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Economic growth in Italian NUTS 3 provinces

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  • Domenica Panzera
  • Paolo Postiglione
Abstract
This paper analyzes the conditional $$\beta $$ β -convergence hypothesis for NUTS 3 Italian provinces. A methodology for the simultaneous treatment of spatial dependence and spatial heterogeneity is developed. Spatial dependence is introduced in the economic model by assuming a spatial Durbin model specification. The absence of data experienced by some economic variables at the NUTS 3 level is addressed through a modified version of the Bayesian interpolation method introduced by Palma and Benedetti (J Geogr Syst 5:199–220, 1998 ). Spatial heterogeneity is taken into account by identifying convergence clubs. For this purpose, we use the modified simulated annealing algorithm introduced by Postiglione et al. (Comput Econ 42:151–174, 2013 ). The methodology is compared with the heteroscedastic approach proposed by Kelejian and Prucha (J Econom 157:53–67, 2010 ). Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • 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.
    • Handle: RePEc:spr:anresc:v:53:y:2014:i:1:p:273-293
    DOI: 10.1007/s00168-014-0628-y
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    Cited by:

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    3. Paolo Postiglione & Alfredo Cartone & Domenica Panzera, 2020. "Economic Convergence in EU NUTS 3 Regions: A Spatial Econometric Perspective," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    4. Alfredo Cartone & Domenica Panzera & Paolo Postiglione, 2022. "Regional economic disparities, spatial dependence and proximity structures," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(5), pages 1034-1050, October.
    5. Kounetas, Kostas & Napolitano, Oreste, 2018. "Modeling the incidence of international trade on Italian regional productive efficiency using a meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 71(C), pages 45-58.
    6. Kyriakos Drivas, 2021. "Which travels farther? Knowledge or rivalry?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(2), pages 299-333, October.
    7. M. Simona Andreano & Roberto Benedetti & Andrea Mazzitelli, 2016. "L?eterogeneit? spaziale nello sviluppo locale in Italia: un?analisi basata sulla costruzione di un indicatore sintetico," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2016(3), pages 9-27.
    8. Kilroy,Austin Francis Louis & Ganau,Roberto, 2020. "Economic Growth in European Union NUTS-3 Regions," Policy Research Working Paper Series 9494, The World Bank.
    9. Carlo Ciccarelli & Stefano Fachin, 2017. "Regional growth with spatial dependence: A case study on early Italian industrialization," Papers in Regional Science, Wiley Blackwell, vol. 96(4), pages 675-695, November.
    10. Pritam Ghosh & Alfredo Cartone, 2020. "A Spatio‐temporal analysis of COVID‐19 outbreak in Italy," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(6), pages 1047-1062, December.
    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. Mindaugas Butkus & Diana Cibulskiene & Alma Maciulyte-Sniukiene & Kristina Matuzeviciute, 2018. "What Is the Evolution of Convergence in the EU? Decomposing EU Disparities up to NUTS 3 Level," Sustainability, MDPI, vol. 10(5), pages 1-37, May.
    13. Cartone, Alfredo & Postiglione, Paolo & Hewings, Geoffrey J.D., 2021. "Does economic convergence hold? A spatial quantile analysis on European regions," Economic Modelling, Elsevier, vol. 95(C), pages 408-417.
    14. Alfredo Cartone & Paolo Postiglione, 2016. "Le componenti principali pesate geograficamente per la definizione di indicatori compositi locali," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2016(1), pages 33-52.
    15. Ganau, Roberto & Kilroy, Austin, 2023. "Detecting economic growth pathways in the EU’s lagging regions," LSE Research Online Documents on Economics 115162, London School of Economics and Political Science, LSE Library.

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    Keywords

    C15; C21; R12; R15;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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