Understanding Post‐Euro Law‐of‐One‐Price Deviations

Abstract

We put together a unique panel of thousands of good‐level prices before and after the euro to compare the determinants and understand the evolution of goods price dispersion across Europe over time. We find that tradeability and nontraded inputs play a significantly smaller role for cross‐country price dispersion after the adoption of the euro, and for Eurozone economies as compared to European Union ones. We then compare the distributions of law‐of‐one‐price (LOP) deviations over time to understand how the degree of integration across European economies changed after the euro. Our tests reveal that the distributions after the euro are typically significantly different from those before, consistent with a greater degree of integration. Utilizing our unique panel data set to trace the location of individual goods in the distribution of LOP deviations, we ask how the price advantage or disadvantage evident in these price distributions evolves over time, and whether goods characteristics play a role for the persistence of these LOP deviations. LOP deviations for these goods are highly correlated over 5‐ or 10‐ year horizons, and correlations remain significantly high over longer horizons. These correlations are greater for homogeneous as compared to differentiated goods and vary across countries. Finally, for most of these European economies and goods, price advantage is typically revealed to be more persistent than price disadvantage.

How different are Monetary Unions to national economies according to prices?

“…The second and third rows respectively report the ratio of the time component and of the locationand-good component to the total variance in LOOP deviations implied by equation (5). In the remaining rows, we decompose the location-and-good component into sub-components as in equations ( 6) and (7) and present the ratio of these sub-components to the total variance in LOOP deviations consistent with equation (8). Due to missing observations the sum of components is not always equal to 100%.…”

Explaining time variation in geographic price dispersion

“…Canada and show that retail prices do not respond to changes in wholesale costs in neighboring stores located across the border. Glushenkova and Zachariadis (2016) compare the explanatory power of tradeability and non-traded inputs before and after the adoption of the euro to study the evolution of European price dispersion. 1 Focusing on international price dynamics, Crucini and Shintani (2008), Klenow and Malin (2010), Crucini et al (2010), Burstein and Jaimovich (2012), and Andrade and Zachariadis (2016) use product-level price data to study time-series persistence and volatility in real exchange rates.…”

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

“…In the case of the distributions for 2005, higher kurtosis values are associated with fatter tails rather than higher peakedness 6 in 2005 as compared to 2014, so we cannot infer that the degree of integration was lower in 2014 as compared to 2005 based on the kurtosis values reported inTable 3. In fact, the higher peakedness of the distributions for 2014 as compared to 2005 for both tradeables and non-tradeables is evident inFigures 1 and 2 7. Next, we present the density functions for each of the 19 EZ economies and the UK inFigures 3 and 4.…”

“…Defined as inGlushenkova 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 Wei (2007, 2008),Faber and Stockman (2009),Lee and Shin (2010), and Lee (2010).…”