DP12579 Structural Scenario Analysis with SVARs

Author(s): Juan Antolin-Diaz, Ivan Petrella, Juan Francisco Rubio-Ramírez
Publication Date: January 2018
Keyword(s): Bayesian methods, Conditional forecasts, probability distribution, SVARs
JEL(s): C32, C53, E47
Programme Areas: Monetary Economics and Fluctuations
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=12579

In the context of vector autoregressions, conditional forecasts are typically constructed by specifying the future path of one or more variables while remaining silent about the structural shocks that might have caused the path. However, in many cases, researchers may be interested in identifying a structural vector autoregression and choosing which structural shock is driving the path of the conditioning variables. This would allow researchers to create a ''structural scenario'' that can be given an economic interpretation. In this paper we show how to construct structural scenarios and develop efficient algorithms to implement our methods. We show how structural scenario analysis can lead to results that are very different from, but complementary to, those of the traditional conditional forecasting exercises. We also propose an approach to assess and compare the plausibility of alternative scenarios. We illustrate our methods by applying them to two examples: comparing alternative monetary policy options and stress testing the reaction of bank profitability to an economic recession.