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Estimation of Health Care Demand and its Implication on Income Effects of Individuals

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Abstract
Zero inflation and over-dispersion issues can significantly affect the predicted probabilities as well as lead to unreliable estimations in count data models. This paper investigates whether considering this issue for German Socioeconomic Panel (1984-1995), used by Riphahn et al (2003), provides any evidence of misspecification in their estimated models for adverse selection and moral hazard effects in health demand market The paper has the following contributions: first, it shows that estimated parameters for adverse selection and moral hazard effects are sensitive to the model choice; second, the random effects panel data as well as standard pooled data models do not provide reliable estimates for health care demand (doctor visits); third, it shows that by appropriately accounting for zero inflation and over-dispersion there is no evidence of adverse selection behaviour and that moral hazard plays a positive and significant role for visiting more doctors. These results are robust for both males and females’ subsamples as well as for the full data sample.

Suggested Citation

  • Hossein Kavand & Marcel-Cristian Voia, 2016. "Estimation of Health Care Demand and its Implication on Income Effects of Individuals," Carleton Economic Papers 16-01, Carleton University, Department of Economics, revised 26 Jun 2017.
    • Handle: RePEc:car:carecp:16-01
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    References listed on IDEAS

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    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273.
    2. Tammy Harris & Joseph M. Hilbe & James W. Hardin, 2014. "Modeling count data with generalized distributions," Stata Journal, StataCorp LP, vol. 14(3), pages 562-579, September.
    3. Keane, Michael & Stavrunova, Olena, 2016. "Adverse selection, moral hazard and the demand for Medigap insurance," Journal of Econometrics, Elsevier, vol. 190(1), pages 62-78.
    4. Maria Melkersson & Dan-Olof Rooth, 2000. "Modeling female fertility using inflated count data models," Journal of Population Economics, Springer;European Society for Population Economics, vol. 13(2), pages 189-203.
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    18. Gupta, Pushpa L. & Gupta, Ramesh C. & Tripathi, Ram C., 1996. "Analysis of zero-adjusted count data," Computational Statistics & Data Analysis, Elsevier, vol. 23(2), pages 207-218, December.
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    More about this item

    Keywords

    over-dispersion; zero-inflated distribution; adverse selection; moral hazard; health demand;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private

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