There has been a call for caution when using the conventional method for Bayesian inference in setidentified structural vector autoregressions on the grounds that the uniform prior over the set of orthogonal matrices could be nonuniform for individual impulse responses or other quantity of...

We propose an approach for Bayesian inference in time-varying structural vector autoregressions (SVARs) identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant time-varying SVARs in which the prior and posterior densities of any sequence of structural...

Are optimism shocks an important source of business cycle fluctuations? Are deficit-financed tax cuts better than deficit-financed spending to increase output? These questions have been previously studied using structural vector autoregressions (SVAR) identified with sign and zero restrictions...

Motivated by the increasing use of external instruments to identify structural vector autoregressions (SVARs), we develop algorithms for exact finite sample inference in this class of time series models, commonly known as proxy-SVARs. Our algorithms make independent draws from the...

This paper studies the effects of monetary policy shocks using structural vector autoregressions (SVARs). We achieve identification by imposing sign and zero restrictions on the systematic component of monetary policy. We consistently find that an increase in the fed funds rate induces a...

We study alternative approaches to the withdrawal of prolonged unconventional monetary stimulus ("exit strategies") by central banks in large, advanced economies. We first show empirically that large-scale asset purchases affect the exchange rate and domestic and foreign term premiums more...