What’s Wrong with How We Teach Estimation and Inference in Econometrics? And What Should We Do About It?

Mark E. Schaffer*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The widespread use of “Null hypothesis significance testing” and p-values in empirical work has come in for widespread criticism from many directions in recent years. Nearly all this literature and commentary has, understandably, focused on practice: how researchers use, and abuse, these methods and tools, and what they should do instead. Surprisingly, relatively little attention has been devoted to what to do about how we teach econometrics and applied statistics more generally. I suggest that it is possible to teach students how to practice frequentist statistics sensibly if the core concepts they are taught at the start are “coverage” and interval estimation. I suggest various tools that can be used to convey these concepts.

Original languageEnglish
Title of host publicationFinancial Econometrics: Bayesian Analysis, Quantum Uncertainty, and Related Topics. ECONVN 2022
PublisherSpringer
Pages133-146
Number of pages14
ISBN (Electronic)9783030986896
ISBN (Print)9783030986889
DOIs
Publication statusPublished - 29 May 2022

Publication series

NameStudies in Systems, Decision and Control
Volume427
ISSN (Print)2198-4182
ISSN (Electronic)2198-4190

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Control and Systems Engineering
  • Automotive Engineering
  • Social Sciences (miscellaneous)
  • Economics, Econometrics and Finance (miscellaneous)
  • Control and Optimization
  • Decision Sciences (miscellaneous)

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