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Sectoral Agglomeration Economies in a Panel of European Regions

  • Marius BRÜLHART
  • Nicole A. MATHYS

We estimate agglomeration economies, defined as the effect of density on labour productivity in European regions. The analysis of Ciccone (2002) is extended in two main ways. First, we use dynamic panel estimation techniques (system GMM), thus offering an alternative methodological treatment of the inherent endogeneity problem. Second, the sector dimension in the data allows for disaggregated estimation. Our results confirm the presence of significant agglomeration effects at the aggregate level, with an estimated long-run elasticity of 13 percent. Repeated crosssection regressions suggest that the strength of agglomeration effects has increased over time. At the sector level, the dominant pattern is of cross-sector "urbanisation" economies and own-sector congestion diseconomies. A notable exception is financial services, for which we find strong positive productivity effects from own-sector density.

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Paper provided by Université de Lausanne, Faculté des HEC, DEEP in its series Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) with number 07.04.

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Length: 28 pages
Date of creation: Jul 2007
Date of revision:
Publication status: Published in Regional Science and Urban Economics, 38(4), July 2008, pp.348-362
Handle: RePEc:lau:crdeep:07.04
Contact details of provider: Postal:
Université de Lausanne, Faculté des HEC, DEEP, Internef, CH-1015 Lausanne

Phone: ++41 21 692.33.20
Web page: http://www.hec.unil.ch/deep/publications/cahiers/series
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  1. Richard Blundell & Steve Bond, 1999. "GMM estimation with persistent panel data: an application to production functions," IFS Working Papers W99/04, Institute for Fiscal Studies.
  2. Ciccone, Antonio, 2002. "Agglomeration effects in Europe," European Economic Review, Elsevier, vol. 46(2), pages 213-227, February.
  3. Uwe Blien & Jens Suedekum & Katja Wolf, 2005. "Local Employment Growth in West Germany - A Dynamic Panel Approach," ERSA conference papers ersa05p620, European Regional Science Association.
  4. Vernon Henderson, 2001. "Marshall's Scale Economies," Working Papers 01-17, Center for Economic Studies, U.S. Census Bureau.
  5. Gilles Duranton & Henry G. Overman, 2005. "Testing for Localization Using Micro-Geographic Data," Review of Economic Studies, Oxford University Press, vol. 72(4), pages 1077-1106.
  6. Stephen Bond & Anke Hoeffler & Jonathan Temple, 2001. "GMM Estimation of Empirical Growth Models," Economics Papers 2001-W21, Economics Group, Nuffield College, University of Oxford.
  7. Maurice Bun & Frank Windmeijer, 2007. "The weak instrument problem of the system GMM estimator in dynamic panel data models," CeMMAP working papers CWP08/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  8. Gordon H. Hanson, 2000. "Scale Economies and the Geographic Concentration of Industry," NBER Working Papers 8013, National Bureau of Economic Research, Inc.
  9. Antonio Ciccone & Robert E. Hall, 1995. "Productivity and the density of economic activity," Economics Working Papers 120, Department of Economics and Business, Universitat Pompeu Fabra.
  10. Henderson, Vernon, 1997. "Externalities and Industrial Development," Journal of Urban Economics, Elsevier, vol. 42(3), pages 449-470, November.
  11. Steve Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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  13. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
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  15. Ottaviano, Gianmarco I.P. & Pinelli, Dino, 2006. "Market potential and productivity: Evidence from Finnish regions," Regional Science and Urban Economics, Elsevier, vol. 36(5), pages 636-657, September.
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  17. 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.
  18. Patricia Rice & Anthony J. Venables, 2004. "Spatial Determinants of Productivity: Analysis for the Regions of Great Britain," CEP Discussion Papers dp0642, Centre for Economic Performance, LSE.
  19. 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.
  20. Pierre-Philippe Combes & Henry G. Overman, 2003. "The spatial distribution of economic activities in the European Union," LSE Research Online Documents on Economics 20023, London School of Economics and Political Science, LSE Library.
  21. Federico Cingano & Fabiano Schivardi, 2003. "Identifying the Sources of Local Productivity Growth," Temi di discussione (Economic working papers) 474, Bank of Italy, Economic Research and International Relations Area.
  22. Dekle, Robert & Eaton, Jonathan, 1999. "Agglomeration and Land Rents: Evidence from the Prefectures," Journal of Urban Economics, Elsevier, vol. 46(2), pages 200-214, September.
  23. Rosenthal, Stuart S. & Strange, William C., 2004. "Evidence on the nature and sources of agglomeration economies," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 49, pages 2119-2171 Elsevier.
  24. Marius Brülhart & Pamina Koenig, 2005. "New Economic Geography meets Comecon: Regional Wages and Industry Location in Central Europe," Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) 05.01, Université de Lausanne, Faculté des HEC, DEEP.
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