111 61 85 113

1950:

White

`)/0 LF 16.8 6.7 10.0 69.0

Annual 3520 4986 4098 5694

Weekly 113 110 84 133

Black

% LF 9.3 8.1 7.1 75.5

Annual 2540 1786 3708 3902

Weekly 113 110 84 133

Note. All earnings figures are presented In 1980 dollars, to adjust for nflatIon

132

1: '

-1, "1 1
TABLE B.2

Earnings Ratios Under Alternative Sample Definitions, Black and White Males,

Ages 16-64

1950 1960 1970 1980

Annual earnings

All workers 51.9 52.7 61.4 66.2

Exci. students 51.1 51.3 59.0 64.9

Excl. students, UFW, 51.2 51.3 59.0 64.9

Excl. students, UFW, self-empl 56.2 54.3 61.9 67.6

Exci. students, UFW, self-empl.

(wages and salary only) 57.3 55.2 62.2 68.0

Excl. students, UFW, self-empl.,

armed forces 56.1 53.5 61.3 68.1

Weekly earnings

All workers 54.5 56.1 68.4 70.1

Excl. students 54.2 55.5 61.8 68.7

Excl. students, UFW 54.3 55.4 61.8 68.7

Excl. students, UFW, self-empl 59.4 58.4 64.6 71.3

Excl. students, UFW, self-empl.

(wages and salary only) 60.5 59.3 64.9 71.7

Excl. students, UFW, self-empl.,

armed forces 59.2 57.6 64.0 71.9

lUnpald family workers.

133

1 4; 2
TABLE B.2.1

Black-White Male Earnings patios, 1980

Excluding:

UFW,

UFW, students,

UFW, students, self-empl.,

UFW students self-empl. armed forces

Age Annual

16-19 83.2 76.5 76.1 74.4

20-24 76.5 72.9 73.5 73.8

25-29 76.4 75.5 76.3 76.4

30-34 72.7 72.0 73.4 73.4

35-39 65.5 65.2 68.6 68.4

40-44 63.8 63.6 66.2 66.0

45-49 62.3 61.9 64.7 64.7

50-54 63.2 63.0 65 5 65.6

55-59 61.3 61.3 63.7 63.6

60-64 61.7 61.8 66.2 66.2

Total 66.1 64.9 68.0 68.4

Weekly

16-19 96.2 86.1 85.5 85.3

20-24 80.9 78.5 79.1 80.4

25.29 80.7 79.9 80.8 81.3

30-34 76.5 75.8 77 2 77.3

35-39 68.7 68.3 71.7 71.5

40-44 66.8 66.6 69.1 69.0

45-49 65.1 64.8 67.5 67.5

50-54 66.1 65.8 66.4 68 5

55-59 63.2 63.2 65.2 65.2

60-64 62.5 62.6 66.4 66.5

Total 70.1 68.7 71.7 72.3

134
TABLE B.2.2.

Black-White Male Earnings Ratios, 1970

Excluding:

UFW,

UFW, students,

UFW, students, sell-empl.,

UFW students self-empl. armed forces

Age Annual

16-19 96.3 79.0 80.1 78.0

20-24 86.1 79.3 80.3 77.8

25-29 71.1 69.9 70.9 70.5

30-34 65.0 64.8 66.7 66.2

35-39 59.6 59.4 61.8 61.3

40-44 56.5 56.4 59.7 59.5

45-49 55.4 55.4 58.3 58.4

50-54 55.4 55.3 58.1 58.3

55-59 54.8 54.6 58.5 58.5

60-64 54.9 54.9 57.9 57.9

Total 61.3 59.6 52.2 61.6

Weekly

16-19 102.3 86.9 87.9 84.6

20-24 84.7 82.2 83.1 80.2

25-29 72.9 72.3 73.3 72.9

30-34 67.3 67.1 69.1 68.6

35-39 62.0 61.7 64.2 63.8

40-44 58.9 58.8 62.1 62.0

45-49 57.7 57.6 60.5 60.6

50-54 57.5 57.4 60.1 60.2

55-59 56.6 56.5 60.3 60.3

60-64 56.1 56.1 58.9 58.9

Total 63.4 61.8 64.9 64.9

135
TABLE B.2.3.

Black-White Male Earnings Ratios, 1960

Excluding:

