Nonparametric Panel Estimation of Labor Supply

Abstract

In this article, we estimate structural labor supply with piecewise-linear budgets and nonseparable endogenous unobserved heterogeneity. We propose a two-stage method to address the endogeneity issue that comes from the correlation between the covariates and unobserved heterogeneity. In the first stage, Evdokimov’s nonparametric de-convolution method serves to identify the conditional distribution of unobserved heterogeneity from the quasi-reduced model that uses panel data. In the second stage, the conditional distribution is plugged into the original structural model to estimate labor supply. We apply this methodology to estimate the labor supply of U.S. married men in 2004 and 2005. Our empirical work demonstrates that ignoring the correlation between the covariates and unobserved heterogeneity will bias the estimates of wage elasticities upward. The labor elasticity estimated from a fixed effects model is less than half of that obtained from a random effects model.

KEY WORDS:

• Fixed effects
• Nonparametric estimation
• Nonseparability
• Piecewise-linear budgets
• Structural labor supply
• Unobserved heterogeneity.

ACKNOWLEDGMENTS

The authors thank an anonymous referee, an associate editor, and a co-editor for their insightful comments and suggestions that helped greatly improve this article. This work was supported by Shanghai Pujiang program (Grant No. 12PJC079) and National Nature Science Foundation of China (Key Project, Grant No. 71133001).