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Geographical Distribution of Unemployment: An Analysis of Provincial Differences in Italy

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  • Maria Francesca Cracolici

    ()
    (University of Palermo)

  • Miranda Cuffaro

    ()
    (University of Palermo)

  • Peter Nijkamp

    ()
    (VU University, Amsterdam)

Abstract

Unemployment rates appear to vary widely at a subregional (e.g., local or provincial) level. Using spatial econometric models for spatial autocorrelation, this paper focuses attention on the spatial structure of regional unemployment disparities of Italian provinces. On the basis of findings from the economic literature and of the available socio-economic data, various model specifications including different explanatory variables are tested to investigate the geographical distribution of unemployment in the 103 provinces of Italy for the years 1998 and 2003. The results suggest that there is a clear explanation of unemployment differentials in terms of spatial equilibrium and disequilibrium factors and a significant degree of spatial dependence among labour markets at the provincial level in Italy. Provinces marked by high unemployment, as well as those characterized by low unemployment, tend to be spatially clustered, demonstrating the presence of unemployment ‘persistency’ in space and time regimes.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 07-065/3.

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Date of creation: 28 Aug 2007
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Handle: RePEc:dgr:uvatin:20070065

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Keywords: unemployment; spatial lag model; spatial autocorrelation; Italian provinces;

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Citations

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Cited by:
  1. R. Patuelli & N. Schanne & D. A. Griffith & P. Nijkamp, 2011. "Persistence of Regional Unemployment: Application of a Spatial Filtering Approach to Local Labour Markets in Germany," Working Papers wp743, Dipartimento Scienze Economiche, Universita' di Bologna.
  2. Demidova, Olga, 2014. "Spatial-autoregressive model for the two groups of related regions (eastern and western parts of Russia)," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 34(2), pages 19-35.
  3. Agovino, Massimiliano, 2013. "Do “good neighbors” enhance regional performances in including disabled people in the labour market? A spatial Markov chain approach," MPRA Paper 47038, University Library of Munich, Germany.
  4. Cristiano Perugini & Marcello Signorelli, 2010. "Youth labour market performance in European regions," Economic Change and Restructuring, Springer, vol. 43(2), pages 151-185, May.
  5. Ciżkowicz, Piotr & Kowalczuk, Michał & Rzońca, Andrzej, 2014. "Heterogeneous determinants of local unemployment in Poland," MPRA Paper 56858, University Library of Munich, Germany.
  6. Michelle Gilmartin & Dimitris Korobilis, 2012. "On Regional Unemployment: An Empirical Examination of the Determinants of Geographical Differentials in the UK," Scottish Journal of Political Economy, Scottish Economic Society, vol. 59(2), pages 179-195, 05.
  7. Roberto Patuelli & Daniel A. Griffith & Michael Tiefelsdorf & Peter Nijkamp, 2009. "Spatial Filtering and Eigenvector Stability: Space-Time Models for German Unemployment Data," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 0902, USI Università della Svizzera italiana.
  8. Maria Cracolici & Miranda Cuffaro & Peter Nijkamp, 2009. "A spatial analysis on Italian unemployment differences," Statistical Methods and Applications, Springer, vol. 18(2), pages 275-291, July.
  9. Ana Maria DIAZ ESCOBAR, 2011. "Spatial Unemployment Differentials in Colombia," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2011014, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  10. César Augusto MERCHÁN HERNÁNDEZ, 2014. "Desempleo y ocupación en las ciudades colombianas. Un ejercicio con datos panel," ARCHIVOS DE ECONOMÍA 011212, DEPARTAMENTO NACIONAL DE PLANEACIÓN.

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