Benchmark Priors Revisited On Adaptive Shrinkage and the Supermodel Effect in Bayesian Model Averaging |
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| Author:
| Feldkircher, Martin
Zeugner, Stefan |
| ISBN: | 978-1-4518-7349-8 |
| Publication Date: | Sep 2009 |
| Publisher: | International Monetary Fund
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| Book Format: | Paperback |
| List Price: | AUD $27.95 |
Book Description:
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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...
More DescriptionDefault 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.