Arbeitspapier

Generic inference on quantile and quantile effect functions for discrete outcomes

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.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP35/16

Klassifikation
Wirtschaft
Thema
quantiles
quantile effects
treatment effects
distribution
discrete
mixed
count data
confidence bands
uniform inference

Ereignis
Geistige Schöpfung
(wer)
Chernozhukov, Victor
Fernandez-Val, Ivan
Melly, Blaise
Wüthrich, Kaspar
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2016

DOI
doi:10.1920/wp.cem.2016.3516
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Chernozhukov, Victor
  • Fernandez-Val, Ivan
  • Melly, Blaise
  • Wüthrich, Kaspar
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2016

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