predictive accuracy in now-casting and forecasting. Our empirical results show that both the monthly version of the DSGE and the …

This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large …

This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large …

While conditional forecasting has become prevalent both in the academic literature and in practice (e.g., bank stress … testing, scenario forecasting), its applications typically focus on continuous variables. In this paper, we merge elements … from the literature on the construction and implementation of conditional forecasts with the literature on forecasting …