Arbeitspapier
Empirical likelihood-based model selection criteria for moment condition models
In this note we propose model selection criteria (MSC) for unconditional moment models using empirical likelihood (EL) statistics in the construction of the MSC The use of EL-statistics in lieu of the more common J-statistics leads to a much more transparent interpretation of the MSC by providing a closer analogy with MSC in standard parametric likelihood models and underlying the common likelihood- (or information-) based underlying model selection procedures for bothe parametric as well as semi-parametric models.
- Language
-
Englisch
- Bibliographic citation
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Series: Working Paper ; No. 459
- Classification
-
Wirtschaft
- Subject
-
Wahrscheinlichkeitsrechnung
Statistischer Test
Theorie
Heteroskedastizität
- Event
-
Geistige Schöpfung
- (who)
-
Hong, Han
Preston, Bruce
Shum, Matthew
- Event
-
Veröffentlichung
- (who)
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The Johns Hopkins University, Department of Economics
- (where)
-
Baltimore, MD
- (when)
-
2001
- Handle
- Last update
-
10.03.2025, 11:41 AM CET
Data provider
This object is provided by:
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Hong, Han
- Preston, Bruce
- Shum, Matthew
- The Johns Hopkins University, Department of Economics
Time of origin
- 2001
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Sensitivity analysis using approximate moment condition models
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Parametric statistical models and likelihood
Estimation of dynamic discrete choice models by maximum likelihood and the simulated method of moments
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Sensitivity analysis using approximate moment condition models
Tests for neglected heterogeneity in moment condition models
Identification- and singularity-robust inference for moment condition models
Parametric statistical models and likelihood
Estimation of dynamic discrete choice models by maximum likelihood and the simulated method of moments
Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments
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Mixed models based on likelihood boosting