Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/149780
Authors: 
Chernozhukov, Victor
Fernandez-Val, Ivan
Melly, Blaise
Wüthrich, Kaspar
Year of Publication: 
2016
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP35/16
Abstract: 
This paper provides a method to construct simultaneous confidence bands for quantile and quantile effect functions for possibly discrete or mixed discrete-continuous random variables. The construction is generic and does not depend on the nature of the underlying problem. It works in conjunction with parametric, semiparametric, and nonparametric modeling strategies and does not depend on the sampling schemes. It is based upon projection of simultaneous confidence bands for distribution functions. We apply our method to analyze the distributional impact of insurance coverage on health care utilization and to provide a distributional decomposition of the racial test score gap. Our analysis generates new interesting findings, and complements previous analyses that focused on mean effects only. In both applications, the outcomes of interest are discrete rendering standard inference methods invalid for obtaining uniform confidence bands for quantile and quantile effects functions.
Subjects: 
quantiles
quantile effects
treatment effects
distribution
discrete
mixed
count data
confidence bands
uniform inference
Document Type: 
Working Paper

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