Robust Bayesian Inference in Proxy Svars

45 Pages Posted: 8 May 2020

See all articles by Raffaella Giacomini

Raffaella Giacomini

University College London - Department of Economics; University of California, Los Angeles - Department of Economics

Toru Kitagawa

University College London

Matthew Read

University College London - Department of Economics

Date Written: April 2020

Abstract

We develop methods for robust Bayesian inference in structural vector autoregressions (SVARs) where the parameters of interest are set-identified using external instruments, or 'proxy SVARs'. Set-identification in these models typically occurs when there are multiple instruments for multiple structural shocks. Existing Bayesian approaches to inference in proxy SVARs require researchers to specify a single prior over the model's parameters, but, under set-identification, a component of the prior is never revised. We extend the robust Bayesian approach to inference in set-identified models proposed by Giacomini and Kitagawa (2018) – which allows researchers to relax potentially controversial point-identifying restrictions without having to specify an unrevisable prior – to proxy SVARs. We provide new results on the frequentist validity of the approach in proxy SVARs. We also explore the effect of instrument strength on inference about the identified set. We illustrate our approach by revisiting Mertens and Ravn (2013) and relaxing the assumption that they impose to obtain point identification.

Suggested Citation

Giacomini, Raffaella and Kitagawa, Toru and Read, Matthew, Robust Bayesian Inference in Proxy Svars (April 2020). CEPR Discussion Paper No. DP14626, Available at SSRN: https://ssrn.com/abstract=3594257

Raffaella Giacomini (Contact Author)

University College London - Department of Economics ( email )

Gower Street
London WC1E 6BT, WC1E 6BT
United Kingdom

University of California, Los Angeles - Department of Economics ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095-1361
United States

Toru Kitagawa

University College London

Gower Street
London, WC1E 6BT
United Kingdom

Matthew Read

University College London - Department of Economics ( email )

Drayton House, 30 Gordon Street
30 Gordon Street
London, WC1H 0AX
United Kingdom

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