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Proxy Vector Autoregressions in a Data-rich Environment

Martin Bruns

Journal of Economic Dynamics and Control, 2021, vol. 123, issue C

Abstract: I propose a Bayesian approach to identify vector autoregressive (VAR) models via proxies in a data-rich environment. The setup augments a small-scale VAR model with latent factors. It allows to trace out the responses of disaggregated series in a unified model while controlling for broad economic conditions. The posterior sampler accounts for the estimation uncertainty in these latent factors as well as the measurement precision of the proxy. In a first application to monetary policy, I extract factors from a wide range of real and financial series and find that the effects of monetary policy shocks vary along the yield curve. In a second application to oil market shocks I add disaggregated US series to a standard model of the global oil market. I find that negative news about future oil supply have adverse effects on the US economy.

Keywords: Factor-augmented VAR; External instruments; Structural VAR; Monetary policy; Oil market shocks (search for similar items in EconPapers)
JEL-codes: C38 E60 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:123:y:2021:i:c:s0165188920302141

DOI: 10.1016/j.jedc.2020.104046

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Journal of Economic Dynamics and Control is currently edited by J. Bullard, C. Chiarella, H. Dawid, C. H. Hommes, P. Klein and C. Otrok

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