Average density estimators: Efficiency and bootstrap consistency

Matias D. Cattaneo, Michael Jansson

Research output: Contribution to journalArticlepeer-review

Abstract

This paper highlights a tension between semiparametric efficiency and bootstrap consistency in the context of a canonical semiparametric estimation problem, namely the problem of estimating the average density. It is shown that although simple plug-in estimators suffer from bias problems preventing them from achieving semiparametric efficiency under minimal smoothness conditions, the nonparametric bootstrap automatically corrects for this bias and that, as a result, these seemingly inferior estimators achieve bootstrap consistency under minimal smoothness conditions. In contrast, several “debiased” estimators that achieve semiparametric efficiency under minimal smoothness conditions do not achieve bootstrap consistency under those same conditions.

Original languageEnglish (US)
JournalEconometric Theory
DOIs
StateAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Social Sciences (miscellaneous)
  • Economics and Econometrics

Fingerprint

Dive into the research topics of 'Average density estimators: Efficiency and bootstrap consistency'. Together they form a unique fingerprint.

Cite this