A Computationally Practical Simulation Estimator for Panel Data
The author develops a practical extension of D. McFadden's method of simulated moments estimator for limited dependent variable models to the panel data case. The method is based on factorization of the method of simulated moments first order condition into transition probabilities, along with development of an accurate new method for simulating transition probabilities. Monte Carlo tests indicate that this method of simulated moments estimator performs quite well relative to quadrature-based maximum likelihood estimators. It allows estimation of complex panel data models involving random effects and ARMA errors in computational time similar to those necessary for estimation of random effects models via maximum likelihood quadrature. Copyright 1994 by The Econometric Society.
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Volume (Year): 62 (1994)
Issue (Month): 1 (January)
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