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Inference Based On Time-Varying SVARs Identified with Time Restrictions

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Abstract

We propose an approach for Bayesian inference in time-varying structural vector autoregressions (SVARs) identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant time-varying 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.

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  • Jonas E. Arias & Juan F. Rubio-Ramirez & Minchul Shin & Daniel F. Waggoner, 2024. "Inference Based On Time-Varying SVARs Identified with Time Restrictions," FRB Atlanta Working Paper 2024-4, Federal Reserve Bank of Atlanta.
    • Handle: RePEc:fip:fedawp:97982
    DOI: 10.29338/wp2024-04
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    Keywords

    time-varying parameters; structural vector autoregressions; identification;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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