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Distribution-Free Estimation of Zero-Inflated Models with Unobserved Heterogeneity

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  • Rodica Gilles
  • Seik Kim

Abstract

Count models often best describe the nature of data in health economics, but the presence of fixed effects with excess zeros and overdispersion strictly limits the choice of estimation methods. This paper presents a quasi-conditional likelihood method to consistently estimate models with excess zeros and unobserved individual heterogeneity when the true generating process is unknown. Monte Carlo simulation studies show that our zero-inflated quasi-conditional maximum likelihood (ZI-QCML) estimator outperforms other methods and is robust to distributional misspecifications. We apply the ZI-QCML estimator to analyze the frequency of doctor visits.

Suggested Citation

  • Rodica Gilles & Seik Kim, 2013. "Distribution-Free Estimation of Zero-Inflated Models with Unobserved Heterogeneity," Working Papers UWEC-2013-03, University of Washington, Department of Economics.
    • Handle: RePEc:udb:wpaper:uwec-2013-03
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    File URL: http://faculty.washington.edu/seikkim/seikkim_qcmle.pdf
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    References listed on IDEAS

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    1. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
    2. García-Gómez, Pilar & Jones, Andrew M. & Rice, Nigel, 2010. "Health effects on labour market exits and entries," Labour Economics, Elsevier, vol. 17(1), pages 62-76, January.
    3. Andreas Million & Regina T. Riphahn & Achim Wambach, 2003. "Incentive effects in the demand for health care: a bivariate panel count data estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 387-405.
    4. Rainer Winkelmann, 2008. "Econometric Analysis of Count Data," Springer Books, Springer, edition 0, number 978-3-540-78389-3, September.
    5. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    6. Maarten Lindeboom & Marcel Kerkhofs, 2009. "Health and work of the elderly: subjective health measures, reporting errors and endogeneity in the relationship between health and work," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 1024-1046.
    7. Adriaan Kalwij & Frederic Vermeulen, 2008. "Health and labour force participation of older people in Europe: What do objective health indicators add to the analysis?," Health Economics, John Wiley & Sons, Ltd., vol. 17(5), pages 619-638, May.
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    Cited by:

    1. Moskvina, Victoria, 2019. "Modelling interregional mobility of university graduates in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 56, pages 99-122.
    2. Rodolfo Metulini & Roberto Patuelli & Daniel A. Griffith, 2018. "A Spatial-Filtering Zero-Inflated Approach to the Estimation of the Gravity Model of Trade," Econometrics, MDPI, vol. 6(1), pages 1-15, February.

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