Testing for Convergence Clubs in Income per-capita: A Predictive Density Approach
AbstractThe 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.
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Bibliographic InfoPaper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 2201.
Date of creation: Aug 1999
Date of revision:
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Other versions of this item:
- Fabio Canova, 2004. "Testing for Convergence Clubs in Income Per Capita: A Predictive Density Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(1), pages 49-77, 02.
- Fabio Canova, 1997. "Testing for convergence clubs in income per-capita: A predictive density approach," Economics Working Papers 404, Department of Economics and Business, Universitat Pompeu Fabra, revised Jun 1999.
- Canova, Fabio, 2001. "Testing for convergence clubs in income per-capita : a predictive density approach," HWWA Discussion Papers 139, Hamburg Institute of International Economics (HWWA).
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- D90 - Microeconomics - - Intertemporal Choice - - - General
- O47 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Measurement of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
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