Shadow-rate VARs - Andrea Carriero; Todd E. Clark; Massimiliano Marcellino; Elmar Mertens (Deutsche Bundesbank, 2023)
VARs are a popular tool for forecasting and structural analysis, but ill-suited to handle occasionally binding constraints, like the effective lower bound on nominal interest rates. We extend the VAR framework by modeling interest rates as censored observations of a latent shadow-rate process, and propose an efficient sampler for Bayesian estimation of such 'shadow-rate VARs.' We analyze specifications where actual and shadow rates serve as explanatory variables and find benefits of including both. In comparison to a standard VAR, shadow-rate VARs generate superior predictions for short- and long-term interest rates, and deliver some gains for macroeconomic variables in US data. Our structural analysis estimates economic responses to shocks in financial conditions, showing strong differences in the reaction of interest rates depending on whether the ELB binds or not. After an adverse shock, our shadow-rate VAR sees a stronger decline of economic activity at the ELB rather than when not.
Keywords: C34; C53; E17; E37; E43; E47; 330; Macroeconomic forecasting; effective lower bound; term structure; censored observations