Arbeitspapier
Sieve Wald and QLR inferences on semi/ nonparametric conditional moment models
This paper considers inference on functionals of semi/nonparametric conditional moment restrictions with possibly nonsmooth generalized residuals, which include all of the (nonlinear) nonparametric instrumental variables (IV) as special cases. There models are often illposed and hence it is difficult to verify whether a (possibly nonlinear) functional is root-n estimable or not. We provide computationally simple, unified inference procedures that are asymptotically valid regardless of whether a functional is root-n estimable or not. We establish the following new useful results: (1) the asymptotic normality of a plug-in penalized sieve minimum distance (PSMD) estimator of a (possibly nonlinear) functional; (2) the consistency of simple sieve variance estimators for the plug-in PSMD estimator, and hence the asymptotic chi-square distribution of the sieve Wald statistic; (3) the asymptotic chi-square distribution of an optimally weighted sieve quasi likelihood ratio (QLR) test under the null hypothesis; (4) the asymptotic tight distribution of a non-optimally weighted sieve QLR statistic under the null; (5) the consistency of generalized residual bootstrap sieve Wald and QLR tests; (6) local power properties of sieve Wald and QLR tests and of their bootstrap versions; (7) asymptotic properties of sieve Wald and SQLR for functionals of increasing dimension. Simulation studies and an empirical illustration of a nonparametric quantile IV regression are presented.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP38/14
- Klassifikation
-
Wirtschaft
- Thema
-
Nonlinear nonparametric instrumental variables
Penalized sieve minimum distance
Irregular functional
Sieve variance estimators
Sieve Wald
Sieve quasi likelihood ratio
Generalized residual bootstrap
Local power
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Chen, Xiaohong
Pouzo, Demian
- Ereignis
-
Veröffentlichung
- (wer)
-
Centre for Microdata Methods and Practice (cemmap)
- (wo)
-
London
- (wann)
-
2014
- DOI
-
doi:10.1920/wp.cem.2014.3814
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Chen, Xiaohong
- Pouzo, Demian
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2014
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