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Limited information Bayesian Model Averaging for dynamic panels with short time periods /

Bayesian Model Averaging (BMA) provides a coherent mechanism to address the problem of model uncertainty. In this paper we extend the BMA framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Chen, Huigang (Autor), Mirestean, Alin (Autor), Tsangarides, Charalambos G. (Autor)
Autor Corporativo: International Monetary Fund. Research Department
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [Washington, DC] : International Monetary Fund, ©2009.
Colección:IMF working paper ; WP/09/74.
Temas:
Acceso en línea:Texto completo
Descripción
Sumario:Bayesian Model Averaging (BMA) provides a coherent mechanism to address the problem of model uncertainty. In this paper we extend the BMA framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation results suggest that asymptotically our methodology performs well both in Bayesian model selection and averaging. In particular, LIBMA recovers the data generating process very well, with high posterior inclusion.
Descripción Física:1 online resource (43 pages) : color illustrations
Bibliografía:Includes bibliographical references (pages 25-27).
ISBN:1462371922
9781462371921
1452712743
9781452712741
9786612842955
6612842954
1451872216
9781451872217
1282842951
9781282842953