| Summary: | 碩士 === 國立清華大學 === 經濟學系 === 100 === The role of female in the labor market becomes indispensable as a result of the increasing popularization of female education, as well as the expanding labor force participation of women. Furthermore, estimating the return to education is always an important issue in labor economics. Three potential problems exist in estimating the return to education of females: selection bias, endogeneity and heterogeneous characteristics. Because of these problems, the traditional OLS estimation will lead to biased results. The goal of this thesis is to discuss how to obtain the unbiased estimate of the return to education of females using Taiwan’s data. This study applies the Heckman’s two-step estimation approach, the two-stage least squares estimation, and the propensity score matching approach to deal with the selection bias and the endogeneity problems. In addition, this study adopts the quantile regression model to take into account the heterogeneous characteristics issue in order to obtain better estimates of the return to education at different wage levels. The estimation results show that the return to higher education from different econometrics methods is between 3%-10% approximately. The estimated return from the OLS estimation method is the smallest, and followed by the Heckman’s two-step estimation approach, the two-stage least squares estimation, and the propensity score matching approach. This result suggests that the OLS estimation has largely underestimated the return to education. The quantile regression model’s results indicate that ignoring the selection bias and the endogeneity problems will underestimate the return to education of females on the right tail of the wages distribution. The return to education and the wages distribution show a significantly positive relationship. This study shows that education and personal skills are mutually reinforcing, hence females wage gap will be enlarged by education.
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