UFW,

UFW, students,

liFW, students, self-empl.,

UFW students self-empl. armed forces

Age Annual

16-19 78.6 69.0 69.9 66.3

20-24 65.7 61.9 63.1 60.2

25-29 61.1 60.0 61.6 60.6

30-34 54.8 54.4 56.9 56.4

35-39 53.2 53.2 56.5 56.3

40-44 50.2 50.2 54.1 54.4

45-49 48.8 48.8 53.0 53.0

50-54 47.2 47.2 51.8 51.8

55-59 48.1 48.1 51.6 51.6

60-64 45.8 45.8 50.3 50.3

Total 52.7 51.3 55.2 54.4

136

145
TABLE B.2.3. (Cont'd.)

Black-White Male Earnings Ratios, 1960

Excluding:

Age

UFW

UFW,

students

UFW,

students,

self-empi.

Weekly

UFW,

students,

self-empl.,

armed forces

16-19 79.8 71.4 72.4 65.5

20-24 68.1 65.9 68.2 65.0

25-29 65.1 64.6 66.2 65.3

30-34 59.2 58.9 61.4 61.0

35-39 57.4 57.4 60.7 60.6

40-44 59.1 54.1 58.1 57.9

45-49 52.4 52.4 56.6 55.6

50-54 51.0 51.0 55.7 55.6

55-59 51.8 51.8 55.3 55.4

60 -64 49.6 49.6 54.0 54.0

Total 56.2 55.5 59.3 58.6

Note School enrollment not asked of individuals ages 35+ in 1960

137

146
TABLE B.2.4.

Black-White Male Earnings Ratios, 1950

Excluding:

Age

UFW

UFW,

UFW, students,

students self-empl.

Annual

UFW,

students,

self-empl.,

armed forces

16-19 , 83.2 74.2 73.7 71.6

20-24 70.5 67.3 69.8 68.6 25-29 61.4 60.5 64.1 64.2 30-34 54.3 54.3 59.9 60.0 35-29 52.5 52.9 58.0 58.0 40-44 49.3 49.3 55.6 55.5 45-49 47.2 47.2 53.9 53.9

50-54 45.5 45.5 53.1 52.9 55-59 46.5 45.5 51.6 51.6

60-64 45.7 49.7 54.2 54.1

Total 52.5 51.4 57.4 57.3

Weekly

16-19 71.8 68.1 67.7 63.7

20-24 69.3 68.9 71.4 70.0

25-29 65.2 64.7 68.7 68.9 30-34 58.1 58.1 64.0 64.1 35-39 56.3 56.3 62.0 62.0 40-44 52.4 52.4 59.0 58.8

45-49 49.6 49.6 56.3 56.4 50-54 47.9 47.9 55.6 55.5 55-59 49.1 49.1 54.8 54.0 50-64 48.7 48.7 57.1 57.0

Total 54.8 54.4 60.6 60.4

Note School enrollment not asked of individuaos ages 30+ in 1950

138
Appendix C

Regression Analysis: Methodology and Estimates

This appendix first describes the statistical methods

used to estimate the sources of the black-white gap in

earnings and presents alternative estimates of the

residual difference in black-white earnings. Next, it

presents the regression coefficients upon which table

6.1 in chapter 6 is based.

Frameworks for Analyzing Earnings

Differences

Regression analysis is frequently used to estimate

racial differences in earnings. The basic idea is to

examine how much of the earnings gap remains after

adjusting for age, education, and other important

determinants of earnings. One method for answering,

this question is to combine both blacks and whites into

a single regression and to include a variable to measure

the individual's race:

(1) in Y, = Xfi + Z,d + e,

where In Y, reflects the natural log earnings of

individual i: Xis a matrix of socioeconomic characteristics; b is a conformable vector of coefficients; Z is a

dummy variable that equals unity if an individual is a

member of a particular race and is zero otherwise, and

d is its coefficient; e, is a random error term with

expected value zero. The coefficient d shifts the

intercept of regression equation (/) and reflects residual

group differences in earnings for individuals holding

measured characteristics (X) constant

The functional form of (/) imposes the restriction

that the coefficients (b)the implicit returns on worker

characteristics such as education, etc. are the same

across race or gender gaups. As such, estimated group

differences in earning, are assumed to be independent

of the characteristics. X.

