Follow us
Publications Commentary Research People Events News Resources and Videos About IFS
Home Publications Robust Bayesian inference in proxy SVARs

Robust Bayesian inference in proxy SVARs

Cemmap Working Paper CWP13/20

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 con-troversial 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.

More on this topic

Cemmap Working Paper CWP09/22
We compare two approaches to using information about the signs of structural shocks at specific dates within a structural vector autoregression (SVAR): imposing ‘narrative restrictions’ (NR) on the shock signs in an otherwise set-identified SVAR; and casting the information about the shock ...
Cemmap Working Paper CWP07/22
Economists are obsessed with rankings of institutions, journals, or scholars according to the value of some feature of interest.
Cemmap Working Paper CWP05/22
We designed a coaching program that focused on one aspect of teacher quality—teacher-child interactions—that researchers in education and psychology have argued is critical for child development and learning.
Cemmap Working Paper CWP04/22
It is often desired to rank different populations according to the value of some feature of each population. For example, it may be desired to rank neighbourhoods according to some measure of intergenerational mobility or countries according to some measure of academic achievement.
Cemmap Working Paper CWP44/21
We study a dynamic ordered logit model for panel data with fixed effects.