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Bayesian inference on structural impulse response functions

Author(s): Plagborg-Møller, Mikkel

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Abstract: Copyright © 2019 The Author. I propose to estimate structural impulse responses from macroeconomic time series by doing Bayesian inference on the Structural Vector Moving Average representation of the data. This approach has two advantages over Structural Vector Autoregressions. First, it imposes prior information directly on the impulse responses in a flexible and transparent manner. Second, it can handle noninvertible impulse response functions, which are often encountered in applications. Rapid simulation of the posterior distribution of the impulse responses is possible using an algorithm that exploits the Whittle likelihood. The impulse responses are partially identified, and I derive the frequentist asymptotics of the Bayesian procedure to show which features of the prior information are updated by the data. The procedure is used to estimate the effects of technological news shocks on the U.S. business cycle.
Publication Date: Jan-2019
Citation: Plagborg-Møller, M. (2019). Bayesian inference on structural impulse response functions. Quantitative Economics, 10 (1), 145 - 184. doi:10.3982/QE926
DOI: doi:10.3982/QE926
ISSN: 1759-7323
EISSN: 1759-7331
Pages: 145 - 184
Type of Material: Journal Article
Journal/Proceeding Title: Quantitative Economics
Version: Final published version. This is an open access article.

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