Examining asymmetries in the transmission of monetary policy in the euro area: Evidence from a mixed cross-section global VAR model

Georgiadis, Georgios

doi:10.1016/j.euroecorev.2014.12.007

Cited by 120 publications

(97 citation statements)

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“…PVAR impulse responses show a stronger euro area monetary policy impact on the Baltic economies than in the case of Lithuanian VAR. This outcome is not too surprising, as the results in other (although few) studies such as Georgiadis (2015) and Errit and Uusküla (2014) suggest that the Baltic region's response to a monetary policy shock can be quite significant.…”

Section: Introductionmentioning

confidence: 73%

“…24. Georgiadis (2015) points to differences in the industry mix as one of the main factors in explaining asymmetries in monetary policy transmission: economies with larger share of aggregate output accounted for by manufacturing and construction, all else being equal, exhibit larger declines in GDP in case of monetary tightening. Note that the manufacturing share in Lithuania is the largest among the three Baltic states (Figure 8), hence, the industry structure does not indicate that responses to monetary policy shock in Lithuania should be smaller than in other Baltic countries.…”

Section: Notesmentioning

confidence: 99%

“…Therefore, the analysis within the framework of an individual country is as important as within the framework of the whole euro area. Indeed, a number of studies show that there is heterogeneity across the transmission mechanisms in different countries, including countries within the euro area (Georgiadis, 2015;Peersman & Smets, 2001).…”

Section: Introductionmentioning

confidence: 99%

“…However, the latter might also be another reason to use VARs, since more theory-based models might not be well-represented for the Lithuanian economy, which in recent decades underwent big economic transformations. In the recent monetary policy literature, VAR models were refined allowing for time variation (Primiceri, 2005), identification by sign restrictions (Uhlig, 2005) or global interaction (Georgiadis, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…To the best of our knowledge, the preferred modelling choice in the literature is a specification in levels, which allows to estimate cointegrating relations. However, during the period under analysis, the Lithuanian economy experienced significant changes, caused by various internal and external factors, which make it very challenging to obtain reliable estimates for the specification in levels (the same argumentation can be found in (Georgiadis, 2015), who opts for specification in differences). 17 On the other hand, the EA data have a relatively long time series, which has been used and tested in many studies concerning monetary policy transmission.…”

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confidence: 96%

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Monetary policy transmission: the case of Lithuania

Stakénas

Stasiukynaite

2016

Baltic Journal of Economics

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We study the effect of a (standard) monetary policy shock in the euro area on the Lithuanian economy. We employ a structural vector autoregressive model incorporating variables from both the euro area and Lithuania. The model exhibits a block exogenous structure to account for the fact that Lithuania is a small economy. In general, we find that a monetary policy shock in the euro area has a stronger effect on the Lithuanian than it does on the euro area economy, though the effects are not statistically significant, preventing firm conclusions. We further broaden our analysis employing a panel vector autoregression (PVAR) model for the three Baltic states. PVAR model results suggest a stronger impact of monetary policy than that estimated using the Lithuanian model and a quite considerable degree of variation over time in the strength of monetary policy transmission. ARTICLE HISTORY

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Section: Introductionmentioning

confidence: 73%

Section: Notesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 96%

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Monetary policy transmission: the case of Lithuania

Stakénas

Stasiukynaite

2016

Baltic Journal of Economics

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The effects of shocks to interest rate expectations in the euro area: Estimates at the country level

Mandler

Scharnagl

2023

Journal of Forecasting

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We estimate the effects of shocks to interest rate expectations on the four largest euro area economies. We identify these shocks in a Bayesian vector autoregressive (BVAR) model augmented by survey expectations. We separate the expectations shocks from standard monetary policy shocks by assuming that they do not affect the current policy rate. Our sign restrictions also ensure that these shocks do not contain central bank information shocks. We find that an expected decline in the future short-term rate leads to an increase in output and prices. The increases do not become larger for changes to interest rate expectations further in the future, that is, we do not find evidence of a forward guidance puzzle. Using the multicountry structure of our model, we test for cross-country differences in the shocks' effects and find output and price effects to be greatest in Germany. We also compare the effects of shocks to interest rate expectations to those of standard monetary policy shocks and show the first type to affect output and prices more strongly in Germany and France.

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Spillover effects of credit default risk in the euro area and the effects on the Euro: A GVAR approach

Bettendorf

2018

Int. J Fin Econ

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During the 2008 financial crisis, increasing risk and spillovers became a main concern for policy makers and banks. In addition, changes in sovereign and bank risk are believed to have had strong effects on world‐wide exchange rates. This paper aims to analyse these dynamics empirically. We estimate a Global VAR (GVAR) model for nine EMU countries plus Japan, the United Kingdom, and the United States and identify structural risk shocks using sign restrictions. Our results indicate that spillover effects of general risk are much stronger than those of bailouts. Furthermore, we demonstrate that the Euro depreciates significantly against the Yen and U.S. dollar following general risk shocks in the euro area and only to a small extent following bailout shocks. The Pound Sterling is not affected by any of these shocks. The Euro variability is, from the EMU perspective, mainly driven by shocks stemming from large countries (e.g., Germany, France, and Italy). However, shocks from third countries also play an important role.

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Examining asymmetries in the transmission of monetary policy in the euro area: Evidence from a mixed cross-section global VAR model

Cited by 120 publications

References 50 publications

Monetary policy transmission: the case of Lithuania

Monetary policy transmission: the case of Lithuania

The effects of shocks to interest rate expectations in the euro area: Estimates at the country level

Spillover effects of credit default risk in the euro area and the effects on the Euro: A GVAR approach

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