A Monte Carlo EM algorithm for FIML estimation of multivariate endogenous switching models with censored and discrete responses

Ricardo Smith ()
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Ricardo Smith: Division of Economics, CIDE

No DTE 425, Working Papers from CIDE, División de Economía

Abstract: This article presents a Monte Carlo EM algorithm to estimate multivariate endogenous switching regression models with censored and/or discrete responses and heteroscedastic errors. Advantages of the algorithm include: (1) it does not require numerical integration; (2) it reduces the estimation of the vector of slopes to the calculation of a GLS estimator and (3) numerical techniques are required only to estimate the parameters in the disturbance covariance matrix. Extensions to panel data are discussed. The algorithm is illustrated on both simulated data and on real data from an agricultural conservation program.

Pages: 19 pages
Date: 2008-10
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