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Generic inference on quantile and quantile effect functions for discrete outcomes

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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.

Language: Englisch

Bibliographic citation: Series: Discussion Papers ; No. 16-07

Classification: Wirtschaft
Hypothesis Testing: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

Subject: quantiles
quantile effects
treatment effects
distribution
discrete
mixed
count data
confidence bands
uniform inference

Event: Geistige Schöpfung

(who): Chernozhukov, Victor
Fernández-Val, Iván
Melly, Blaise
Wüthrich, Kaspar

Event: Veröffentlichung

(who): University of Bern, Department of Economics

(where): Bern

(when): 2016

Handle: http://hdl.handle.net/10419/149120

Last update: 10.03.2025, 11:43 AM CET

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Object type

Arbeitspapier

Associated

Chernozhukov, Victor
Fernández-Val, Iván
Melly, Blaise
Wüthrich, Kaspar
University of Bern, Department of Economics

Time of origin

2016

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