DP14271 Drawing Conclusions from Structural Vector Autoregressions Identified on the Basis of Sign Restrictions

Author(s): Christiane Baumeister, James Hamilton
Publication Date: January 2020
Keyword(s): Bayesian inference, Capital Flows, identified set, informative priors, monetary policy, sign restrictions, structural vector autoregressions
JEL(s): C30, E5, F2
Programme Areas: International Macroeconomics and Finance, Monetary Economics and Fluctuations
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=14271

This paper discusses the problems associated with using information about the signs of certain magnitudes as a basis for drawing structural conclusions in vector autoregressions. We also review available tools to solve these problems. For illustration we use Dahlhaus and Vasishtha's (2019) study of the effects of a U.S. monetary contraction on capital flows to emerging markets. We explain why sign restrictions alone are not enough to allow us to answer the question and suggest alternative approaches that could be used.