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Identification and Estimation of Average Partial Effects in Semiparametric Binary Response Panel Models

作者: 发布时间:2022-04-25 点击数:
主讲人:Liu Yu
主讲人简介:

Liu Yu got her Ph.D. degree in Economics from University of Pennsylvania in 2017. She is now an Assistant Professor at the Department of Economics, Indiana University. Her research interest includes Econometrics, Macroeconomics, and Network Economics. She has published numerous papers on top economics journals, including Econometrica, Journal of Econometrics, JBES, JAE. She is now an Associate Editor of JAE. 

主持人:Xu Xingbai
讲座简介:

Average partial effects (APEs) are generally not point-identified in binary response panel models with unrestricted unobserved heterogeneity. We show their point-identification under an index sufficiency assumption on the unobserved heterogeneity, even when the error distribution is unspecified. This assumption does not impose parametric restrictions on the unobserved heterogeneity. We then construct a three-step semiparametric estimator for the APE. In the first step, we estimate the common parameters using either a conditional logit or smoothed maximum score estimator. In the second step, we estimate the conditional expectation of the outcomes given the indices and a generated regressor that depends on first-step estimates. In the third step, we average derivatives of this conditional expectation to obtain a partial mean that estimates the APE. We show that this proposed three-step APE estimator is consistent and asymptotically normal. We evaluate its finite-sample properties in Monte Carlo simulations. We then illustrate our estimator in a study of determinants of married women’s labor supply.

时间:2022-04-25(Monday)09:00-10:20
地点:Zoom Meeting
讲座语言:English
主办单位:太阳成tyc7111cc、王亚南经济研究院、邹至庄经济研究中心
承办单位:太阳成tyc7111cc统计学与数据科学系
期数:TBA
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