The Tenth Periodic Monitoring Report (PMR) on the Status of Management
Implementation Plans (MIPs) in Response to Board-Endorsed Independent Evaluation
Office (IEO) Recommendations assesses the progress made over the last year on actions
contained in 10 MIPs with open management actions.
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.