Artikel
Bootstrap tests for overidentification in linear regression models
We study the finite-sample properties of tests for overidentifying restrictions in linear regression models with a single endogenous regressor and weak instruments. Under the assumption of Gaussian disturbances, we derive expressions for a variety of test statistics as functions of eight mutually independent random variables and two nuisance parameters. The distributions of the statistics are shown to have an ill-defined limit as the parameter that determines the strength of the instruments tends to zero and as the correlation between the disturbances of the structural and reduced-form equations tends to plus or minus one. This makes it impossible to perform reliable inference near the point at which the limit is ill-defined. Several bootstrap procedures are proposed. They alleviate the problem and allow reliable inference when the instruments are not too weak. We also study their power properties.
- Sprache
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Englisch
- Erschienen in
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Journal: Econometrics ; ISSN: 2225-1146 ; Volume: 3 ; Year: 2015 ; Issue: 4 ; Pages: 825-863 ; Basel: MDPI
- Klassifikation
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Wirtschaft
Econometric and Statistical Methods and Methodology: General
Hypothesis Testing: General
Statistical Simulation Methods: General
Multiple or Simultaneous Equation Models; Multiple Variables: General
- Thema
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Sargan test
Basmann test
Anderson-Rubin test
weak instruments
- Ereignis
-
Geistige Schöpfung
- (wer)
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Davidson, Russell
MacKinnon, James G.
- Ereignis
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Veröffentlichung
- (wer)
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MDPI
- (wo)
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Basel
- (wann)
-
2015
- DOI
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doi:10.3390/econometrics3040825
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:42 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Davidson, Russell
- MacKinnon, James G.
- MDPI
Entstanden
- 2015
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