Simulation Estimation of Dynamic Panel Discrete Choice Models Using the t Distributions
Journal
Computational Economics
Journal Volume
43
Journal Issue
4
Pages
395-409
Date Issued
2014
Author(s)
Abstract
In this paper a practical robust simulation estimator is proposed for the dynamic panel data discrete choice models using the t distribution. The maximum simulated likelihood estimators are obtained through a recursive algorithm formulated by Geweke-Hajivassiliou-Keane simulators. Monte Carlo experiments indicate that the proposed robust simulation estimators perform well under the errors with longer than normal tails for a small simulation size, even with the initial conditions problem. © 2014 Springer Science+Business Media New York.
In this paper a practical robust simulation estimator is proposed for the dynamic panel data discrete choice models using the t distribution. The maximum simulated likelihood estimators are obtained through a recursive algorithm formulated by Geweke-Hajivassiliou-Keane simulators. Monte Carlo experiments indicate that the proposed robust simulation estimators perform well under the errors with longer than normal tails for a small simulation size, even with the initial conditions problem. © 2014 Springer Science+Business Media New York.
Type
journal article