Arbeitspapier

Practical and theoretical advances in inference for partially identified models

This paper surveys some of the recent literature on inference in partially identified models. After reviewing some basic concepts, including the definition of a partially identified model and the identified set, we turn our attention to the construction of confidence regions in partially identified settings. In our discussion, we emphasize the importance of requiring confidence regions to be uniformly consistent in level over relevant classes of distributions. Due to space limitations, our survey is mainly limited to the class of partially identified models in which the identified set is characterized by a finite number of moment inequalities or the closely related class of partially identified models in which the identified set is a function of a such a set. The latter class of models most commonly arise when interest focuses on a subvector of a vectorvalued parameter, whose values are limited by a finite number of moment inequalities. We then rapidly review some important parts of the broader literature on inference in partially identified models and conclude by providing some thoughts on fruitful directions for future research.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP05/16

Klassifikation
Wirtschaft
Hypothesis Testing: General
Semiparametric and Nonparametric Methods: General
Thema
Partially Identified Model
Confidence Regions
Uniform Asymptotic Validity
Moment Inequalities
Subvector Inference

Ereignis
Geistige Schöpfung
(wer)
Canay, Ivan
Shaikh, Azeem
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2016

DOI
doi:10.1920/wp.cem.2016.0516
Handle
Letzte Aktualisierung
10.03.2025, 11:44 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

  • Canay, Ivan
  • Shaikh, Azeem
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2016

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