It is likely, however, that there are systematic

difference:, across groups in the returns on characteristics. A more general framework for analyzing earnings

differences, developed by Blinder (1973) and Oaxaca

(1973), is to "decompose" the gross differential into

portions attributable to differences in group characteristics (X) and to differences in coefficients (b). This

requires estimating two different regressions one for

blacks and one for whites. Thus, at sample means the

following relationships hold:

(2) (i) In Y = Xb.

(2) (ii) In Y,, =

The group difference in earnings can be written:

(3) In Y 1, In Y = Xb.

Adding and subtracting X..bi, to (31 yields:

,(4) In Yb Y = X)bb+ (bb--b)X

Equation (4) decomposes the difference in mean

earnings between blacks and whites into a term

reflecting the difference in characteristics (weighted by

black coefficients) plus a term measuring the difference

in factor payments (weighted 1- the white characteristics). The second term reflects the change in earnings

for whites if they received the same return on characteristics as blacks. One minus this term is often referred to

as the "unexplained" residual difference in earnings

because it measures what the black-white earnings gap

would be if blacks and whites had the same characteristics but received different monetary returns on those

characteristics. This residual reflects a variety of

factors, including, for example, discrimination and

racial differences in the "qu "lity" of characteristics,

such as schooling. Although the decomposition in (4)

is not unique the alternative method is presented

139
in table C.2 - it is the most frequently implemented

(table C.1).

TABLE C.1

Effects of Differences in Characteristics on the Wage Gap

Increase in

Black-white earnings ratio: eamings ratio Percent of gap

adjusting for due to differences

Unadjusted Adjusted characteristicsb in characteristicsb

1940

25-34 48.7 70.0 43.7 41.5

35-44 44.9 60.6 05.0 28.5

45-54 42.7 58.4 36.8 27.4

55-64 42.6 57.7 35.4 26.3

1950

25-34 64.9 79.2 22.0 40.7

35-44 59.3 74.5 25.6 37.3

45-54 56.3 67.7 20.2 26.1

55-64 54.2 69.0 27.3 32.3

1980

25-34 62.3 75.1 20.5 34.0

35-44 58.4 72.7 24.5 34.4

45-54 55.7 71.1 27.6 34.8

55-64 53.2 68.3 28.4 32.3

1970

25-34 70.3 81.5 15.9 37.7

35-44 62.8 74.9 19.3 32.5

45-54 59.5 73.9 24.2 35.6

55-64 58.9 74.4 26.3 37.7

1980

25-34 78.8 87.4 10.9 40.6

35-44 70.5 80.9 14.8 35.3

45-54 67.5 77.9 15.4 32.0

55-64 65.0 75.7 16.5 30.6

'Assumes black males have the average charactenstcs of white workers These charactenstcs cons, of years of schooling completed. years of potential work since school,

region of residence. industry of employment. and marital status

bThis is the percentage increase in the earnings ratio when white charactenstics are :satgned

c(Column #2 -Column #1)4100 - Column #1) X 100

140
TABLE C.k

Effects of Differences in Characteristics on the Wage Gap

Increase in

Black-white earnings ratio: earnings ratio Percent of gap

adjusting for due to differences

Unadjusted Adjusted' characteristic Sb in characteristicsc

1940

25-34 48.7 69.5 42.7 40.5

35-44 44.9 66.7 48.6 39.6

45-54 42.7 63.9 49.6 37.0

55-64 42.6 65.4 53.5 39.7

1950

25-34 64.9 78.9 21.6 39.9

35-44 59.3 75.6 27.5 40.0

45-54 56.3 74.7 32.7 42.1

55-64 54.2 74.8 38.0 45.0

1960

25-34 62.3 77.0 23.6 39.0

35-44 58.4 77.5 32.7 45.9

45-54 55.7 78.3 40.6 51.0

55-64 53.2 74.3 39.7 45.1

1970

25-34 70.3 81.0 15.2 36.0

35-44 62.8 78.8 25.5 43.0

45-54 59.5 79.3 33.3 48.9

55-64 58.9 80.3 36.3 52.1

1980

25-34 78.8 87.1 10.5 39.2

35-44 70.5 82.9 17.6 42.0

45-54 67.5 82.8 22.7 47.1

55-64 65.0 83.2 28.0 52.0

Assumes black males have the average characteristics of white workers These characteristics consist of years of schooling completed, years of potential work since school

