Limited information Bayesian Model Averaging for dynamic panels with short time periods / prepared by Huigang Chen, Alin Mirestean, and Charalambos Tsangarides.
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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Full Text (via ProQuest) |
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| Main Authors: | , , |
| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
[Washington, DC] :
International Monetary Fund,
©2009.
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| Series: | IMF working paper ;
WP/09/74. |
| Subjects: |
| Summary: | 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. |
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| Physical Description: | 1 online resource (43 pages) : color illustrations. |
| Bibliography: | Includes bibliographical references (pages 25-27) |
| ISBN: | 1462371922 9781462371921 1452712743 9781452712741 9786612842955 6612842954 1451872216 9781451872217 1282842951 9781282842953 |