A Computationally Practical Robust Simulation Estimator for Dynamic Panel Tobit Models

Chang Sheng-Kai ()
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Chang Sheng-Kai: National Taiwan University

Studies in Nonlinear Dynamics & Econometrics, 2011, vol. 15, issue 4, 21

Abstract: In this paper, a computationally robust simulation estimator is proposed for the dynamic panel Tobit model with large categories of dependence structures. The maximum simulated likelihood estimators are obtained through a recursive algorithm formulated by Geweke-Hajivassiliou-Keane and Gibbs sampling simulators. Monte Carlo experiments indicate that the proposed robust simulation estimators perform well under the errors having a heavy-tailed distribution, even for a small simulation size. The initial conditions problem is also investigated for the robust simulation estimators through Monte Carlo experiments.

Date: 2011
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DOI: 10.2202/1558-3708.1832

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