Asymptotic analysis of statistical decision rules in econometrics

Keisuke Hirano, Jack R. Porter

Research output: Chapter in Book/Report/Conference proceedingChapter

11 Scopus citations

Abstract

Statistical decision rules map data into actions. Point estimators, inference procedures, and forecasting methods can be viewed as statistical decision rules. However, other types of rules are possible, such as rules for assigning individuals to treatments based on covariates, and methods for designing auctions. We discuss heuristics for constructing statistical decision rules, and survey results that characterize the properties of various classes of decision rules. Particular attention is paid to developing large-sample approximations to the distributions and associated risk properties of statistical decision rules.

Original languageEnglish (US)
Title of host publicationHandbook of Econometrics
EditorsSteven N. Durlauf, Lars Peter Hansen, James J. Heckman, Rosa L. Matzkin
PublisherElsevier B.V.
Pages283-354
Number of pages72
ISBN (Print)9780444636492
DOIs
StatePublished - Jan 2020

Publication series

NameHandbook of Econometrics
Volume7
ISSN (Print)1573-4412

Keywords

  • Limit experiments
  • Risk
  • Statistical decision theory
  • Treatment assignment rules

ASJC Scopus subject areas

  • Economics and Econometrics

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