forward, backward, and stepwise confounding variable selection estimate the ATE compared to spike-and-slab Bayesian variable …. Overall, results suggest that Bayesian variable selection is more appealing in smaller sample sizes than frequentist variable …

allocation process, focusing on common heuristics and Bayesian methods. The Black-Litterman model, an application of the Bayesian …

's pollution equation remains unclear. This study uses a Bayesian approach and threshold estimation to quantitatively assess the … Bayesian techniques and threshold estimation, the research highlights the significant role of fiscal policy tools …

We ask whether Bayesian estimation creates a potential estimation bias as compared with standard estimation techniques … treat each in turn as the true model and create Bayesian estimates of it under priors from the true model and its false … alternative. The Bayesian estimation of macro models may thus give very misleading results by placing too much weight on prior …

This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using …

approach using a Bayesian MS-VAR which is net of these arbitrary components. This method allows for the consistent …

There has been a call for caution when using the conventional method for Bayesian inference in setidentified structural …

)), a derivation of the Bayesian methods developed in academia, has particular practical appeal for institutional investors …