UCLA

This dissertation contributes towards our understanding of Labor Economics and Applied Econometrics. It consists of three chapters. The first two chapters shed light on the determinants of female labor supply behavior by connecting theory to household-level data. The third chapter studies the nonlinear generalized method of moments (GMM) in dynamic panels and its application to value-added models of learning.

In Chapter 1, I propose that the rising sex ratio (number of males per female) imbalance has been an important factor in the recent feminization of rural-to-urban migration in China. To establish this connection, I first develop a three-player noncooperative household model in which both the parents and the daughter contribute time or money to improve the well-being of sons. The local sex ratio can affect the players' choices via two channels: either by influencing the preference towards sons, or by imposing negative impact on sons' welfare due to intensified marriage market competition. My model predicts that daughters are more likely to participate in migratory work when the local sex ratio is higher. Drawing on data from Rural-Urban Migration in China Survey, I then test the hypothesis by comparing unmarried rural women with brothers and those without brothers when conditioning on family size. My identification strategy exploits the exogenous variation in the number of brothers a rural woman has that comes from the randomness in parental sibling structure. I show that an increase in the local sex ratio significantly raises the probability of becoming a migrant worker for unmarried rural women who have brothers, while no significant effect is observed among those without brothers. The positive link is stronger for rural women who have a larger number of brothers or whose brothers are relatively younger. I also discover that around 40% of the increase in rural female labor migration rate from 1990 to 2000 could be explained by the changes in the sex ratio. I further find evidence in favor of the marriage market pressure mechanism.

Chapter 2 (joint work with Zhongda Li) examines the intergenerational determinants of women's labor force participation decision. Existing studies have established a positive correlation between a married woman's work behavior and her mother-in-law's. Such linkage is attributable to the profound influence of maternal employment on son's gender role preferences or household productivity. In this chapter we investigate the relative importance of the two potential mechanisms using the Chinese survey data. We show that a substantive part of the intergenerational correlation is left unexplained even if we control for the husband's gender role attitudes. Instead, we find that the husband's household productivity is more crucial in the wife's work decision, suggesting the dominance of the endowment channel over the preference channel.

Chapter 3 develops a novel framework for constructing nonlinear moment conditions in dynamic panel data models. I demonstrate that the nonlinear GMM estimator considerably mitigates the classical weak identification problem arising from two data generating processes: (i) the autoregressive parameter is close to the unit circle; (ii) the ratio of variances of individual heterogeneity and idiosyncratic errors diverges to infinity. I further derive analytical expressions for the bias term of the linear and nonlinear GMM estimators, and show that the use of nonlinear moments results in smaller finite sample bias. In simulation studies, the nonlinear GMM estimator performs well compared to both the difference and system GMM estimators. As an empirical illustration, I estimate the effect of class size reduction and private school attendance on student academic achievement using a value-added model with learning dynamics.