Citation

Discussion Paper Details

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

Author(s): Christiane Baumeister and James Hamilton

Publication Date: January 2020

Keyword(s): Bayesian inference, Capital Flows, identified set, informative priors, monetary policy, sign restrictions and structural vector autoregressions

Programme Area(s): International Macroeconomics and Finance and Monetary Economics and Fluctuations

Abstract: 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.

For full details and related downloads, please visit: https://cepr.org/active/publications/discussion_papers/dp.php?dpno=14271

Bibliographic Reference

Baumeister, C and Hamilton, J. 2020. 'Drawing Conclusions from Structural Vector Autoregressions Identified on the Basis of Sign Restrictions'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=14271