Simulation Estimation of Dynamic Panel Discrete Choice Models Using the <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$t$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>t</mi> </math> </EquationSource> </InlineEquation> Distributions

In this paper a practical robust simulation estimator is proposed for the dynamic panel data discrete choice models using the <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$t$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>t</mi> </math> </EquationSource> </InlineEquation> 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. Copyright Springer Science+Business Media New York 2014