Over the past five decades, the labor force participation rate of American men has declined significantly---from 80% in the 1970s to just around 68% today---and similar trends are observed across the developed world. During the same period, the fastest-growing occupations have been those traditionally considered "feminine," such as nursing. Are these two trends connected? Do masculinity norms discourage men from entering the labor force by deterring them from pursuing jobs perceived as feminine? We provide evidence at the macro, micro, and experimental level. At the macro level, we document that male employment participation declined more following sectoral reallocation in more gender-traditional labor markets. At the micro level, we show that gender-progressive men's employment recovers somewhat faster after layoff than that of gender-traditional men, partly through switching into female-dominated industries and occupations. Finally, we are piloting a survey experiment designed to measure men's willingness to pay to avoid occupations perceived as feminine and to assess whether correcting misperceptions about masculinity norms changes this willingness to pay. Understanding the role of masculinity norms in shaping men's labor market decisions is crucial for addressing the ongoing decline in male labor force participation.
This study analyzes whether and how much workers value the gender composition of their workplace and the aggregate consequences of these valuations for occupational segregation, tipping, and welfare. To measure these valuations, I conduct a survey with an embedded hypothetical job choice experiment. From my survey, I estimate that women's valuations for gender composition are homophilic but concave and men value gender diversity. There is significant individual heterogeneity in these valuations: older workers are more likely to value gender homophily, suggesting that as men and women's labor market outcomes have converged over time the value of gender homophily has declined. I then use the survey estimates of gender composition valuations in a structural model of occupation choice to assess their consequences for gender sorting and welfare. I find that if workers did not value gender composition, women's employment in male-dominated jobs would increase substantially, but the estimated gender composition valuations are not large enough to create tipping points in segregation. Gender composition valuations also create a sorting externality: a welfare-maximizing social planner would reallocate workers across occupations to substantially decrease gender segregation.
We show better-managed firms are more dynamic in plant acquisitions, disposals, openings and closings in U.S. Census and international data. Better-managed firms also birth better-managed plants, and improve the performance of the plants they acquire. To explain these findings we build a model with two key elements. First, management is a combination of firm-level management ability (e.g. CEO quality), which can be transferred to all plants, and plant-level management practices, which can be changed through intangible investment (e.g. consulting or training). Second, management both raises productivity and also reduces the operational costs of dynamism: buying, selling, opening and closing plants. We structurally estimate the model on Census microdata, fitting our key dynamic moments, and then use it to establish three additional results. First, mergers and acquisitions raise economy-wide management and productivity by reallocating plants to firms with higher management ability. Banning M&A would depress GDP and management by about 15%. Second, greater product market competition improves both management and productivity by reallocating away from badly managed plants. Finally, management practices account for about a fifth of the cross-country productivity differences with the US.
In this paper, I study the role of gender wage gaps in spurring labor-replacing technological innovation. Using data on the universe of U.S. patents matched with occupational task content, I show that occupations with a higher male share have overlapped more with new patents in the past century, even within groups of closely related occupations. I then present preliminary evidence that the relationship between gender composition and innovation is causal using state-level variation in equal pay policies. In future work, I plan to study the aggregate implications of these results for the dynamics of gender gaps in a model of directed technical change.
We investigate the importance of job-to-job (JJ) transitions for cyclical wage dynamics. By exploiting cross-state variation, we find that wage growth is tightly linked to variation in the JJ transition probability, and conditional on this, the job finding probability of the unemployed has no explanatory power. We investigate the robustness of our results to several caveats and find the result to hold. Finally, we discuss the implications of our findings for competing theories of wage dynamics.