The international transmission of US shocks—Evidence from Bayesian global vector autoregressions

Feldkircher, Martin; Huber, Florian

doi:10.1016/j.euroecorev.2015.01.009

Cited by 144 publications

(124 citation statements)

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“…Indeed, a growing body of empirical research provides evidence that financial interlinkages play a critical role in the transmission of shocks across economies (Ehrmann and Fratzscher, 2003, 2005, 2009Ehrmann et al, 2011;Hale et al, 2016). Similarly, several studies document the sizable impact of-in particular USmonetary policy on output and inflation in the rest of the world that materialises through financial spillover channels (Kim, 2001;Canova, 2005;Nobili and Neri, 2006;Dedola et al, 2015;Feldkircher and Huber, 2015;Georgiadis, 2016). And related work even suggests that economies' financial markets are subject to a global financial cycle, which is argued to materialise in variations in global risk aversion and to be driven by US monetary policy (Bekaert et al, 2013;Ghosh et al, 2014;Bruno and Shin, 2015b,a;Miranda-Agrippino and Rey, 2015;Passari and Rey, 2015;Rey, 2015).…”

Section: Introductionmentioning

confidence: 99%

Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks

Georgiadis¹,

Jančoková²

2017

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Financial globalisation and spillovers have gained immense prominence over the last two decades. Yet, powerful cross-border financial spillover channels have not become a standard element of structural monetary models. Against this background, we hypothesise that New Keynesian DSGE models that do not feature powerful financial spillover channels confound the effects of domestic and foreign disturbances when confronted with the data. We derive predictions from this hypothesis and subject them to data on monetary policy shock estimates for 29 economies obtained from more than 280 monetary models in the literature. Consistent with the predictions from our hypothesis we find: Monetary policy shock estimates obtained from New Keynesian DSGE models that do not account for powerful financial spillover channels are contaminated by a common global component; the contamination is more severe for economies that are more susceptible to financial spillovers in the data; and the shock estimates imply implausibly similar estimates of the global output spillovers from monetary policy in the US and the euro area. None of these findings applies to monetary policy shock estimates obtained from VAR and other statistical models, financial market expectations and the narrative approach. JEL codes: F42, E52, C50

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Section: Introductionmentioning

confidence: 99%

Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks

Georgiadis¹,

Jančoková²

2017

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“…de Waal et al (2013) show that a richer GVAR 3 GVAR models have, for instance, been used to analyze the international transmission of oil price shocks (Cashin et al, 2014), house price shocks (Cesa-Bianchi, 2013), credit supply shocks (Eickmeier and Ng, 2015), cost-push shocks (Galesi and Lombardi, 2013), financial stress shocks (Dovern and van Roye, 2014), monetary policy shocks (Feldkircher and Huber, 2015), liquidity shocks during the Great Recession of -2009(Chudik and Fratzscher, 2011, and for stresstesting of the financial sector (Castrén et al, 2010). For a more complete overview, see Chudik and Pesaran (2014).…”

Section: Related Literaturementioning

confidence: 99%

“…appendix of Feldkircher and Huber (2015) for a sensitivity analysis with respect to the choice of weights.…”

Section: Prior Implementationmentioning

confidence: 99%

“…14 Alternatively one could introduce a set of dummy variables for the observations in question as in Crespo Cuaresma et al (2014a) or Feldkircher and Huber (2015). While this might improve the behavior of the country-models' residuals, it still poses the risk that outlier effects could be carried over to other country models via the trade-weighted foreign variables.…”

Section: Prior Implementationmentioning

confidence: 99%

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Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR

Dovern

Feldkircher

Huber

2016

Journal of Economic Dynamics and Control

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We analyze how modeling international dependencies improves forecasts for the global economy based on a Bayesian GVAR with SSVS prior and stochastic volatility. To analyze the source of performance gains, we decompose the predictive joint density into its marginals and a copula term capturing the dependence structure across countries. The GVAR outperforms forecasts based on country-specific models. This performance is solely driven by superior predictions for the dependence structure across countries, whereas the GVAR does not yield better predictive marginal densities. The relative performance gains of the GVAR model are particularly pronounced during volatile periods and for emerging economies.JEL classification: C53, E37, F47 Keywords: GVAR, global economy, forecast evaluation, log score, copula * Corresponding author: Florian Huber, Oesterreichische Nationalbank (OeNB), Phone: +43-1-404 20-5208. E-mail: florian.huber@oenb.at. We would like to thank Hans Manner and all participants of the AWI seminar as well as the OeNB seminar for helpful comments on earlier drafts of this paper. The opinions expressed in this paper are those of the authors and do not necessarily reflect the official viewpoint of the OeNB or of the Eurosystem.

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“…For example, the global VAR (GVAR) model developed by Pesaran et al (2004) has also been used to study the global effects of US monetary policy considering a large number of non-US spillover-receiving economies simultaneously (Chen et al, 2012;Feldkircher and Huber, 2015;Georgiadis, forthcoming). In a similar vein, Canova and Ciccarelli (2009) put forth high-dimensional multi-country VAR models, which they suggest to estimate by Bayesian methods.…”

Section: Introductionmentioning

confidence: 99%

To Bi, or not to Bi? Differences in Spillover Estimates from Bilateral and Multilateral Multi-country Models

Georgiadis

2015

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Asymptotic analysis and Monte Carlo simulations show that spillover estimates obtained from widely-used bilateral (such as two-country VAR) models are significantly less accurate than those obtained from multilateral (such as global VAR) models. In particular, the accuracy of spillover estimates obtained from bilateral models depends on two aspects of economies' integration with the rest of the world. First, accuracy worsens as direct bilateral transmission channels become less important, for example when the spillover-sender accounts only for a small share of the spillover-recipient's overall integration with the rest of the world. Second, accuracy worsens as indirect higher-order spillovers and spillbacks become more important, for example when the spillover-recipient is more integrated with the rest of the world overall. Empirical evidence on the global output spillovers from US monetary policy is consistent with these generic results: Spillover estimates obtained from two-country VAR models are systematically smaller than those obtained from a global VAR model; and the differences between spillover estimates obtained from two-country VAR models and a global VAR model are more pronounced for economies for which the US accounts for a smaller share of their overall trade and financial integration with the rest of the world, and for economies which are more integrated with the rest of the world overall. JEL codes: F44, C33

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The international transmission of US shocks—Evidence from Bayesian global vector autoregressions

Cited by 144 publications

References 30 publications

Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks

Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks

Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR

To Bi, or not to Bi? Differences in Spillover Estimates from Bilateral and Multilateral Multi-country Models

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