Measuring international uncertainty using global vector autoregressions with drifting parameters

Michael Pfarrhofer

No 2019-3, Working Papers in Economics from University of Salzburg

Abstract: This paper investigates the time-varying impacts of international macroeconomic uncertainty shocks. We use a global vector autoregressive (GVAR) specification with drifting coefficients and factor stochastic volatility in the errors to model six economies jointly. The measure of uncertainty is constructed endogenously by estimating a scalar driving the innovation variances of the latent factors, and is included also in the mean of the process. To achieve regularization, we use Bayesian techniques for estimation, and introduce a set of hierarchical global local shrinkage priors. The adopted priors center the model on a constant parameter specification with homoscedastic errors, but allow for time-variation if suggested by likelihood information. Moreover, we assume coefficients across economies to be similar, but provide sufficient flexibility via the hierarchical prior for country-specific idiosyncrasies. The results point towards pronounced real and financial effects of uncertainty shocks in all countries, with differences across economies and over time.

Keywords: Bayesian global vector autoregressive model; state space modeling; hierarchical priors; factor stochastic volatility; stochastic volatility in mean (search for similar items in EconPapers)
JEL-codes: C11 C55 E32 E66 G15 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2019-08-19
New Economics Papers: this item is included in nep-ets, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Measuring International Uncertainty Using Global Vector Autoregressions with Drifting Parameters (2023)
Working Paper: Measuring international uncertainty using global vector autoregressions with drifting parameters (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:ris:sbgwpe:2019_003

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