Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/76166
Authors: 
Winkelmann, Rainer
Year of Publication: 
2003
Series/Report no.: 
Working Paper, Socioeconomic Institute, University of Zurich 0314
Abstract: 
I consider the problem of evaluating the effect of a health care reform on the demand for doctor visits when the effect is potentially different in different parts of the outcome distribution. Quantile regression is a useful technique for studying such heterogeneous treatment effects. Recent progree has been made to extend such methods to applications with a count dependent variable. An analysis of a 1997 health care reform in Germany shows the benefit of the approach: lower quantiles, such as the 25 percent quantile, fell by substantially larger amounts than what would have been predicted based on Poisson or negative binomial models.
Subjects: 
heterogeneous treatment effect
count data
quantile regression
Poisson model
JEL: 
I11
I18
C25
Document Type: 
Working Paper

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