Benchmark Priors Revisited : On Adaptive Shrinkage and the Supermodel Effect in Bayesian Model Averaging /
Default prior choices fixing Zellner's g are predominant in the Bayesian Model Averaging literature, but tend to concentrate posterior mass on a tiny set of models. The paper demonstrates this supermodel effect and proposes to address it by a hyper-g prior, whose data-dependent shrinkage adapts...
| Հիմնական հեղինակ: | |
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| Այլ հեղինակներ: | |
| Ձևաչափ: | Ամսագիր |
| Լեզու: | English |
| Հրապարակվել է: |
Washington, D.C. :
International Monetary Fund,
2009.
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| Շարք: | IMF Working Papers; Working Paper ;
No. 2009/202 |
| Առցանց հասանելիություն: | Full text available on IMF |
| Ամփոփում: | Default prior choices fixing Zellner's g are predominant in the Bayesian Model Averaging literature, but tend to concentrate posterior mass on a tiny set of models. The paper demonstrates this supermodel effect and proposes to address it by a hyper-g prior, whose data-dependent shrinkage adapts posterior model distributions to data quality. Analytically, existing work on the hyper-g-prior is complemented by posterior expressions essential to fully Bayesian analysis and to sound numerical implementation. A simulation experiment illustrates the implications for posterior inference. Furthermore, an application to determinants of economic growth identifies several covariates whose robustness differs considerably from previous results. |
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| Նյութի նկարագրություն: | <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required |
| Ֆիզիկական նկարագրություն: | 1 online resource (39 pages) |
| Ձևաչափ: | Mode of access: Internet |
| ISSN: | 1018-5941 |
| Հասանելի: | Electronic access restricted to authorized BRAC University faculty, staff and students |