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.