2016
DOI: 10.1016/j.jimonfin.2015.06.010
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Determinants of global spillovers from US monetary policy

Abstract: Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in… Show more

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Cited by 262 publications
(173 citation statements)
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References 61 publications
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“…For the US we fix ϑ us = 0.2 and w us,j = 0.5, reflecting our assumption of the US being the core economy. The dynamics of domestic and foreign variables in response to monetary policy shocks under the two polar parameterisations are qualitatively plausible and-in particular for the "financial spillovers" parametrisation-consistent with the findings on monetary policy spillovers in the empirical literature (see Figures 7 and 8 in Appendix C.2 as well as Dedola et al, 2015;Feldkircher and Huber, 2015;Banerjee et al, 2016;Chen et al, 2016;Georgiadis, 2016). Figure 1 presents the distribution of the cross-country correlations between the monetary policy shock estimates for the non-core economies of the euro area and Japan obtained from feeding the data simulated from the multi-country data-generating process into the corresponding single-country versions across the 1,000 replications of the Monte Carlo experiment.…”
Section: The Data-generating Processsupporting
confidence: 83%
See 1 more Smart Citation
“…For the US we fix ϑ us = 0.2 and w us,j = 0.5, reflecting our assumption of the US being the core economy. The dynamics of domestic and foreign variables in response to monetary policy shocks under the two polar parameterisations are qualitatively plausible and-in particular for the "financial spillovers" parametrisation-consistent with the findings on monetary policy spillovers in the empirical literature (see Figures 7 and 8 in Appendix C.2 as well as Dedola et al, 2015;Feldkircher and Huber, 2015;Banerjee et al, 2016;Chen et al, 2016;Georgiadis, 2016). Figure 1 presents the distribution of the cross-country correlations between the monetary policy shock estimates for the non-core economies of the euro area and Japan obtained from feeding the data simulated from the multi-country data-generating process into the corresponding single-country versions across the 1,000 replications of the Monte Carlo experiment.…”
Section: The Data-generating Processsupporting
confidence: 83%
“…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%
“…In some cases, the sign is different than what would be expected. This result is consistent with that of Burriel and Galesi (2015) and Georgiadis (2015). These authors attribute the higher pass through of monetary policy in these countries to better bank capitalization and better institutions, as shown in higher spots on rankings like ease of doing business.…”
Section: Effects Of Conventional Monetary Policysupporting
confidence: 91%
“…Source: World Development Indicators, Author calculations Note: Cyclically components are computed using the filter developed by Baxter and King (1999) We run another regression by introducing interaction terms between landlocked situation and trade with in order to investigate the role of non-linearities similarly to Georgiadis (2015). Table 2 reports the results.…”
Section: Figure 5 Headline and Cyclically Adjusted Balancementioning
confidence: 99%