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About the article
Published Online: 2013-04-02
Published in Print: 2013-01-01
In particular, the euro area Finance Ministers noted in early-2010 that “competitiveness divergences and current-account imbalances increased steadily in pre-crisis years and have in most cases largely persisted throughout the crisis […] Given vulnerabilities and the magnitude of the adjustment required, the need for policy action is particularly pressing in Member States showing persistently large current-account deficits and large competitiveness losses” (Eurogroup conclusions on the surveillance of intra-euro area competitiveness and macroeconomic imbalances, Brussels, 15 March 2010).
European Commission (2008) and European Central Bank (2008) provide thorough surveys.
As to the former aspect, it is important to note that there is heterogeneity among euro area countries in terms of exposure to both overall non-euro area trade and to the various countries and regions outside the euro area.
For instance, for a VAR model with three lags, we have in our case 62 (number of variables) ×62×3=11532 parameters to estimate and only 12 (months) ×10 (years) ×62=7440 observations.
Arguably, the aggregated impact of non-neighbors could still be large, depending on the degree of cross-section dependence among the units. Such an aggregated impact is in general important when the cross-section dependence is strong [in the sense defined by Chudik, Pesaran, and Tosetti (2011)], in which case it is possible to control for it by using cross-section averages, an idea originally introduced by Pesaran (2006) in the context of the estimation of large heterogenous panels with a multi-factor error structure.
Changes in risk aversion and appetite are regarded as important drivers of foreign exchange markets, not only when it comes to emerging market economies but also, more recently, to advanced economies [e.g., McCauley and McGuire (2009), Adrian, Etula, and Shin (2010)]. For a recent discussion of risk aversion shocks, see also Popescu and Smets (2010).
As to price competitiveness specifically, this study finds that differences appear to have stemmed mainly from higher increases in labor costs in external deficit countries relative to those with external surpluses. In turn, these heterogeneous developments in labor costs mirror heterogeneous developments in tax wedges (i.e., direct taxes and social security contributions). According to this report, slow productivity growth also played a role in some countries, reflecting resource reallocations from traded to non-traded sectors. In addition to this, the report finds that some elements of non-price competitiveness also appear to explain heterogeneous developments in external competitiveness across euro countries in the first 10 years of EMU. These elements include technological innovation (R&D), labor force characteristics (e.g., skills), product market regulations and business environment factors (e.g., procedures for enforcing contracts).
These results are not reported due to space considerations. Even in longer time spans of data, it is common to find unit roots in real effective exchange rates [see e.g., Pesaran, Schuermann, and Weiner (2004)], although for very long periods – such as centuries – there is some evidence of mean reversion, see for instance Taylor, Peel, and Sarno (2001). Such very long datasets are only available for a handful of currencies, however.
On the one hand, specifying a relatively parsimonious model often yields strong estimation results, but at the expense of omission bias of key variables if the model is too simple. On the other hand, a more complex model allows for a richer representation of the interactions between variables, but at the expense of estimation precision, due to the loss in degrees of freedom.
Overal, our set of neighbors is
It is difficult to establish long-run relations for real exchange rates in such a short time span (one decade), as documented by an extensive literature on the relative version of the purchasing power parity.
Our main data source for the real effective exchange rates in our sample is the IMF IFS database, which does not disclose details on the composition of their currency baskets and which might also change over time.
Identifying economic shocks is arguably a traditional challenge in the literature due to, e.g., the potential existence of different competing structural models underlying such shocks, or to the difficulty to identify their geographic origin. As to the latter, it is reasonable indeed to assume that different structural shocks, say productivity and monetary policy shocks, are uncorrelated within a closed economy, but not when other economies are considered in the analysis. This therefore makes it even more difficult to identify such shocks in a large system. For a related discussion, see Dees et al. (2010).
See Chudik and Pesaran (2011) for further details on the analysis of systems featuring a dominant unit.
In particular, the exceptional rise in volatility in the US dollar, euro and yen during the 2007/09 global crisis, has been largely ascribed to an unprecedented rise in risk aversion which triggered a massive flight to the safety and liquidity of US dollar-denominated assets and confounded previous scenarios of disorderly unwinding of global imbalances.
Identification with sign restrictions is referred to as “weak” here in the sense that a variety of structural models could satisfy the selected signs.
We also used alternative sets of restrictions to identify risk shocks, which did not change our main findings qualitatively.
For shocks to risk aversion, we follow the literature in summarizing the available information in multiple structural models by reporting median and quantiles of impulse responses obtained through bootstrap replications. It should be highlighted, however, that the median itself is not an impulse response function per se (and generally does not belong to the space of impulse responses). In the same spirit, quantiles cannot be interpreted as confidence intervals in this case and, for the same reason, measures of euclidian distance cannot be calculated.
To ensure comparability between the two estimation periods, we only include in our sample those countries which were members of the euro area from the outset in 1999 (i.e., Austria, Belgium, Finland, France, Germany, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain) and Greece, which joined relatively early on (namely in 2001). We therefore discard those new EU Member States which joined later (after 2004), including Slovenia, Slovakia, Malta, Cyprus and Estonia.
Prior to EMU, a large part of the volatility in the relative evolution of REERs across European economies occurred between the late 1980s and the mid-1990s.
Over the two decades we consider, some of the countries in our sample have indeed experienced well-known devaluations, exchange rate regime changes and other large country-specific shock (such as Germany’s unification).
Corresponding to an appreciation of the US dollar, Japanese yen and Swiss franc of 0.5%, 1.5% and 1.2%, respectively; a depreciation of the Korean won and Polish zloty of –3.1% and –3.0%, respectively; and an increase in the VIX of 10%.
Corresponding to an appreciation of the US dollar, Japanese yen and Swiss franc of 1.2%, 2.2% and 1.2%, respectively; a depreciation of the Korean won and Polish zloty of –2.4% and –2.2%, respectively; and an increase in the VIX of 20%.
This seemed notably the case in the 2007/9 crisis, in particular at times of heightened uncertainty and flight to the safety and liquidity of US dollar assets [see e.g., McCauley and McGuire (2009)].
Such a view is most candidly expressed by a column of M. Wolf, the Financial Times’ Chief Economics commentator, written in late-2010 (Wolf 2010): “The euro has also shielded the German economy from what would have been still bigger shocks: imagine what would have happened, in the absence of the euro. The exchange rate of the German mark would have exploded upwards, as currency crises savaged the European economy, as happened in the 1990s. In peripheral Europe, currency depreciations would have been at least as big as, if not bigger than, sterling’s. The absence of such shocks has greatly enhanced the prospects for the German recovery. The creation of the eurozone was, for this reason alone, much more than a favour Germany did for its partners. It was also a big economic (not to mention political) gain for Germany. German industrialists are clear on this, as is the government.”