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Incentive effects in the demand for health care: a bivariate panel count data estimation Author info | Abstract | Publisher info | Download info | Related research | Statistics Andreas Million
Regina T. Riphahn
Achim Wambach
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This paper contributes in three dimensions to the literature on health care demand. First, it features the first application of a bivariate random effects estimator in a count data setting, to permit the efficient estimation of this type of model with panel data. Second, it provides an innovative test of adverse selection and confirms that high-risk individuals are more likely to acquire supplemental add-on insurance. Third, the estimations yield that in accordance with the theory of moral hazard, we observe a much lower frequency of doctor visits among the self-employed, and among mothers of small children. Copyright © 2002 John Wiley & Sons, Ltd.
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics .
Volume (Year): 18 (2003)
Issue (Month): 4 ()
Pages: 387-405
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Handle: RePEc:jae:japmet:v:18:y:2003:i:4:p:387-405Contact details of provider: Web page: http://www.interscience.wiley.com/jpages/0883-7252/
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.: Pierre-Andre Chiappori & Bernard Salanie, 2001.
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
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Teresa Bago d'Uva & Andrew M. Jones & Eddy van Doorslaer, 2007.
"Measurement of Horizontal Inequity in Health Care Utilisation using European Panel Data ,"
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Teresa Bago d’Uva & Andrew M. Jones & Eddy van Doorslaer, 2007.
"Measurement of horizontal inequity in health care utilisation using European Panel data ,"
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"Measurement of horizontal inequity in health care utilisation using European panel data ,"
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