region of residence. industry of employment. and marital status

bilks is the percentage increase in the earnings ratio when Mute cteracterlstits are assigned

epolumn #2 -Column #11/000 - Column #1) X 100

141
TABLE C.3

Estimated Effects of Worker Characteristics on Weekly Earnings by Race'

Age Greup 25-34

1940 1950 1960 1970 1980

Years of schooling2

0-12 years

Black 4.2 2.9 4.1 5.6 7.0

White 8.3 5.9 8.0 7.6 9.3

13+ years

Black 7.7 3.8 5.2 7.3 7.1

Whit^ 9.9 4.8 6.9 7.8 6.9

Years of work experience3

Black 1.7 0.8 1.5 1.7 2.5

White 3.2 2.3 3.0 2.9 3.5

Region (reference = Northeast)4

North Central

Black 2.3 5.4 6.3 4.9 14.3

White 6.5 2.0 2.6 0.3 5.7

West

Black 0.6 9.1 0.9 4.0 5.2

White 1.7 7.4 5.8 0.8 4.9

South.

Black -38.9 -29.0 -31.3 -25.0 5.2

Whit( -19.0 7.2 -10.6 -11.1 1.7

142
TABLE C.3 (Cont'd.)

Estimated Effects of Worker Characteristics on Weekly Earnings by Race'

Age Group 25-34 (Cont'd.)

1940 1950 1960 1970 1980

Industrial sector (reference = private nonagriculture)5

Agriculture

Black -68.4 -66.5 -63.5 -53.5 -42.6

White -74.2 -68.2 -59.9 -39.0 -31.2

Government

Black 7.9 6.6 6.5 1.4 3.4

White 8.2 7.3 -14.5 -10.8 -14.6

Other industry

Black -19.3 -30.5 -17.6 -14.6 -30.2

White -51.8 -14.0 -33.3 -30.2 -35.9

Marital status (reference = nonmarried)6

Black 8.9 12.1 16.8 14.0 15.5

White 17.9 17.7 20.7 18.7 18.2

Intercept

Black 1.44 3.38 3.60 3.96 4.30

White 1.73 3.04 3.21 3.76 4.08

'See notes at end of tab'e

143
TABLE C.3 (Cont'd.)

Estimated Effects of Worker Characteristics on Weekly Earnings by Race'

Age Group 35-44

1940 1950 1960 1970 1980

Years of schooling2

0-12 years

Black . 2.0 2.5 2.5 3.2 5.2

White 8.2 4.9 6.1 6.0 7.2

13+ year.

Black 5.1 2.2 4.6 7.4 6.8

White 15.1 8.3 7.9 9.5 8.7

Years of work experience3

Black 0.1 0.0 0.1 0.3 0.4

White 1.8 1.0 0.7 0.9 1.2

Region (reference = Northeast)4

North Central

Black 1.6 8.9 7.4 4.3 16.1

White 7.6 0.2 19.9 0.6 3.6

West

Black -15.6 10.8 3.3 1.4 4.4

White 3.1 5.4 4.1 0.9 4.1

South

Black -39.2 -29.8 -32.1 -25.6 - 9.6

White -20.3 -11.2 -10.1 -10.3 4.9

144

.".t 5 3
TABLE C.3 (Cont'd.)

Estimated Effects of Worker Characteristics on Weekly Earnings by Race'

Age Group 35-44 (Cont'd.)

