Limited Information Bayesian Model Averaging for Dynamic Panels with Short Time Periods / / Alin Mirestean, Charalambos Tsangarides, Huigang Chen |
Autore | Mirestean Alin |
Pubbl/distr/stampa | Washington, D.C. : , : International Monetary Fund, , 2009 |
Descrizione fisica | 1 online resource (45 p.) |
Altri autori (Persone) |
TsangaridesCharalambos
ChenHuigang |
Collana | IMF Working Papers |
Soggetto topico |
Panel analysis
Bayesian statistical decision theory Econometrics Data Processing Bayesian Analysis: General Estimation Data Collection and Data Estimation Methodology Computer Programs: General Bayesian inference Econometrics & economic statistics Data capture & analysis Bayesian models Estimation techniques Data processing Econometric models Electronic data processing |
ISBN |
1-4623-7192-2
1-4527-1274-3 9786612842955 1-4518-7221-6 1-282-84295-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents; 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
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) 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 |
Record Nr. | UNINA-9910788337703321 |
Mirestean Alin | ||
Washington, D.C. : , : International Monetary Fund, , 2009 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Limited Information Bayesian Model Averaging for Dynamic Panels with Short Time Periods / / Alin Mirestean, Charalambos Tsangarides, Huigang Chen |
Autore | Mirestean Alin |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Washington, D.C. : , : International Monetary Fund, , 2009 |
Descrizione fisica | 1 online resource (45 p.) |
Disciplina | 332.152 |
Altri autori (Persone) |
ChenHuigang
TsangaridesCharalambos |
Collana | IMF Working Papers |
Soggetto topico |
Panel analysis
Bayesian statistical decision theory Bayesian Analysis: General Bayesian inference Bayesian models Computer Programs: General Data capture & analysis Data Collection and Data Estimation Methodology Data Processing Data processing Econometric models Econometrics & economic statistics Econometrics Electronic data processing Estimation techniques Estimation |
ISBN |
1-4623-7192-2
1-4527-1274-3 9786612842955 1-4518-7221-6 1-282-84295-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents; 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
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) 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 |
Record Nr. | UNINA-9910812320003321 |
Mirestean Alin | ||
Washington, D.C. : , : International Monetary Fund, , 2009 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|