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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 459
- Klassifikation
-
Wirtschaft
- Thema
-
Wahrscheinlichkeitsrechnung
Statistischer Test
Theorie
Heteroskedastizität
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Hong, Han
Preston, Bruce
Shum, Matthew
- Ereignis
-
Veröffentlichung
- (wer)
-
The Johns Hopkins University, Department of Economics
- (wo)
-
Baltimore, MD
- (wann)
-
2001
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 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.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Hong, Han
- Preston, Bruce
- Shum, Matthew
- The Johns Hopkins University, Department of Economics
Entstanden
- 2001
Ähnliche Objekte (12)
GEL criteria for moment condition models
Exogeneity in semiparametric moment condition models
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
On approximate likelihood in survival models
Forecasting using predictive likelihood model averaging
Mixed models based on likelihood boosting
Termination criteria for model transformation
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
GEL criteria for moment condition models
Exogeneity in semiparametric moment condition models
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
On approximate likelihood in survival models
Forecasting using predictive likelihood model averaging
Mixed models based on likelihood boosting
Termination criteria for model transformation
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
GEL criteria for moment condition models
Exogeneity in semiparametric moment condition models
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
On approximate likelihood in survival models
Forecasting using predictive likelihood model averaging
Mixed models based on likelihood boosting
Termination criteria for model transformation
Estimation of dynamic discrete choice models by maximum likelihood and the simulated method of moments