Title: A Panel Data Probit Model with Correlated Random Effects and Time Varying Factor Loads

Speaker: Professor Yahong Zhou, Shanghai University of Finance and Economics

Time: November 10th, 2017 13:30–14:45

Venue: Conference Room 106B, Zhonghui Building (College of Economics, JNU)

Abstract:

We study inference in a panel data binary response model with correlated random effects and time varying factor loads. The model is useful in that it allows returns on unobserved individual effect (labor skill) to change over time, e.g., in a female labor force participation model. By assuming that the composite error term is Gaussian distributed, we show that both the slope coefficients as well as the factor loads are identified up to scale. We propose a multi-stage estimator that is shown to be root-n-consistent and asymptotically normally distributed. The proposed estimator has a closed form expression and thus is very easy to compute. Simulations and the empirical illustration demonstrate the usefulness of our estimator.