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Testing for convergence clubs in income per-capita: A predictive density approach

Fabio Canova ()

No 139, HWWA Discussion Papers from Hamburg Institute of International Economics (HWWA)

Abstract: The paper proposes a technique to jointly tests 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 economics characteristics.

Keywords: Heterogeneities; Panel Data; Predictive Density; Income Inequality (search for similar items in EconPapers)
JEL-codes: O47 C11 D90 (search for similar items in EconPapers)
Date: 2001
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https://www.econstor.eu/bitstream/10419/19412/1/139.pdf (application/pdf)

Related works:
Journal Article: Testing for Convergence Clubs in Income Per Capita: A Predictive Density Approach (2004) Downloads
Working Paper: Testing for Convergence Clubs in Income Per-Capita: A Predictive Density Approach (2001) Downloads
Working Paper: Testing for Convergence Clubs in Income per-capita: A Predictive Density Approach (1999) Downloads
Working Paper: Testing for convergence clubs in income per-capita: A predictive density approach (1999) Downloads
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