This document summarizes several studies that investigate the black-white male earnings gap in the United States. It finds that differences in human capital, such as education and experience, explain a significant portion of the earnings gap but not all, suggesting labor market discrimination still exists. The gap narrowed between 2000 and 2010, with human capital explaining more of the difference and discrimination playing a smaller role over time.

1. Black/White Male
Earnings gap
BEN SCHROCK
MIKE SCHUENKE
EMILY GROSSKOPF
JAMES DUGGAN

2. Key Problem
 This study investigates the determinants of earnings
difference between black and white males?
 Do black males still face labor market discrimination
that limits their opportunities?
 Does the earnings gap between black and white males
reflect differences in human capital?
 The importance of this is to determine if we have
fairness and maximum efficiency in the economy.

3. Smith & Welch (1989)
 Shows how trends have effected the
economic situation of the black
community in America (1940-1980
Cohorts)
 Their study found that:
 Improved quantity and quality of education
 Migration from South to North
 Increase in labor force participation and affirmative
action

4. O’Neill (1990)
 O’Neill’s studies paralleled Richard Freeman’s (1981)
findings in that:
 In 1987, differences in background factors (Years of
school completed, AFQT scores) explained ¾ of the
earnings difference between black men and white men
under age 30
 Differences in work experience accounted for most of the
remaining gap
 Found that human capital is approximately the sole
source of earnings amongst the individual, NOT
discrimination

5. Corcoran & Duncan (1979)
 This article compares the differences in earnings
between Black and White sexes
 Education and some human capital factors has a strong
effect on black male earnings but cannot fully explain the
earnings gap
 Found that the wage advantages enjoyed by white men
cannot be explained solely by superior qualifications or
more attachment to the labor force
 Their results prove that there is discrimination in the
market

6. Bostic (1997)
 Minorities differ in levels of education, work
experience, etc…
 Growth for blacks are 67%/88% compared to whites
 Earnings growth in the short run for blacks is less than
whites
 These results are consistent with discrimination in the
market
 Evidence suggest that among potential homebuyers,
blacks are inherently riskier than comparable whites
due to differences in earnings variability

7. Semyonov & Lewin-Epstein (2009)
 Trends in racial earnings inequality observed in the
market as a whole mask considerable differences
between the private and public sectors of the economy
 Found that:
 Little to no racial disparity in the public sector
 Substantial amounts of discrimination remained in the
private sector even into 2000
 In contrast, the private sector is characterized by
racial disparities in earnings even after taking into
considerations racial variations in socio-
demographic attributes and in occupational
distributions

8. Model to be Tested
 Ln Wi = HCiß + Oi∂ + Biα + εi
 Where:
 Wi = Wage/ annual salary income
 HC = Vector of human capital
 O = Vector of occupation
 B = Vector of personal background

9. Variables
 Dependent:
 Wage
 Independent:
 Human Capital
 Years of education
 Experience (Age – Years of Edu – 6)
 Usual hours worked
 Occupation
 Background
 Race
 Marital status
 Age
 Region

10. Hypothesis: Human Capital
Education
 Ho: There is no correlation between earnings and
education
 Ha: There is a positive correlation between earnings
and education

11. Hypothesis: Human Capital
Experience
 Ho: There is no correlation between earnings and
experience
 Ha: There is a positive correlation between earnings
and experience

12. Hypothesis: Human Capital
Hours Worked
 Ho: There is no correlation between earnings and
hours worked
 Ha: There is a positive correlation between earnings
and hours worked

13. Hypothesis: Race
Race
 Ho: There is no correlation between earnings and
Race.
 Ha: There is positive correlation between earnings and
race.

14. Data sources
 Integrated Public Use Microdata Series (IPUMS)
 American Community Survey
 Years Analyzed: 2000, 2010
 Age analyzed: 18-65

15. Variable definitions and anticipated
signs

16. Mean values

17. OLS regressions

18. Oaxaca Decomposition
 w̄ W – w̄ B= (αW – αB) + (βW – βB)x̄ Bi + βWi(x̄ wi – x̄ Bi)
 w̄ W – w̄ B= (αW – αB) + (βW – βB)x̄ Wi + βBi(x̄ wi – x̄ Bi)
Discrimination Human Capital
and other
characteristics
Human Capital
and other
characteristics
Discrimination

20. Decomposing the raw wage
differential (2000)
 Ln w̄ W = 11.10 Ln w̄ B = 9.396
 Ln w̄ W – Ln w̄ B = 1.704
 1.704= (αW – αB) + (βW – βB)x̄ βi +.48
 1.704 = X + .48
 X = 1.224

21. Decomposing the raw wage
differential (2010)
 Ln w̄ W = 10.461 Ln w̄ B = 9.138
 Ln w̄ W – Ln w̄ B = 1.323
 1.323= (αW – αB) + (βW – βB)x̄ βi +.65
 1.323 = X + .65
 X = 0.673

22. Conclusions

23. Works Cited
 Altonji, J., & Blank, R. (2010). Race and gender in the labor market. In O. Ashenfelter &
D. Card (Eds.), Handbook of labor economics (Vol. 3, p. 3143–3259). Amsterdam:
North Holland.
 Burkhauser, R., & Larrimore, J. (2009). Using internal CPS data to reevaluate trends in
labor-earnings gaps. Monthly Labor review.
 Concoran, M., & Duncan, G. (1979). Work History, Labor Force Attachment, and
Earnings Differences between the Races and Sexes. The Journal of Human
Resources, 14(1), 3-20.
 Federal Reserve, Racial Differences in Short-Run Earnings Stability and Implications
for Credit Markets, Doc., at 6-10 (1997).
 Lewin-Epstein, N., & Semyonov, M. (2009). The declining racial earnings’ gap in United
States: Multi-level analysis of males’ earnings, 1960–2000. Social Science Research,
38(2), 296-311. Retrieved from
http://www.sciencedirect.com/science/article/pii/S0049089X08001105
 O'Neill, J. (1990). The Role of Human Capital in Earnings Differences Between Black
and White Men. The Journal of Economic Perspectives, 4(4), 43-44.
 Smith, J. P., & Welch, F. R. (1989). Black Economic Progress After Myrdal. Journal of
Economic Literature, 27(2), 519-564.
 Steven Ruggles, J. Trent Alexander, Katie Genadek, Ronald Goeken, Matthew B.
Schroeder, and Matthew Sobek. Integrated Public Use Microdata Series: Version 5.0
[Machine-readable database]. Minneapolis: University of Minnesota, 2010.