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Erschienen in: Empirical Economics 4/2020

14.09.2018

Understanding post-Crisis price deviations in Europe: Disintegration or mere adjustment?

verfasst von: Marina Glushenkova, Marios Zachariadis

Erschienen in: Empirical Economics | Ausgabe 4/2020

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Abstract

The paper investigates the process of European integration using law of one price (LOP) deviations for a large number of individual goods and services during the recent Crisis. We find that the degree of integration of Eurozone economies continued to increase during this period. Importantly, we trace the location of individual goods in the distribution of LOP deviations so as to understand how price advantage or disadvantage has evolved or persisted during the Crisis. We find that rigidities rendering prices in some markets higher persisted during the same period. Thus, while well-deserved policy emphasis has been placed by the Eurozone on correcting fiscal imbalances and on monetary policy to address the resulting deflationary bias, our work suggests that little has been done in practice to break structural rigidities in goods and services markets during the period under study. Finally, comparing the distributions of LOP deviations for each of the Eurozone economies, we show that to the extent that there was adjustment for some of these economies this did not occur via the same channels for all Eurozone countries, suggesting different non-tradeables and tradeables adjustment mechanisms being in place in different countries.

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Fußnoten
1
Rigidities could also arise due to transactions costs in international arbitrage due to market frictions (Dixit 1989; Krugman 1989), or costs associated with preferences and technology (O’Connell and Wei 2002), and constraints due to laws, regulations and institutions (e.g., Brock and Hommes 1997).
 
2
Defined as in Glushenkova and Zachariadis (2016) as the percentage of goods which remain on the same side of the distribution (in this case, above zero thus more expensive) for the pair of years being compared in each case.
 
3
The importance of traded and non-traded inputs has been emphasized, for example, by Parsley and Wei (2007, 2008), Faber and Stockman (2009), Lee and Shin (2010), and Lee (2010).
 
5
We do not present these wage deviations in a Table here to save space but this is available upon request.
 
6
As pointed by Ruppert (1987) kurtosis is a measure of both peakedness and tail weight, with higher kurtosis values indicating peakedness and fatter tails of the distribution, while lower kurtosis values indicate flatness and thinner tails. Kurtosis can be poorly informative about the change of the degree of integration over time to the extent that the comparison might involve distributions with very different tail characteristics, so it would not be clear whether high kurtosis values are associated with peakedness or fat tails for both distributions, or with peakedness for one distribution and fat tails for another distribution.
 
7
We note that when we eliminate outliers by restricting the tails of the distributions with the support ranging from − 1.5 to 1.5 so that fat tails are no longer an issue, kurtosis values for the EZ 19 increase, for example, from 4.762 in 2005 to 4.895 in 2014 for tradeables (not shown in Table 3 nor reflected in Fig. 2).
 
8
That kurtosis values are greater in 2014 as compared to 2005 for the first four countries, is in this case due to fatter tails in 2014 as compared to 2005.
 
9
Income is plausibly closely associated with the non-traded component in a basic retail price model as in Crucini et al. (2005) where each good is produced by a traded input combined with a non-traded one. In our current application, we focus on the traded component so that our results are not driven by the documented close link between income and prices.
 
10
We thank an anonymous referee of this journal for pointing this out. Results from this exercise are available upon request.
 
11
More specifically, our results show that for the vast majority of rich countries in our sample (such as Austria, Belgium, Denmark, France, Germany, Ireland, Luxembourg, the Netherlands, Sweden, Switzerland, and the UK) the percentage of non-traded goods that were more expensive for any pair of years is higher than the respective share of traded goods. Moreover, for relatively poorer countries in our sample (such as Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia, Slovenia, and Turkey) the percentage of non-traded goods that were cheaper for any pair of years is higher than the respective share of traded goods.
 
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Metadaten
Titel
Understanding post-Crisis price deviations in Europe: Disintegration or mere adjustment?
verfasst von
Marina Glushenkova
Marios Zachariadis
Publikationsdatum
14.09.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Empirical Economics / Ausgabe 4/2020
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI
https://doi.org/10.1007/s00181-018-1565-x

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