Joseph Altonji Publications

This paper examines the gender gap in log earnings among full-time, college-educated workers born between 1931 and 1984. Using data from the National Survey of College Graduates and other sources, we decompose the gender earnings gap across birth cohorts into three components: (i) gender differences in the relative returns to undergraduate and graduate fields, (ii) gender-specific trends in undergraduate field, graduate degree attainment, and graduate field, and (iii) a cohort-specific “residual component” that shifts the gender gap uniformly across all college graduates. We have three main findings. First, when holding the relative returns to fields constant, changes in fields of study contribute 0.128 to the decline in the gender gap. However, this decline is partially offset by cohort trends in the relative returns to specific fields that favored men over women, reducing the contribution of field-of-study changes to the decline to 0.055. Second, gender differences in the relative returns to undergraduate and graduate fields of study contribute to the earnings gap, but they play a limited role in explaining its decline over time. Third, much of the convergence in earnings between the 1931 and 1950 cohorts is due to a declining “residual component.” The residual component remains stable for cohorts born between 1951 and the late 1970s, after which it resumes its decline.

For birth cohorts 1935–44, 1945–62, and 1964–74, we estimate the contribution of education; permanent heterogeneity in wage rates, employment, and hours; labor market shocks; spouse characteristics and shocks; nonlabor income shocks; and marital histories to the age profiles of the variance of family income per adult equivalent. Education and employment heterogeneity are key sources of the rise in variance with age and across cohorts. Wage heterogeneity is important at all ages. Own characteristics and shocks matter more for men than women, while spouse characteristics and shocks matter more for women. Gender differences have declined across cohorts.

We estimate causal effects of 121 graduate degrees on log earnings. The returns average 0.159 but vary widely across fields, with a standard deviation of 0.176. Experience profiles of the returns also vary and are particularly steep for medicine. Internal rates of return, which account for program length, tuition, and in-school earnings, are sizable but vary less across fields. Earnings effects are higher for women, lower for part time students, and depend on undergraduate major. Students from lower-paying undergraduate majors benefit more from an MBA or JD. School specific returns are higher for higher ranked JD and MBA programs.

This chapter uses a college-by-graduate degree fixed effects estimator to evaluate the returns to 19 different graduate degrees for men and women. We find substantial variation across degrees, and evidence that OLS overestimates the returns to degrees with the highest average earnings and underestimates the returns to degrees with the lowest average earnings. Second, we decompose the impacts on earnings into effects on wage rates and effects on hours. For most degrees, the earnings gains come from increased wage rates, though hours play an important role in some degrees, such as medicine, especially for women. Third, we estimate the net present value and internal rate of return for each degree, which account for the time and monetary costs of degrees. Finally, we provide descriptive evidence that satisfaction gains are large for some degrees with smaller economic returns, such as education and humanities degrees, especially for men.

This paper uses a college-by-graduate degree fixed effects estimator to evaluate the returns to 19 different graduate degrees for men and women. We find substantial variation across degrees, and evidence that OLS overestimates the returns to degrees with high average earnings and underestimates the returns to degrees with low average earnings. Second, we decompose the impacts on earnings into effects on wage rates and effects on hours. For most degrees, the earnings gains come from increased wage rates, though hours play an important role in some degrees, such as medicine, especially for women. Third, we estimate the net present value and internal rate of return for each degree, which account for the time and monetary costs of degrees. We show annual earnings and hours worked while enrolled in graduate school vary a lot by gender and degree. Finally, we provide descriptive evidence that gains in overall job satisfaction and satisfaction with contribution to society vary substantially across degrees.
 

We estimate the returns to a broad set of graduate degrees. To control for heterogeneity in preferences and ability, we use fixed effects for combinations of field-specific undergraduate and graduate degrees obtained by the last time we observe an individual. Basically, we compare earnings before the graduate degree to earnings after it. Using National Science Foundation data, we find large differences across graduate fields in earnings effects. The returns often depend on the undergraduate major. The contribution of occupational upgrading to the earnings gain varies across degrees. Finally, simple regression-based estimates of returns to graduate fields are often highly misleading.

The onset of the Covid-19 pandemic has led to a dramatic reduction in employment and hours worked in the US economy. The decline can be measured using conventional data sources such as the Current Population Survey and in the number of individuals filing for unemployment. However, given the unprecedented pace of the ongoing changes to labor market conditions, detailed, up-to-date, high frequency data on wages, employment, and hours of work is needed. Such data can provide insights into how firms and workers have been affected by the pandemic so far, and how those effects differ by type of firm and worker wage level. It can also be used to detail – in real time – the state of the labor market.