ESTIMATION OF DYNAMIC DISCRETE CHOICE MODELS BY MAXIMUM LIKELIHOOD AND THE SIMULATED METHOD OF MOMENTS

Philipp Eisenhauer, James Heckman and Stefano Mosso

International Economic Review, 2015, vol. 56, issue 2, 331-357

Abstract: We compare the performance of maximum likelihood (ML) and simulated method of moments (SMM) estimators for dynamic discrete choice models. We construct and estimate a simplified dynamic structural model of education that captures some basic features of educational choices in the United States in the 1980s and early 1990s. We use estimates from our model to simulate a synthetic data set and assess the ability of ML and SMM to recover the model parameters on this sample. We investigate the performance of alternative tuning parameters for SMM.

Date: 2015
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https://doi.org/10.1111/iere.12107

Related works:
Working Paper: Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments (2014)
Working Paper: Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments (2014)
Working Paper: Estimation of dynamic discrete choice models by maximum likelihood and the simulated method of moments (2014)
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