A Macro-Augmented Jump-Diffusion Shadow-Rate Model

Abstract

This paper proposes a new shadow-rate model that incorporates stochastic jumps, macro-financial variables, and regime-dependent dynamics into the short-rate process. To this end, we extract the first principal component from daily zero-coupon yields in the United States, Euro Area, and United Kingdom and augment it with inflation, real GDP, unemployment, exchange rates, and sovereign CDS spreads. The latent short-rate component, augmented by these macro factors, follows a mean-reverting jump-diffusion process, and the final policy stance is constructed as a convex combination of the two pillars. We find that, relative to the standard benchmark in the literature, the resulting shadow rates exhibit smaller fitting errors and, in our forecasting exercises, provide more informative signals, particularly during periods of elevated macro-financial uncertainty. Robustness checks using an OLS VAR and a FAVAR framework broadly support these findings. Overall, our approach provides a flexible tool for policy analysis on monetary policy under extended episodes at or near the effective lower bound.