Robust Bayesian inference in proxy SVARs

Kitagawa, Toru; Read, Matthew

doi:10.1016/j.jeconom.2021.02.003

Cited by 27 publications

(13 citation statements)

References 36 publications

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“…17 These restrictions are also considered in Braun and Brüggemann (forthcoming). In a similar vein, Ludvigson, Ma and Ng (2017), Piffer and Podstawski (2018), Arias, Rubio-Ramírez and Waggoner (2021), Caggiano and Castelnuovo (2021) and Giacomini, Kitagawa and Read (2022b) impose sign restrictions on the correlations between structural shocks and variables that are external to the VAR. 18 I write this restriction in terms of the covariance, but it is equivalent to a restriction on the correlation; to write the restriction in terms of the correlation, divide by  …”

Section: Restrictions On Relationship With a Proxy Variablementioning

confidence: 99%

Estimating the Effects of Monetary Policy in Australia Using Sign-restricted Structural Vector Autoregressions

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2023

RBA Research Discussion Papers

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Existing estimates of the macroeconomic effects of Australian monetary policy tend to be based on strong, potentially contentious, assumptions. I estimate these effects under weaker assumptions. Specifically, I estimate a structural vector autoregression identified using a variety of sign restrictions, including restrictions on impulse responses to a monetary policy shock, the monetary policy reaction function, and the relationship between the monetary policy shock and a proxy for this shock. I use an approach to Bayesian inference that accounts for the problem of posterior sensitivity to the choice of prior that arises in this setting, which turns out to be important. Some sets of identifying restrictions are not particularly informative about the effects of monetary policy. However, combining the restrictions allows us to draw some useful inferences. There is robust evidence that an increase in the cash rate lowers output and consumer prices at horizons beyond a year or so. The results are consistent with the macroeconomic effects of a 100 basis point increase in the cash rate lying towards the upper end of the range of existing estimates.

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Section: Restrictions On Relationship With a Proxy Variablementioning

confidence: 99%

Estimating the Effects of Monetary Policy in Australia Using Sign-restricted Structural Vector Autoregressions

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2023

RBA Research Discussion Papers

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“…When applying this approach in a set-identified SVAR, they focus on the impulse responses to standard deviation shocks as the parameters of interest. Giacomini, Kitagawa and Read (2022b) describe an algorithm for conducting robust Bayesian inference in proxy SVARs (i.e. SVARs identified using an external instrument) under the unit-effect normalisation.…”

Section: Related Literaturementioning

confidence: 99%

The Unit-effect Normalisation in Set-identified Structural Vector Autoregressions

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2022

RBA Research Discussion Papers

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Structural vector autoregressions that are set identified (e.g. with sign restrictions) are typically used to analyse the effects of standard deviation shocks. However, answering questions of economic interest often requires knowing the effects of a 'unit' shock. For example, central bankers want to answer questions like 'what are the effects of a 100 basis point increase in the policy rate?' The problem is that set-identifying restrictions do not always rule out the possibility that a variable does not react contemporaneously to its own shock. As a consequence, identified sets for the impulse responses to unit shocks may be unbounded, which implies that set-identifying restrictions may be extremely uninformative. Simply assuming that responses are non-zero turns out to be an arbitrary and unsatisfactory solution. I argue that it is therefore important to communicate about the extent to which the identified set may be unbounded, since this tells us about the informativeness of the identifying restrictions, and I develop tools to facilitate this. I explain how to draw useful posterior inferences about impulse responses when identified sets are unbounded with positive probability. I illustrate the empirical relevance of these issues by estimating the response of US output to a 100 basis point federal funds rate shock under different sets of identifying restrictions. Some restrictions are very uninformative about the effects of a 100 basis point shock. The output responses I obtain under a rich set of identifying restrictions lie towards the smaller end of the range of existing estimates.

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“…10 To be specific, consider introducing the external variables m t = (m 1t , m 2t , m 3t ) , each of which acts as a proxy for some contemporaneous structural shocks. Following Angelini and Fanelli (2019), Arias et al (2021), and Giacomini et al (2022), we augment m t into the original SVAR,…”

Section: Iii5 Proxy-svarmentioning

confidence: 99%