Author(s)

Phillip Li

Department of Economics, Office of the Comptroller of the Currency, Washington, DC, USA.

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.

Multivariate Sample Selection, Heckman Correction, Incidental Truncation, Expectation Maximization

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.