Gender differences in the volatility of work hours and labor demand

Abstract

This paper examines the role of heterogeneity in a real business cycle model, which traditionally has not fully captured the relative volatility of hours to output. Men and women have different cyclical volatilities in hours worked, which is robust to different filtering methods. This empirical regularity is used to motivate a standard RBC model augmented to allow for two different agents following Jaimovich et al. (2013). These two agents have identical utility functions, but face different elasticities of labor demand due to their different complementarities with capital. These estimated elasticities find that women are more complementary to capital. The calibrated model generates the cyclical volatility of work hours by gender and for the total hours worked that matches the U.S. data better than the traditional representative agent model. I then explore other extensions to this model including investigating the stability of the estimated labor demand elasticities and allowing for various Frisch elasticities of labor supply. This paper demonstrates that allowing for even broad levels of heterogeneity in a simple framework can increase the model’s tractability with the data. Since gender is important to explain U.S. business cycle dynamics, we need to carefully consider heterogeneity when analyzing counter-cyclical economic policy, as it may not have symmetric effects across assorted groups.

Age- and Gender-specific Output-employment Relationship across Economic Sectors

“…Some authors also state that males and females vary in occupations (Blau et al, 2013;Cortes and Pan, 2017;Petrongolo and Ronchi, 2020) and levels of educational attainment (He et al, 2011;Pekkarinen, 2012;Bertocchi and Bozzano, 2020;Baten et al, 2021;Evans et al, 2021) which also could be a reason for the higher volatility of female employment. Additionally, Guisinger (2020) states that female labour is more complementary to capital than male which influences the higher elasticity of female employment. This can be explained by shifting requirements from physical toward intellectual work and increased demand for office work, where females usually have a comparative advantage due to their higher educational attainment (Rendall, 2017).…”

Multivariate decompositions and seasonal gender employment

“…Recent studies relating to the US indicate that cyclical movements have gender-specific employment consequences, with both Hoynes, Miller and Schaller (2012) and Guisinger (2020) finding cyclical movements to be more marked for males than females. However, neither considers seasonal aspects of employment and, although Guisinger (2020) uses a correlated UC model as one of three decomposition techniques, the methods she applies are univariate.…”