Arbeitspapier
Inference for functions of partially identified parameters in moment inequality models
This paper introduces a bootstrap-based inference method for functions of the parameter vector in a moment (in)equality model. As a special case, our method yields marginal confidence sets for individual coordinates of this parameter vector. Our inference method controls asymptotic size uniformly over a large class of data distributions. The current literature describes only two other procedures that deliver uniform size control for this type of problem: projection-based and subsampling inference. Relative to projection-based procedures, our method presents three advantages: (i) it weakly dominates in terms of finite sample power, (ii) it strictly dominates in terms of asymptotic power, and (iii) it is typically less computationally demanding. Relative to subsampling, our method presents two advantages: (i) it strictly dominates in terms of asymptotic power (for reasonable choices of subsample size), and (ii) it appears to be less sensitive to the choice of its tuning parameter than subsampling is to the choice of subsample size.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP22/14
- Klassifikation
-
Wirtschaft
Econometrics
Hypothesis Testing: General
Statistical Simulation Methods: General
- Thema
-
Partial Identification
Moment Inequalities
Subvector Inference
Hypothesis Testing
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Bugni, Federico
Canay, Ivan
Shi, Xiaoxia
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2014
- DOI
-
doi:10.1920/wp.cem.2014.2214
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Bugni, Federico
- Canay, Ivan
- Shi, Xiaoxia
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2014
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