Research Database

Women are well represented in some academic fields but notably underrepresented in others, including many STEM fields. Motivated by studies that show collaboration is more attractive to women than men, we investigate whether female participation across academic fields is related to how collaborative those fields are. Using panel data for 30 academic fields from 1975 to 2014, we find that one additional author on the average paper published in a field is associated with an increase of 2.5 percentage points in the female share of PhD recipients. This estimate implies that about 30 percent of the observed rise in female share during our sample period can be attributed to increased collaboration.

We incorporate nominal wage contracts and government into a quantitative general equilibrium framework. Thus, our model includes three types of shocks: a fiscal shock, a monetary shock, and a technology shock. We show that it is possible in this type of environment to generate a low correlation between hours worked and the return to working, a moderately negative correlation between output and aggregate prices and a moderately positive correlation between the real wage rate and output. In sharp contrast with RBC models with indivisible labor, wage contracts magnify mainly the effect of monetary shocks on the volatility of hours worked. An attractive feature of the contracting model is that it avoids a trade-off that RBC models have to face in their predictive capacity when additional features are incorporated to them.

This article describes some facts about financial inequality in the United States that a good theory of inequality must be able to explain. These include the facts that labor earnings, income, and wealth are all unequally distributed among U.S. households, but the distributions are significantly different. Wealth is much more concentrated than the other two. Wealth is positively correlated with earnings and income, but not strongly. The movement of households up and down the economic scale is greater when measured by income than by earnings or wealth. Differences across the three variables remain when the data are disaggregated by age, employment status, educational level, and marital status of the heads of U.S. households. Each of these classifications also has significant differences across households. All the facts are based on data taken from the 1992 Survey of Consumer Finances and the 1984–85 and 1989–90 Panel Study of Income Dynamics.