1940

Industrial sector (reference = private nonagriculture)5

Agriculture

Black -75.7

White -81.6

Government

Black 9.2

White -10.7

Other industry

Black -32.1

White -68.4

Marital status (reference = nonmarried)6

Black 10.8

White 23.8

Weir- t

Black

White

'See notes at end of table

1950 1960 1970 1980

-58.1 -32.9 -56.0 -37.7

-65.4 -66.9 -47.6 -38.3

0.6 7.5 3.9 4.8

-15.2 -16.4 -14.2 -19.3

13.8 -10.4 9.3 -14.5

-11.4 -17.5 -23.7 -32.0

11.5 14.7 16.0 17.3

22.0 24.8 23.6 20.1

0.92 3.61 4.10 4.41 4.86

1.52 3.33 3.75 4.17 4.67

145

144
TABLE C.3 (Cont'd.)

Estimated Effects of Worker Characteristics on Weekly Earnings by Race,

Age Group 45-54

1940 1950 - 1960 1970 1980

Years of schooling2

0-12 years

Black 1.3 1.0 1.4 2.2 2.4 White 6.3 4.5 5.6 5.4 5.2

13+ years

Black 5.9 1.4 4.5 7.3 6.8 White 15.8 8.1 8.8 9.7 9.2

Years of work experience3

Black 0.4 0.5 0.4 0.4 0.2 White 0.1 0 3 0.1 0.1 0.2

Region (reference = Northeast

North Central

Black 2.2 5.3 10.8 5.6 15.4 White 7.2 3.6 0.5 0. i 4.8

West

Black 2.4 2.1 4.0 1.0 2.9 White 5.2 0.3 1.9 2.0 4.9

South

Black -38.3 -29.9 -34.8 -28.9 -14.3 White -19.8 -14.5 -13.9 9.8 4.7

146

.1 5 5
TABLE C.3 (Cont'd.)

Estimated Effects of Worker Characteristics on Weekly Earnings by Race'

Age Group 45-54 (Cont'd.)

1940 1950 1960 1970 1980

Industrial sector (reference = private nonagriculture)5

Agriculture

Black -74.4 -55.8 -84.3 -65.6 -58.7

White -90.6 -79.3 -75.1 -50.6 -37.2

Government

Black 11.0 4.7 7.4 3.1 3.2

White -11.0 -14.0 -18.2 -13.2 -18.1

Other industry

Black -31.5 20.6 -10.6 -27.9 -23.0

White -72.7 -12.6 -20.2 3.8 9.8

Marital status (reference = nonmarried)6

Black 12.6 16.2 14.8 20.7 20.1

White 24.8 24.2 26.8 23.8 21.9

Intercept

Black 0.73 3.87 4.29 4.67 5.19

White 0.83 3.58 3.96 4.47 5.12

'See notes at end of table

147

1 tri6
TABLE C.3 (Cont'd.)

Estimated Effects of Worker Characteristics on Weekly Earnings by Race'

Age Group 55-64

1940 1950 1960 1970 1980

Years of schooling2

0-12 years

Black 0.5 0.4 0.3 0.7 0.7 White 6.0 2.4 4.7 4.6 3.8

13+ years

Black 4.6 4.3 3.7 5.7 4.7

White 14.0 5.2 8.1 9.8 8.0

Years of work experience3

Black 1.3 1.5 0.9 - 1.2 0.8 White 0.3 1.3 0.2 0.3 1.1

Region (reference = Northeast)"

North Central

Black 1.8 13.0 8.6 7.2 15.8 White 6.6 3.5 1.0 0.2 5.4

West

Black -19.6 19.1 5.5 0.7 5.0 White 1.8 0.3 0.1 1.6 6.8

South

Black , White

-39.9

-15.8

-22.5

-20.0

-39.6

-15.0

-33.8

-12.0

-17.5

3.6

148

.15 7
TABLE C.3 (Cont'd.)

Estimated Effects of Worker Characteristics on Weekly Earnings by Race'

Age Group 55-64 (Cont'd.)

