Inference Based on Time-Varying SVARs Identified with Sign Restrictions

Jonas Arias, Rubio-Ramírez, Juan Francisco, Minchul Shin and Daniel Waggoner

No 18837, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: We propose an approach for Bayesian inference in \TV SVARs identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant \TV SVARs in which the prior and posterior densities of any sequence of structural parameters belonging to the class are invariant to orthogonal transformations of the sequence. Our methodology is new to the literature. In contrast to existing algorithms for inference based on sign restrictions, our algorithm is the first to draw from a uniform distribution over the sequences of orthogonal matrices given the reduced-form parameters. We illustrate our procedure for inference by analyzing the role played by monetary policy during the latest inflation surge.

Keywords: Time-varying parameters; Structural vector autoregressions; Sign restrictions (search for similar items in EconPapers)
JEL-codes: C11 C51 E52 E58 (search for similar items in EconPapers)
Date: 2024-02
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Working Paper: Inference Based on Time-Varying SVARs Identified with Sign Restrictions (2024)
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