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

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  • Ricardo Smith

    (Division of Economics, CIDE)

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.

Suggested Citation

  • Ricardo Smith, 2008. "A Monte Carlo EM algorithm for FIML estimation of multivariate endogenous switching models with censored and discrete responses," Working papers DTE 425, CIDE, División de Economía.
    • Handle: RePEc:emc:wpaper:dte425
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    File URL: http://www.economiamexicana.cide.edu/RePEc/emc/pdf/DTE/DTE425.pdf
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