A bayesian approach to model-based clustering for panel probit models
Consideration of latent heterogeneity is of special importance in non linear models for gauging correctly the effect of explaining variables on the dependent variable. This paper adopts the stratified model-based clustering approach for modeling latent heterogeneity for panel probit models. Within a Bayesian framework an estimation algorithm dealing with the inherent label switching problem is provided. Determination of the number of clusters is based on the marginal likelihood and out-of-sample criteria. The ability to decide on the correct number of clusters is assessed within a simulation study indicating high accuracy for both approaches. Different concepts of marginal effects incorporating latent heterogeneity at different degrees arise within the considered model setup and are directly at hand within Bayesian estimation via MCMC methodology. An empirical illustration of the developed methodology indicates that consideration of latent heterogeneity via latent clusters provides the preferred model specification compared to a pooled and a random coefficient specification.
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- Fraley C. & Raftery A.E., 2002. "Model-Based Clustering, Discriminant Analysis, and Density Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 611-631, June.
- Bertschek, Irene & Lechner, Michael, 1998.
"Convenient estimators for the panel probit model,"
Journal of Econometrics,
Elsevier, vol. 87(2), pages 329-371, September.
- Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model-based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354.
- Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
- Matthew Stephens, 2000. "Dealing with label switching in mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 795-809.
- Ishwaran H. & James L.F. & Sun J., 2001. "Bayesian Model Selection in Finite Mixtures by Marginal Density Decompositions," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1316-1332, December.
- Lancaster, Tony, 2000. "The incidental parameter problem since 1948," Journal of Econometrics, Elsevier, vol. 95(2), pages 391-413, April.
- Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, October.
- Andrews, Donald W K & Ploberger, Werner, 1994.
"Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative,"
Econometric Society, vol. 62(6), pages 1383-1414, November.
- Tom Doan, . "APGRADIENTTEST: RATS procedure to perform Andrews-Ploberger Structural Break Test for GARCH/Maximum Likelihood," Statistical Software Components RTS00007, Boston College Department of Economics.
- Donald W.K. Andrews & Werner Ploberger, 1992. "Optimal Tests When a Nuisance Parameter Is Present Only Under the Alternative," Cowles Foundation Discussion Papers 1015, Cowles Foundation for Research in Economics, Yale University.
- Tom Doan, . "REGHBREAK: RATS procedure to perform structural break test with bootstrapped p-values," Statistical Software Components RTS00176, Boston College Department of Economics.
- Tom Doan, . "APBREAKTEST: RATS procedure to implement Andrews-Ploberger Structural Break Test," Statistical Software Components RTS00006, Boston College Department of Economics.
- Heard, Nicholas A. & Holmes, Christopher C. & Stephens, David A., 2006. "A Quantitative Study of Gene Regulation Involved in the Immune Response of Anopheline Mosquitoes: An Application of Bayesian Hierarchical Clustering of Curves," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 18-29, March.
- Frühwirth-Schnatter, Sylvia & Kaufmann, Sylvia, 2004.
"Model-based Clustering of Multiple Time Series,"
CEPR Discussion Papers
4650, C.E.P.R. Discussion Papers.
- Aßmann, Christian, 2007. "Determinants and Costs of Current Account Reversals under Heterogeneity and Serial Correlation," Economics Working Papers 2007,17, Christian-Albrechts-University of Kiel, Department of Economics.
- David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
- Chen, Jiahua & Khalili, Abbas, 2008. "Order Selection in Finite Mixture Models With a Nonsmooth Penalty," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1674-1683.
- Dunson, David B. & Herring, Amy H. & Siega-Riz, Anna Maria, 2008. "Bayesian Inference on Changes in Response Densities Over Predictor Clusters," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1508-1517.
- Surajit Ray & Bruce G. Lindsay, 2008. "Model selection in high dimensions: a quadratic-risk-based approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 95-118.
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