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

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  • Canova, Fabio

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.

Suggested Citation

  • Canova, Fabio, 1999. "Testing for Convergence Clubs in Income per-capita: A Predictive Density Approach," CEPR Discussion Papers 2201, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:2201
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    References listed on IDEAS

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    More about this item

    Keywords

    Heterogeneities; Income Inequality; Panel Data; Predictive Density;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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