Estimation of Multivariate Sample Selection Models via a Parameter-Expanded Monte Carlo EM Algorithm

Abstract

This paper develops a parameter-expanded Monte Carlo EM (PX-MCEM) algorithm to perform maximum likelihood estimation in a multivariate sample selection model. In contrast to the current methods of estimation, the proposed algorithm does not directly depend on the observed-data likelihood, the evaluation of which requires intractable multivariate integrations over normal densities. Moreover, the algorithm is simple to implement and involves only quantities that are easy to simulate or have closed form expressions.

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Li, P. (2014) Estimation of Multivariate Sample Selection Models via a Parameter-Expanded Monte Carlo EM Algorithm. Open Journal of Statistics, 4, 851-856. doi: 10.4236/ojs.2014.410080.

Conflicts of Interest

The authors declare no conflicts of interest.

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