Arbeitspapier

Impossible inference in econometrics: Theory and applications

This paper studies models in which hypothesis tests have trivial power, that is, power smaller than size. This testing impossibility, or impossibility type A, arises when any alternative is not distinguishable from the null. We also study settings where it is impossible to have almost surely bounded confidence sets for a parameter of interest. This second type of impossibility (type B) occurs under a condition weaker than the condition for type A impossibility: the parameter of interest must be nearly unidentifi ed. Our theoretical framework connects many existing publications on impossible inference that rely on different notions of topologies to show models are not distinguishable or nearly unidentifi ed. We also derive both types of impossibility using the weak topology induced by convergence in distribution. Impossibility in the weak topology is often easier to prove, it is applicable for many widely-used tests, and it is useful for robust hypothesis testing. We conclude by demonstrating impossible inference in multiple economic applications of models with discontinuity and time-series models.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP02/19

Klassifikation
Wirtschaft
Hypothesis Testing: General
Semiparametric and Nonparametric Methods: General
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Thema
hypothesis tests
confidence intervals
weak identification
regression discontinuity

Ereignis
Geistige Schöpfung
(wer)
Bertanha, Marinho
Moreira, Marcelo J.
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2019

DOI
doi:10.1920/wp.cem.2019.0219
Handle
Letzte Aktualisierung
10.03.2025, 11:41 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

  • Bertanha, Marinho
  • Moreira, Marcelo J.
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2019

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