dc.contributor.author Canova, Fabio
dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
dc.date.accessioned 2012-07-11T02:07:21Z
dc.date.available 2012-07-11T02:07:21Z
dc.date.issued 2005-09-15T23:14:33Z
dc.identifier.uri http://hdl.handle.net/10230/487
dc.description.abstract The paper proposes a technique to jointly test for groupings of unknown size in the cross sectional dimension of a panel and estimates the parameters of each group, and applies it to identifying convergence clubs in income per-capita. The approach uses the predictive density of the data, conditional on the parameters of the model. The steady state distribution of European regional data clusters around four poles of attraction with different economic features. The distribution of income per-capita of OECD countries has two poles of attraction and each group has clearly identifiable economic characteristics.
dc.language.iso eng
dc.rights.uri Aquest document està subjecte a una llicència d'ús de Creative Commons, amb la qual es permet copiar, distribuir i comunicar públicament l'obra sempre que se'n citin l'autor original, la universitat i el departament i no se'n faci cap ús comercial ni obra derivada, tal com queda estipulat en la llicència d'ús (http://creativecommons.org/licenses/by-nc-nd/2.5/es/)
dc.subject.other Heterogeneities, panel data, predictive density, income inequality
dc.title Testing for Convergence Clubs in Income per-capita: A Predictive Density Approach
dc.type info:eu-repo/semantics/workingPaper
dc.date.modified 2012-07-10T07:27:29Z

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