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Working Paper
Bells and Whistles of Nowcasting Models: Which Matter and When?
This paper investigates which features of a Bayesian dynamic factor model improve U.S. GDP nowcasts and whether their contribution varies across historical episodes. Using pseudo-real-time information sets for 25 series, we estimate 16 combinations of dynamic heterogeneity, stochastic volatility, time-varying long-run growth, and a multiplicative outlier adjustment. We evaluate their marginal contributions to point, density, and quantile score forecasts using balanced paired factorial contrasts. Dynamic heterogeneity improves point, density, and tail forecasts, and it is the only feature that ...