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On Regional Unemployment: An Empirical Examination of the Determinants of Geographical Differentials in the UK

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  • Michelle Gilmartin
  • Dimitris Korobilis

Abstract

This paper considers the determinants of regional disparities in unemployment rates for the UK regions at NUTS-II level. We use a mixture panel data model to describe unemployment differentials between heterogeneous groups of regions. The results indicate the existence of two clusters of regions in the UK economy, characterised by high and low unemployment rates respectively. A major source of heterogeneity seems to be caused by the varying (between the two clusters) effect of the share of employment in the services sector, and we trace its origin to the fact that the "high unemployment" cluster is characterised by a higher degree of urbanization.
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Suggested Citation

  • 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, May.
  • Handle: RePEc:bla:scotjp:v:59:y:2012:i:2:p:179-195
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    Cited by:

    1. Piotr Ciżkowicz & Michał Kowalczuk & Andrzej Rzońca, 2016. "Heterogeneous determinants of local unemployment in Poland," Post-Communist Economies, Taylor & Francis Journals, vol. 28(4), pages 487-519, October.
    2. Michal Šulc & Jana Borůvková & Roman Fiala, 2012. "Relationship between Unemployment and Wages at the Regional Level in the Czech Republic in the Period 2003-2010 [Vztah nezaměstnanosti a mezd na regionální úrovni v České republice v období 2003-20," Acta Universitatis Bohemiae Meridionalis, University of South Bohemia in Ceske Budejovice, Faculty of Economics, vol. 15(1), pages 91-101.
    3. Qingyu, Zhu, 2010. "Regional unemployment and house price determination," MPRA Paper 41785, University Library of Munich, Germany.
    4. Donald Houston, 2020. "Local resistance to rising unemployment in the context of the COVID‐19 mitigation policies across Great Britain," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(6), pages 1189-1209, December.
    5. César Augusto MERCHÁN HERNÁNDEZ, 2014. "Desempleo y ocupación en las ciudades colombianas. Un ejercicio con datos panel," Archivos de Economía 11212, Departamento Nacional de Planeación.
    6. George Grekousis, 2018. "Further Widening or Bridging the Gap? A Cross-Regional Study of Unemployment across the EU Amid Economic Crisis," Sustainability, MDPI, vol. 10(6), pages 1-18, May.
    7. George Grekousis & Stelios Gialis, 2019. "More Flexible Yet Less Developed? Spatio-Temporal Analysis of Labor Flexibilization and Gross Domestic Product in Crisis-Hit European Union Regions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(2), pages 505-524, June.
    8. Kevin Ralston & Dawn Everington & Zhiqiang Feng & Chris Dibben, 2022. "Economic Inactivity, Not in Employment, Education or Training (NEET) and Scarring: The Importance of NEET as a Marker of Long-Term Disadvantage," Work, Employment & Society, British Sociological Association, vol. 36(1), pages 59-79, February.

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • J08 - Labor and Demographic Economics - - General - - - Labor Economics Policies
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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