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Testing for Convergence Clubs in Income per-capita: A Predictive Density Approach

Fabio Canova ()

No 2201, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: The paper proposes a technique to test jointly for groupings of unknown size in the cross-sectional dimension of a panel and estimates the parameters of each group, applying 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-cpaita of OECD countries has two poles of attraction and each group has clearly identifiable economic characteristics.

Keywords: Heterogeneities; Income Inequality; Panel Data; Predictive Density (search for similar items in EconPapers)
JEL-codes: C11 D90 O47 (search for similar items in EconPapers)
Date: 1999-08
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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 (2001) Downloads
Working Paper: Testing for convergence clubs in income per-capita: A predictive density approach (1999) Downloads
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