have used potential work experience and three have used age as a proxy. They vary widely in their use of other controls.
Of the 27 studies, 18 report unambiguously higher schooling coefficients for females. Six report multiple estimates where the female coefficients are mostly
higher.
5
Two report mixed results that are evenly balanced.
6
Only one reports higher schooling coefficients for males, and this study had a relatively small sample.
7
In gen- eral the studies report only point estimates, and it is thus impossible to determine
whether the differences in the coefficients are significant. However, taking the studies together, the effect is undoubtedly significant, for under the null hypothesis that the
coefficients are the same; the probability of 24 out of 27 studies finding higher coef- ficients for either sex is less than 0.01 percent.
As to which levels of schooling are responsible for the effect, there is some evi- dence that the returns to partial and complete college are higher for females than for
males; for years of high school, the evidence points the other way; and for postgrad- uate studies, the evidence is mixed.
8
Given the institutional differences between the labor market in the United States and labor markets in other countries, one would not anticipate that a feature of the U.S. mar-
ket would necessarily be encountered elsewhere. However, two recent surveys suggest that the effect may not be confined to the United States. Trostel, Walker, and Woolley
2002 estimate the returns to schooling in 28, mostly European, countries with data derived from a common survey instrument and found that the female schooling coeffi-
cient was higher in 24. Psacharopoulos and Patrinos 2002 list 95 estimates of male and female schooling coefficients from 49 countries at different dates. Of these 63 are greater
for females, three are equal, and 23 are greater for males.
III. Possible Causes of the Effect
Candidates for an explanation of the male-female differential in the schooling coefficient include the following possibilities: an inverse relationship between
5. Angle and Wissman 1981, Gregory et al. 1989, Blau and Kahn 1997, and Brown and Corcoran 1997 use dummy variables for education and thus have different estimates for different levels. Gwartney
and Long 1978 and Carlson and Swartz 1988 have multiple estimates because they fit wage equations for nine and 12 ethnic categories, respectively. In each of these studies most of the estimates of the returns to
schooling are higher for females. 6. Kane and Rouse 1995 find higher returns to schooling for females using the NLS72 data but mostly
lower ones using NLSY data. Mincer and Polachek 1974 find that males have higher returns than married females but lower ones than single females.
7. Barron, Black, and Lowenstein 1993. 8. Larger returns to partial or complete college for females are implicit in the dummy variable coefficients
reported by Altonji 1993, Grogger and Eide 1995, Brown and Corcoran 1997, and Loury 1997. For postgraduate degrees, Daymont and Andrisani 1984, Gregory et al. 1989, and Brown and Corcoran
1997 report coefficients indicating higher returns for females, but Angle and Wissman 1981 report a lower one and Grogger and Eide 1995 find no difference. Brown and Corcoran 1997 and Gregory et al.
1989 find that males actually have higher returns to high school years of schooling. The conclusion that females benefit relatively greatly from later years of schooling is corroborated by the three studies that have
used years of schooling in quadratic form Oaxaca 1973, Gwartney and Long 1978, Carlson and Swartz 1988. All of them report positive coefficients for the quadratic terms, with the female coefficient generally
being larger than the male one.
The Journal of Human Resources 972
years of schooling and DTC; a male-female differential in the quality of educational attainment; occupational segregation of females into sectors where the returns to school-
ing are relatively high; biased estimates attributable to a failure to take account of sam- ple selection; and biased estimates attributable to a failure to take account of the
endogeneity of schooling or work experience. Doubtless this list is incomplete.
The present intention is to argue that, of these explanations, the first may be an important one. It is suggested that schooling may have two effects on earnings, at least
for females: a direct human capital effect, and an indirect effect via an attenuation of the adverse impact of DTC.
There are two reasons for hypothesizing that the impact of discrimination may not be uniform in the labor market and that, in particular, it may be inversely related to
the level of schooling. First, it is possible that the better educated an individual is, the more likely he or she is to have a degree or other formal qualification that would help
to standardize wage offers regardless of sex. Second, it is possible that the better edu- cated a woman is, the more likely she is to be capable of resisting discrimination.
Similar arguments may be made with respect to that component of the unexplained earnings gap attributable to tastes and circumstances. It is possible that the better edu-
cated a woman is, the more likely she is to be willing to seek employment outside the low-paying traditionally female occupations. At the same time, it is possible that the
better educated she is and the greater her potential earnings, the more capable she is of paying for childcare and other services that allow her to seek a wage offer that fully
values her characteristics. The impact of these factors may be inversely related to the level of schooling and failure to allow for them could impart an upward bias in the
estimated female schooling coefficient.
IV. Evidence from the National Longitudinal Survey of Youth 1979–
