OJS  Vol.4 No.10 , December 2014
Estimation of Multivariate Sample Selection Models via a Parameter-Expanded Monte Carlo EM Algorithm
Author(s) Phillip Li
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.

Cite this paper
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.
References
[1]   Heckman, J. (1974) Shadow Prices, Market Wages, and Labor Supply. Econometrica, 42, 679-694.
http://dx.doi.org/10.2307/1913937

[2]   Heckman, J. (1976) The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models. Annals of Economic and Social Measurement, 5, 475-492.

[3]   Heckman, J. (1979) Sample Selection Bias as a Specification Error. Econometrica, 47, 153-161.
http://dx.doi.org/10.2307/1912352

[4]   Su, S.J. and Yen, S.T. (2000) A Censored System of Cigarette and Alcohol Consumption. Applied Economics, 32, 729-737.
http://dx.doi.org/10.1080/000368400322354

[5]   Yen, S.T., Kan, K. and Su, S.J. (2002) Household Demand for Fats and Oils: Two-Step Estimation of a Censored Demand System. Applied Economics, 34, 1799-1806.
http://dx.doi.org/10.1080/00036840210125008

[6]   Hao, A.F. (2008) A Discrete-Continuous Model of Households’ Vehicle Choice and Usage, with an Application to the Effects of Residential Density. Transportation Research Part B: Methodological, 42, 736-758.
http://dx.doi.org/10.1016/j.trb.2008.01.004

[7]   Li, P. (2011) Estimation of Sample Selection Models with Two Selection Mechanisms. Computational Statistics & Data Analysis, 55, 1099-1108.
http://dx.doi.org/10.1016/j.csda.2010.09.006

[8]   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

[9]   Yen, S.T. (2005) A Multivariate Sample-Selection Model: Estimating Cigarette and Alcohol Demands with Zero Observations. American Journal of Agricultural Economics, 87, 453-466.
http://dx.doi.org/10.1111/j.1467-8276.2005.00734.x

[10]   Tauchmann, H. (2010) Consistency of Heckman-Type Two-Step Estimators for the Multivariate Sample-Selection Model. Applied Economics, 42, 3895-3902.
http://dx.doi.org/10.1080/00036840802360179

[11]   Puhani, P.A. (2000) The Heckman Correction for Sample Selection and Its Critique. Journal of Economic Surveys, 14, 53-68.
http://dx.doi.org/10.1111/1467-6419.00104

[12]   Dempster, A.P., Laird, N.M. and Rubin, D.B. (1977) Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society, 39, 1-38.
http://dx.doi.org/10.2307/2984875

[13]   Liu, C., Rubin, D.B. and Wu, Y.N. (1998) Parameter Expansion to Accelerate EM: The PX-EM Algorithm. Biometrika, 85, 755-770.
http://dx.doi.org/10.1093/biomet/85.4.755

 
 
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