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Food inflation in the European Union: Distribution analysis and spatial effects

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dc.contributor.author Liontakis, A en
dc.contributor.author Kremmydas, D en
dc.date.accessioned 2014-06-06T06:53:03Z
dc.date.available 2014-06-06T06:53:03Z
dc.date.issued 2014 en
dc.identifier.issn 15384632 en
dc.identifier.uri http://dx.doi.org/10.1111/gean.12033 en
dc.identifier.uri http://62.217.125.90/xmlui/handle/123456789/6330
dc.subject.other autocorrelation en
dc.subject.other economic integration en
dc.subject.other empirical analysis en
dc.subject.other European Union en
dc.subject.other food market en
dc.subject.other inflation en
dc.subject.other macroeconomics en
dc.subject.other Europe en
dc.title Food inflation in the European Union: Distribution analysis and spatial effects en
heal.type journalArticle en
heal.identifier.primary 10.1111/gean.12033 en
heal.publicationDate 2014 en
heal.abstract In the European Union (EU), homogenous inflation forces are expected to prevail because of increased economic integration, especially after the creation of a single currency area. This expectation is directly related to the issue of inflation convergence, which has gained increasing attention by both academics and policy makers in Europe. Although the examination of core inflation is of great importance for macroeconomic policy, the role of disaggregate inflation indices, and especially food inflation, has also been emphasized in the literature. However, the issue of food inflation convergence has been largely ignored to date in empirical studies. This study explores the evolving distribution of food inflation rates in the EU-25 member states using distribution dynamics analysis and covering the period from January 1997 to March 2011. This analysis assumes that each country represents an independent observation, providing unique information that can be used to estimate the transition dynamics of inflation. We show that spatial autocorrelation prevails inside the EU-25, and, therefore, the independency assumption is violated. To ensure spatial independence, the Getis spatial filter is implemented prior to a distribution dynamics analysis. The results of this analysis confirm the existence of convergence trends, which are even clearer after the spatial filtering procedure, indicating, on the one hand, the influence of spatial effects on food inflation and, on the other hand, the effectiveness of the Getis spatial filtering technique. © 2014 The Ohio State University. en
heal.publisher Blackwell Publishing Inc. en
heal.journalName Geographical Analysis en
dc.identifier.issue 2 en
dc.identifier.volume 46 en
dc.identifier.doi 10.1111/gean.12033 en
dc.identifier.spage 148 en
dc.identifier.epage 164 en


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