Large Bayesian SVARs with linear restrictions

Chenghan Hou

Journal of Econometrics, 2024, vol. 244, issue 1

Abstract: This paper develops a Markov Chain Monte Carlo (MCMC) algorithm for Bayesian inference in large structural vector autoregressions (SVARs) with linear restrictions. Our proposed method is based on a novel parameter transformation scheme, which aims to facilitate sampling from the posterior distribution of model parameters when linear equality and inequality restrictions are imposed on contemporaneous impulse responses. A prominent feature of the proposed methodology is its applicability for inference in SVARs with over-identifying restrictions. In our empirical application, we demonstrate the usefulness of our method by employing a large Proxy-SVAR with multiple proxy variables to simultaneously identify multiple macroeconomic shocks and investigate their contributions to the 2007–09 Recession.

Keywords: Large vector autoregression; Equality and inequality restrictions; Over-identifying restrictions; Proxy-SVAR (search for similar items in EconPapers)
JEL-codes: C11 C32 C55 E52 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:244:y:2024:i:1:s0304407624001957

DOI: 10.1016/j.jeconom.2024.105850

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