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Reforming health care: Evidence from quantile regressions for counts


Winkelmann, Rainer (2005). Reforming health care: Evidence from quantile regressions for counts. Journal of Health Economics, 25(1):131-145.

Abstract

I consider the problem of estimating the effect of a health care reform on the frequency of individual
doctor visits when the reform effect is potentially different in different parts of the outcome distribution.
Quantile regression is a powerful method for studying such heterogeneous treatment effects. Only
recently has this method been extended to situations where the dependent variable is a (non-negative
integer) count. An analysis of a 1997 health care reform in Germany shows that lower quantiles, such
as the first quartile, fell by substantially larger amounts than what would have been predicted based
on Poisson or negative binomial models.

I consider the problem of estimating the effect of a health care reform on the frequency of individual
doctor visits when the reform effect is potentially different in different parts of the outcome distribution.
Quantile regression is a powerful method for studying such heterogeneous treatment effects. Only
recently has this method been extended to situations where the dependent variable is a (non-negative
integer) count. An analysis of a 1997 health care reform in Germany shows that lower quantiles, such
as the first quartile, fell by substantially larger amounts than what would have been predicted based
on Poisson or negative binomial models.

Citations

22 citations in Web of Science®
22 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Language:English
Date:22 June 2005
Deposited On:11 Feb 2008 12:21
Last Modified:05 Apr 2016 12:17
Publisher:Elsevier
ISSN:0167-6296
Publisher DOI:10.1016/j.jhealeco.2005.03.005
Permanent URL: http://doi.org/10.5167/uzh-1167

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