New trends in gender pay gaps

Is the gender pay gap as large as many studies show?

Strittmatter and Wunsch, in this paper, use a large data set of 1.7 million employees in Switzerland,  to investigate whether the methodological improvements made possible by big data could affect estimates of the unexplained gender pay gap. They argue that standard models are characterized by the following three methodological restrictions:

1. Functional forms for the wage equation are relatively inflexible. For example, the returns to education are often assumed to be the same across occupations, age and experience, which contradicts both theory and empirical evidence.
2. There is lack of observationally comparable men for every woman.
3. There is no heterogeneity in gender pay gaps to variable-specific differences in coefficients.

We find that these three factors matter greatly. Blinder-Oaxaca estimates of the unexplained gender pay gap decline by up to 39% when we enforce comparability between men and women and use a more flexible specification of the wage equation. Semi-parametric matching yields estimates that when compared with the Blinder-Oaxaca estimates, are up to 50% smaller and also less sensitive to the way wage determinants are included.

The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?
Authors: Anthony Strittmatter, Conny Wunsch
From: Institut Polytechnique Paris, University of Basel

How both the marriage and labor markets determine the gender wage gap

This is an interesting paper which studies how inequality in economic outcomes results from agents interacting in both the marriage and the labor market. The authors, Reynoso et al., use data from the German Socioeconomic Panel for the period from 1984 to 2018 and data from the German Employment Survey of 2012. They find:

• Today’s Germany is characterized by stronger complementarity in spouses’ home hours and increased relative productivity of men. These changes in home production technology account for around 70% of the observed decline in the gender wage gap and for the entire drop in within-household inequality.
• In contrast, changes in labor market technology—which we interpret as skill-biased technical change—had very different effects: they fueled gender and household inequality across the board, preventing gender gaps from falling even further.

Finally, we find that changes in both marriage market sorting and labor market sorting—which increased by 10% and 8%, respectively—significantly affected these inequality shifts. If sorting patterns had stayed constant at their 1990 levels, gender inequalities would be wider today and between-household inequality narrower. Intuitively, stronger marriage market sorting over time generated more gender balanced labor market outcomes—in hours, sorting, and pay. In turn, the increase in labor sorting over the past decades also significantly narrowed gender disparities, since it was predominantly driven by women’s improved labor sorting; this helped them catch up with men’s pay.

Marriage Market and Labor Market Sorting
Authors: Ana Reynoso, Paula Calvo, Ilse Lindenlaub
From: University of Michigan, Yale University