IMF Working Papers

Benchmark Priors Revisited: On Adaptive Shrinkage and the Supermodel Effect in Bayesian Model Averaging

Author/Editor:

Martin Feldkircher ; Stefan Zeugner

Publication Date:

September 1, 2009

Electronic Access:

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Summary:

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.

Series:

Working Paper No. 2009/202

Subject:

Bayesian models Data processing Human capital Inflation Public investment and public-private partnerships (PPP)