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Finite Mixture for Panels with Fixed Effects

Author

Listed:
  • Deb Partha

    (Department of Economics, Hunter College and the Graduate Center, City University of New York, and National Bureau of Economic Research)

  • Trivedi Pravin K.

    ()

Abstract

This paper develops finite mixture models with fixed effects for two families of distributions for which the incidental parameter problem has a solution. Analytical results are provided for mixtures of Normals and mixtures of Poisson. We provide algorithms based on the expectations-maximization (EM) approach as well as computationally simpler equivalent estimators that can be used in the case of the mixtures of normals. We design and implement a Monte Carlo study that examines the finite sample performance of the proposed estimator and also compares it with other estimators such the Mundlak-Chamberlain conditionally correlated random effects estimator. The results of Monte Carlo experiments suggest that our proposed estimators of such models have excellent finite sample properties, even in the case of relatively small T and moderately sized N dimensions. The methods are applied to models of healthcare expenditures and counts of utilization using data from the Health and Retirement Study.

Suggested Citation

  • Deb Partha & Trivedi Pravin K., 2013. "Finite Mixture for Panels with Fixed Effects," Journal of Econometric Methods, De Gruyter, vol. 2(1), pages 35-51, July.
  • Handle: RePEc:bpj:jecome:v:2:y:2013:i:1:p:35-51:n:7
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    References listed on IDEAS

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    1. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
    2. David Card & Carlos Dobkin & Nicole Maestas, 2004. "The Impact of Nearly Universal Insurance Coverage on Health Care Utilization and Health: Evidence from Medicare," NBER Working Papers 10365, National Bureau of Economic Research, Inc.
    3. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54.
    4. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    5. Geert Dhaene & Koen Jochmans, 2011. "Profile-score Adjustements for Nonlinearfixed-effect Models," Working Papers hal-01073733, HAL.
    6. Deb, Partha & Trivedi, Pravin K., 2002. "The structure of demand for health care: latent class versus two-part models," Journal of Health Economics, Elsevier, vol. 21(4), pages 601-625, July.
    7. Conway, Karen Smith & Deb, Partha, 2005. "Is prenatal care really ineffective? Or, is the 'devil' in the distribution?," Journal of Health Economics, Elsevier, vol. 24(3), pages 489-513, May.
    8. David Card & Carlos Dobkin & Nicole Maestas, 2008. "The Impact of Nearly Universal Insurance Coverage on Health Care Utilization: Evidence from Medicare," American Economic Review, American Economic Association, vol. 98(5), pages 2242-2258, December.
    9. Anders Skrondal & Sophia Rabe-Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745.
    10. Smith, James P, 1998. "Socioeconomic Status and Health," American Economic Review, American Economic Association, vol. 88(2), pages 192-196, May.
    11. Deb, Partha & Trivedi, Pravin K, 1997. "Demand for Medical Care by the Elderly: A Finite Mixture Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 313-336, May-June.
    12. Lancaster, Tony, 2000. "The incidental parameter problem since 1948," Journal of Econometrics, Elsevier, vol. 95(2), pages 391-413, April.
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    Cited by:

    1. Silvia Balia, 2014. "Survival expectations, subjective health and smoking: evidence from SHARE," Empirical Economics, Springer, vol. 47(2), pages 753-780, September.
    2. Péter Elek & Balázs Váradi & Márton Varga, 2015. "Effects of Geographical Accessibility on the Use of Outpatient Care Services: Quasi‐Experimental Evidence from Panel Count Data," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1131-1146, September.
    3. Thomas Bassetti & Raul Caruso & Darwin Cortes, 2015. "Behavioral differences in violence: The case of intra-group differences of Paramilitaries and Guerrillas in Colombia," DISCE - Quaderni dell'Istituto di Politica Economica ispe0073, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    4. repec:spr:jstada:v:4:y:2017:i:1:d:10.1186_s40488-017-0066-3 is not listed on IDEAS
    5. repec:ris:apltrx:0315 is not listed on IDEAS
    6. Ryo Okui & Wendun Wang, 2018. "Heterogeneous structural breaks in panel data models," Papers 1801.04672, arXiv.org.
    7. Galina Besstremyannaya, 2014. "Heterogeneous effect of coinsurance rate on healthcare costs: generalized finite mixtures and matching estimators," Discussion Papers 14-014, Stanford Institute for Economic Policy Research.
    8. Egger, Peter H. & Merlo, Valeria & Wamser, Georg, 2014. "Unobserved tax avoidance and the tax elasticity of FDI," Journal of Economic Behavior & Organization, Elsevier, vol. 108(C), pages 1-18.
    9. Deguilhem, Thibaud & Berrou, Jean-Philippe & Combarnous, François, 2017. "Using your ties to get a worse job? The differential effects of social networks on quality of employment: Evidence from Colombia," MPRA Paper 78628, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • J28 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Safety; Job Satisfaction; Related Public Policy
    • I1 - Health, Education, and Welfare - - Health

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