经济与社会研究院SEMINAR第6期

Internally Consistent Estimation of Nonlinear Panel Data Models with Correlated Random Effects

报告人：徐吉良副教授

时间：2016年7月14日下午2:00-3:00

地点：暨南大学经济学院楼102室

主办方：暨南大学经济与社会研究院

报告人简介：

徐吉良，现任中国人民大学汉青经济与金融高级研究院副教授、经济系副主任，曾任台湾嘉义中正大学助理教授。徐吉良于1998年6月毕业于台湾清华大学数学系，获数学学士与硕士学位；2004年6月获得美国印地安那大学伯明顿分校数学博士学位；2009年6月获得约翰霍普金斯大学经济学博士学位。主要研究领域包括：微观计量经济学，应用计量经济学，应用微观经济学，劳动经济学。研究成果发表于Journal of Econometrics, Econometric Journal,Empirical Economics等著名期刊。

论文摘要

This paper investigates identification and estimation of parametric nonlinear panel data models with correlated unobserved effects. It is shown under the Mundlak-type specification, a conditional distribution of the unobserved heterogeneity can be recovery by means of Fourier inversion formula.

Combining the proposed panel data models with the conditional distribution, we can construct a parametric family of average likelihood functions of observables and then the parameter vector is identifiable by the negative definiteness of the information matrix. The result fills an important theoretic gap for the misspecification issue in random effect approaches. Based on the identification condition, we propose a semiparametric two-step maximum likelihood estimator which is root n consistent and asymptotically normal. The finite-sample properties of the estimator are investigated through Monte Carlo simulations.