1940

Industrial sector (reference = private nonagriculture)5

Agriculture

1950 1960 1970 1980

Black -70.5 -80.8 -92.3 -53.0 -49.5

White -91.1 -85.9 -78.6 -59.3 -49.0

Government

Black 6.3 3.7 Lt.2 3.5 7.2

White 8.2 --15.7 -18.0 -13.8 -15.5

Other industry

Black -28.8 - -17.9 -36.7 14.8

White -73.8 11.3 -33.4 -25.3 6.7

Marital status (reference = nonmarried)6

Black 11.1 12.5 16.9 18.4 21.5

White 23.9 21.3 24.8 25.6 21.8

Intercept

Black 0.19 4.36 4.53 5.18 5.69

White 0.67 4.48 4 21 4.62 5.75

Each estimated coefficient, or return. is derived from a multiple regression of weekly earnings on the five variables indicated in the table Separate estimates aremade by age

group, race, and census year They are interpreted as percentage changes in earnings due to a change in the characteristic

2The return on schooling is estimated separately for years 0-12 and for years 13 and over It measures the percentage increase in earnings associated witha year of schooling

3This is the return on one year of potential work experience.

Each estimate indicates the (percentage) earnings difference associated with living in the particular region in contrast to living in the Northeast region

6Eanh estimate indicates the (percentage) earnings difference associated with working in the particular sector in contrast to working in a private nonagricultui al industry A

residual category of "other industries" was also included but is not reported to save space

6 Each estimate indicates how much more a married man earns than an unmarned man (in percentage terms)

149
Appendix D

Black-White Earnings Ratios

TABLE D.1

Black-White Earn:7:p Ratios by Region and Education

Annual earnings Weekly earnings Hourly earnings

Ages 25-34 1940 1960 1980 1940 1960 1980 1940 1960 1980

Non-South

8-11 years 69.6 75.7 80.0 70.1 80.8 87.3 70.1 86.7 94.6

High school 67.1 71.5 80.7 70.6 '75.6 85.5 70.6 81.6 91.0

College ns 72.9 88.3 ns 73.3 91.4 ns 77.9 96.5

All levels 63.2 69.5 79.7 66.9 74.0 84.9 66.9 79.2 91.4

South

8-11 years 58.5 60.5 77.3 59.8 64.4 80.4 59.8 68.4 86.8

High school 51.1 59.7 76.1 53.1 63.2 79.5 53.1 65.6 86.4

College 49.8 62.2 81.0 55.7 68 4 83.5 55.7* 73.0 90.2

All levels 45.2 53.7 73.3 42.4 57.6 77.1 47.4 60.7 83.8

All regions

8-11 years 61.8 67.4 77.4 62.3 71.6 -81.6 62.3 75.8 87.1

High school 59.8 66.1 76.9 61.9 69.8 80.5 61.9 74.6 85.9

College 55.9 66.7 84.6 61.2 69.9 87.0 61.2 73.9 92.2

All levels 46.6 59.6 75.3 48.9 63.7 79.4 48.9 67.2 85.2

150
Ages 45-54

Non-South

8-11 years 64.4 73.7 84.8 62.2 76 8 8/ ,- 6',' 2 i2.2 93.1

High school 48.8 65.3 81.1 51.3' 6,:' 4 84 : 51 3* 73.6 89.3

College ns 47.8* 71.5 ns 50 4* 73.9 ns 55 4* 79.6

All levels 49.4 63.6 72.2 51.9 68.1 75.1 51.9 72.2 80.1

South

8-11 years 45.5 58.6 69.2 48.0 61.0 72.3 48.0 65.0 78.7

High school ns 54.0 69.9 ns 55.1 72.1 ns 60.1 76.5

College ns 54.2 62.7 ns 58.6 66.8 ns 61.9 71.3

All levels 34.4 47.3 60.6 36.5 50.2 63.4 36.5 54.2 68.8

All regions

8-11 years 55.2 66.3 77.3 56.4 69.1 79.1 56.4 72.3 84.6

High school 39.8 60.8 75.8 42.4 65.7 78.5 42.4 67.8 82.9

College 24.2* 49.4 66.9 26.4* 52.8 78.5 26.4* 55.9 74.8

All levels 38.2 52.5 65.4 40.3 56.2 68.2 40.5 57.6 68.7

'Based on less than 100 observations, but more than 50 observations

ns .g, not statistically reltable

Source Census of Population, 1940.1980, Public Use Sample

151

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