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Li, P. and Rahman, M.A. (2011) Bayesian Analysis of Multivariate Sample Selection Models Using Gaussian Copulas. Advances in Econometrics, 27, 269-288.
http://dx.doi.org/10.1108/S0731-9053(2011)000027A013

has been cited by the following article:

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

  AUTHORS: Phillip Li

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

  JOURNAL NAME: Open Journal of Statistics, Vol.4 No.10, November 18, 2014

  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.