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Investigating Agglomeration Economies in a Panel of European Cities and Regions

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  • Michael Artis
  • Declan Curran
  • Marianne Sensier

Abstract

This paper investigates agglomeration economies in an annual panel of NUTS 2 and NUTS 3 city regions across France, Germany, Ireland, Italy, Spain and the UK over 1980-2006 and comparing three sub-samples to see if the effects have changed over time. We uncover evidence of long run agglomeration effects of around 6% for NUTS 2 and NUTS 3 city regions for the full sample. The underlying pattern that this data reflects is changing sectoral composition in which manufacturing was declining, to be largely replaced by services; then more recently a period of city-based economic growth with the financial and business services-led boom at its heart.

Suggested Citation

  • Michael Artis & Declan Curran & Marianne Sensier, 2011. "Investigating Agglomeration Economies in a Panel of European Cities and Regions," SERC Discussion Papers 0078, Spatial Economics Research Centre, LSE.
  • Handle: RePEc:cep:sercdp:0078
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    References listed on IDEAS

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    1. Ciccone, Antonio & Hall, Robert E, 1996. "Productivity and the Density of Economic Activity," American Economic Review, American Economic Association, vol. 86(1), pages 54-70, March.
    2. Ciccone, Antonio, 2002. "Agglomeration effects in Europe," European Economic Review, Elsevier, vol. 46(2), pages 213-227, February.
    3. Rafael E. De Hoyos & Vasilis Sarafidis, 2006. "Testing for cross-sectional dependence in panel-data models," Stata Journal, StataCorp LP, vol. 6(4), pages 482-496, December.
    4. Rice, Patricia & Venables, Anthony J. & Patacchini, Eleonora, 2006. "Spatial determinants of productivity: Analysis for the regions of Great Britain," Regional Science and Urban Economics, Elsevier, vol. 36(6), pages 727-752, November.
    5. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    6. Eleonora Patacchini & Patricia Rice, 2007. "Geography and Economic Performance: Exploratory Spatial Data Analysis for Great Britain," Regional Studies, Taylor & Francis Journals, vol. 41(4), pages 489-508.
    7. Anders Malmberg & Peter Maskell, 2002. "The elusive concept of localization economies: towards a knowledge-based theory of spatial clustering," Environment and Planning A, Pion Ltd, London, vol. 34(3), pages 429-449, March.
    8. Michael Artis & Ernest Miguélez & Rosina Moreno, 2009. "Assessing Agglomeration Economies in a Spatial Framework with Endogenous Regressors," SERC Discussion Papers 0023, Spatial Economics Research Centre, LSE.
    9. Leon Oerlemans & Marius Meeus, 2005. "Do Organizational and Spatial Proximity Impact on Firm Performance?," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 89-104.
    10. Brülhart, Marius & Mathys, Nicole A., 2008. "Sectoral agglomeration economies in a panel of European regions," Regional Science and Urban Economics, Elsevier, vol. 38(4), pages 348-362, July.
    11. Pesaran, M.H., 2004. "‘General Diagnostic Tests for Cross Section Dependence in Panels’," Cambridge Working Papers in Economics 0435, Faculty of Economics, University of Cambridge.
    12. Melo, Patricia C. & Graham, Daniel J. & Noland, Robert B., 2009. "A meta-analysis of estimates of urban agglomeration economies," Regional Science and Urban Economics, Elsevier, vol. 39(3), pages 332-342, May.
    13. Wheeler, Christopher H, 2001. "Search, Sorting, and Urban Agglomeration," Journal of Labor Economics, University of Chicago Press, vol. 19(4), pages 879-899, October.
    14. Federico Cingano & Fabiano Schivardi, 2004. "Identifying the Sources of Local Productivity Growth," Journal of the European Economic Association, MIT Press, vol. 2(4), pages 720-742, June.
    15. Ron Boschma, 2005. "Proximity and Innovation: A Critical Assessment," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 61-74.
    16. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    17. Bennett Harrison, 2007. "Industrial Districts: Old Wine in New Bottles? (Volume 26, Number 5, 1992)," Regional Studies, Taylor & Francis Journals, vol. 41(sup1), pages 107-121.
    18. Chris Van Egeraat & David Jacobson, 2006. "The Geography Of Production Linkages In The Irish And Scottish Microcomputer Industry: The Role Of Information Exchange," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 97(4), pages 405-417, September.
    19. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
    20. Romer, Paul M, 1987. "Growth Based on Increasing Returns Due to Specialization," American Economic Review, American Economic Association, vol. 77(2), pages 56-62, May.
    21. John B Parr, 2002. "Agglomeration economies: ambiguities and confusions," Environment and Planning A, Pion Ltd, London, vol. 34(4), pages 717-731, April.
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    Cited by:

    1. Ferhan Gezici & Burçin Yazgı & Sinem Metin, 2013. "Analyzing the determinants of agglomeration for the manufacturing industry in Turkey," ERSA conference papers ersa13p808, European Regional Science Association.

    More about this item

    Keywords

    agglomeration; system dynamic panel data estimations;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E40 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - General

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