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:
Bayesian statistical decision theory.
Théorie de la décision bayésienne.
Bayesian statistical decision theory
Bayes-Statistik.
Panel.
Momentenmethode.
Acceso en línea:Texto completo

MARC

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100 1 |a Chen, Huigang,  |e author. 
245 1 0 |a Limited information Bayesian Model Averaging for dynamic panels with short time periods /  |c prepared by Huigang Chen, Alin Mirestean, and Charalambos Tsangarides. 
260 |a [Washington, DC] :  |b International Monetary Fund,  |c ©2009. 
300 |a 1 online resource (43 pages) :  |b color illustrations 
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490 1 |a IMF working paper ;  |v WP/09/74 
504 |a Includes bibliographical references (pages 25-27). 
588 0 |a Print version record. 
520 |a 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. 
506 |3 Use copy  |f Restrictions unspecified  |2 star  |5 MiAaHDL 
533 |a Electronic reproduction.  |b [Place of publication not identified] :  |c HathiTrust Digital Library,  |d 2011.  |5 MiAaHDL 
538 |a Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.  |u http://purl.oclc.org/DLF/benchrepro0212  |5 MiAaHDL 
583 1 |a digitized  |c 2011  |h HathiTrust Digital Library  |l committed to preserve  |2 pda  |5 MiAaHDL 
505 0 |a I. Introduction; II. Model Uncertainty in the Bayesian Context; A. Model Selection and Hypothesis Testing; B. Bayesian Model Averaging; C. Choice of Priors; III. Limited Information Bayesian Model Averaging; A.A Dynamic Panel Data Model with Endogenous Regressors; B. Estimation and Moment Conditions; C. The Limited Information Criterion; IV. Monte Carlo Simualtions and Results; A. The Data Generating Process; B. Simulation Results; V. Conclusion; References; Tables; 1. Posterior Probability of the True Model; 2. Posterior Probability Ratio of True Model/Best among the Other Models 
505 8 |a 3. Probability of Retrieving the True Model4. Model Recovery: Medians and Variances of Posterior Inclusi; 5. Model Recovery: Medians and Variances of Estimated Paramet; 6. Posterior Probability of the True Model (Non-Gaussian Case); 7. Posterior Probability Ratio: True Model/best among the Other Models (Non-Gaussian Case); 8. Probability of Retrieving the True Model (Non-Gaussian Case); 9. Model Recovery: Medians and Variances of Posterior Inclusion Probability for Each Variable (Non-Gaussian Case); 10. Model Recovery: Medians and Variances of Estimated Parameter Values (Non- Gaussian Case) 
505 8 |a Appendix A Figures1. Posterior Densities for the Probabilities in Table 1; 2. Posterior Densities for the Probabilities in Table 2; 3. Box Plots for Parameters in Table 5; 4. Posterior Densities for the Probabilities in Table 6; 5. Posterior Densities for the Probabilities in Table 7; 6. Box Plots for Parameters in Table 10 
546 |a English. 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Bayesian statistical decision theory. 
650 6 |a Théorie de la décision bayésienne. 
650 7 |a Bayesian statistical decision theory  |2 fast 
650 7 |a Bayes-Statistik.  |2 stw 
650 7 |a Panel.  |2 stw 
650 7 |a Momentenmethode.  |2 stw 
700 1 |a Mirestean, Alin,  |e author. 
700 1 |a Tsangarides, Charalambos G.,  |e author. 
710 2 |a International Monetary Fund.  |b Research Department. 
758 |i has work:  |a Limited information Bayesian model averaging for dynamic panels with short time periods (Text)  |1 https://id.oclc.org/worldcat/entity/E39PD3J8bdK7P7XCgjHBtpHdw3  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a Chen, Huigang.  |t Limited information Bayesian Model Averaging for dynamic panels with short time periods.  |d [Washington, DC] : International Monetary Fund (IMF), ©2009  |w (OCoLC)539056651 
830 0 |a IMF working paper ;  |v WP/09/74. 
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