“…For each application, we compare the accuracy of quantile forecasts obtained from simple quantile regression, averages of quantile regression forecasts obtained with one indicator at a time, partial quantile regression, quantile regression with ridge penalty, and a few different specifications of priors for Bayesian quantile regression. These prior specifications include a fixed Minnesota-type prior (e.g., Carriero, Clark, and Marcellino (2022)) and a horseshoe prior (e.g., Kohns and Szendrei (2021) and Mitchell, Poon, and Mazzi (2022)). In comparing accuracy, we consider a range of quantiles -spanning from the left to right tail -and use quantile scores (e.g., Giacomini and Komunjer (2005)), as well as quantile-weighted continuous ranked probability scores developed in Gneiting and Ranjan (2011) that consider the entire predictive density.…”