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A regression tree algorithm for the identification of convergence clubs

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  • Postiglione, Paolo
  • Benedetti, Roberto
  • Lafratta, Giovanni

Abstract

The concept of convergence clubs is analyzed and compared with classical methods for the study of economic [beta]-convergence, which often consider the entire data set as one sample. A technique for the identification of convergence clubs is proposed. The algorithm is based on a modified version of the usual regression trees procedure. The objective function of the method is represented by the difference among the parameters of the model under investigation. Different strategies are adopted in the definition of the model used in the objective function of the algorithm. The first is the classical non-spatial [beta]-convergence model. The others are modified [beta]-convergence models which take into account the dependence showed by spatially distributed data. The proposed procedure identifies situation of local stationarity in the economic growth of the different regions: a group of regions is divided into two sub-groups if the parameter estimates are significantly different among them. The algorithm is applied to 191 European regions for the period 1980-2002. Given the adaptability of the algorithm, its implementation provides a flexible tool for the use of any regression model in the analysis of non-stationary spatial data.

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  • Postiglione, Paolo & Benedetti, Roberto & Lafratta, Giovanni, 2010. "A regression tree algorithm for the identification of convergence clubs," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2776-2785, November.
    • Handle: RePEc:eee:csdana:v:54:y:2010:i:11:p:2776-2785
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    Cited by:

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    2. Konrad Lyncker & Rasmus Thoennessen, 2017. "Regional club convergence in the EU: evidence from a panel data analysis," Empirical Economics, Springer, vol. 52(2), pages 525-553, March.
    3. Vidoli, Francesco & Pignataro, Giacomo & Benedetti, Roberto, 2022. "Identification of spatial regimes of the production function of Italian hospitals through spatially constrained cluster-wise regression," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
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    5. M. Simona Andreano & Roberto Benedetti & Andrea Mazzitelli & Federica Piersimoni, 2018. "Spatial autocorrelation and clusters in modelling corporate bankruptcy of manufacturing firms," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 45(4), pages 475-491, December.
    6. Andreano, M. Simona & Laureti, Lucio & Postiglione, Paolo, 2013. "Economic growth in MENA countries: Is there convergence of per-capita GDPs?," Journal of Policy Modeling, Elsevier, vol. 35(4), pages 669-683.
    7. Diego Aboal & Bibiana Lanzilotta & Martin Pereyra & Maria Paz Queraltó, 2020. "Regional Economic Development and Convergence Clubs in Uruguay," Documentos de Trabajo 17902, The Latin American and Caribbean Economic Association (LACEA).
    8. Domenica Panzera & Paolo Postiglione, 2014. "Economic growth in Italian NUTS 3 provinces," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 273-293, August.
    9. Michael Cary, 2019. "Increasing Access to Clean Fuels and Clean Technologies: A Club Convergence Approach," Clean Technol., MDPI, vol. 1(1), pages 1-18, September.
    10. Gianfranco Piras & Paolo Postiglione & Patricio Aroca, 2012. "Specialization, R&D and productivity growth: evidence from EU regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 49(1), pages 35-51, August.
    11. Alfredo Cartone & Paolo Postiglione, 2016. "Modelli spaziali di regressione quantilica per l?analisi della convergenza economica regionale," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2016(3), pages 28-48.
    12. Luc Anselin & Pedro Amaral, 2024. "Endogenous spatial regimes," Journal of Geographical Systems, Springer, vol. 26(2), pages 209-234, April.
    13. Cartone, Alfredo & Díaz-Dapena, Alberto & Langarita, Raquel & Rubiera-Morollón, Fernando, 2021. "Where the city lights shine? Measuring the effect of sprawl on electricity consumption in Spain," Land Use Policy, Elsevier, vol. 105(C).
    14. Philipp Piribauer, 2016. "Heterogeneity in spatial growth clusters," Empirical Economics, Springer, vol. 51(2), pages 659-680, September.
    15. María Candelaria Barrios‐González & Ana María García‐Pérez & Vanessa Yanes‐Estévez, 2024. "Cooperative employment in the regions of Spain (1999–2019): The convergence clubs," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 95(2), pages 305-325, June.
    16. M. Simona Andreano & Roberto Benedetti & Paolo Postiglione, 2017. "Spatial regimes in regional European growth: an iterated spatially weighted regression approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(6), pages 2665-2684, November.
    17. Paolo Postiglione & Maria Simona Andreano & Roberto Benedetti, 2017. "Spatial Clusters in EU Productivity Growth," Growth and Change, Wiley Blackwell, vol. 48(1), pages 40-60, March.

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