Structural Scenario Analysis with SVARs

Abstract

Macroeconomists seeking to construct conditional forecasts often face a choice between taking a stand on the details of a fully-specified structural model or relying on empirical correlations from vector autoregressions and remain silent about the underlying causal mechanisms. This paper develops tools for constructing "structural scenarios" that can be given an economic interpretation using identified structural VARs. We provide a unified and transparent treatment of conditional forecasting and structural scenario analysis and relate our approach to entropic forecast tilting. We advocate for a careful treatment of uncertainty, making the methods suitable for density forecasting and risk assessment. We also propose a metric to assess and compare the plausibility of alternative scenarios. We illustrate our methods with two applications: assessing the power of forward guidance about future interest rate policies and stress testing the reaction of bank profitability to an economic recession.

Binary Conditional Forecasts

“…In this paper, we develop methods for forming conditional forecasts of binary outcomes. We apply recent innovations on conditional forecasting in Bayesian VARs by Zha (1999) and, in particular, Antolin-Diaz, Petrella, andRubio-Ramirez (2020) to the Qual-VAR developed in Dueker (2005). The Qual-VAR is a standard VAR in which one series is a latent Gaussian variable that is deterministically related to the binary outcome in a manner similar to a probit.…”

“…Because the model retains a VAR structure, much of the existing literature on conditional forecasts remains applicable. In particular, we construct the conditional forecasts of the latent in a Bayesian framework similar to that described in Antolin-Diaz, Petrella, and Rubio-Ramirez (2020) for VARs with strictly observable predictors, but with an added step in which the latent variable is drawn from an appropriately truncated normal distribution. Forecasts of the latent then map directly to probabilistic forecasts of the binary event.…”