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A class of spatial econometric methods in the empirical analysis of clusters of firms in the space

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  • Giuseppe Arbia

    ()

  • Giuseppe Espa

    ()

  • Danny Quah

    ()

Abstract

In this paper we aim at identifying stylized facts in order to suggest adequate models of spatial co–agglomeration of industries. We describe a class of spatial statistical methods to be used in the empirical analysis of spatial clusters. Compared to previous contributions using point pattern methods, the main innovation of the present paper is to consider clustering for bivariate (rather than univariate) distributions, which allows uncovering co–agglomeration and repulsion phenomena between the different industrial sectors. Furthermore we present the results of an empirical application of such methods to a set of European Patent Office (EPO) data and we produce a series of empirical evidences referred to the the pair–wise intra–sectoral spatial distribution of patents in Italy in the nineties. In this analysis we are able to identify some distinctive joint patterns of location between patents of different sectors and to propose some possible economic interpretations.

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Bibliographic Info

Article provided by Springer in its journal Empirical Economics.

Volume (Year): 34 (2008)
Issue (Month): 1 (February)
Pages: 81-103

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Handle: RePEc:spr:empeco:v:34:y:2008:i:1:p:81-103

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Related research

Keywords: Agglomeration; Bivariate K-functions; Co-agglomeration; Spatial clusters; Spatial econometrics; C21; D92; L60; O18; R12;

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References

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  1. Breschi, Stefano & Lissoni, Francesco, 2001. "Knowledge Spillovers and Local Innovation Systems: A Critical Survey," Industrial and Corporate Change, Oxford University Press, vol. 10(4), pages 975-1005, December.
  2. Ellison, G. & Glaeser, E.L., 1994. "Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach," Working papers 94-27, Massachusetts Institute of Technology (MIT), Department of Economics.
  3. 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.
  4. Jaffe, A.B. & Trajtenberg, M., 1992. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," Papers 14-92, Tel Aviv.
  5. Devereux, Michael P. & Griffith, Rachel & Simpson, Helen, 2004. "The geographic distribution of production activity in the UK," Regional Science and Urban Economics, Elsevier, vol. 34(5), pages 533-564, September.
  6. Yannis Ioannides & Henry G. Overman, 2004. "Spatial evolution of the US urban system," LSE Research Online Documents on Economics 600, London School of Economics and Political Science, LSE Library.
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Citations

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Cited by:
  1. Reinhold Kosfeld & Hans-Friedrich Eckey & Jørgen Lauridsen, 2011. "Spatial point pattern analysis and industry concentration," The Annals of Regional Science, Springer, vol. 47(2), pages 311-328, October.
  2. José M. Albert & Marta R. Casanova & Jorge Mateu & Vicente Orts, 2013. "Distance-Based Methods: An improvement of Ripley’s K function vs. the K density function," Working Papers 2013/07, Economics Department, Universitat Jaume I, Castellón (Spain).
  3. Laura de Dominicis & Giuseppe Arbia & Henri L.F. de Groot, 2007. "The Spatial Distribution of Economic Activities in Italy," Tinbergen Institute Discussion Papers 07-094/3, Tinbergen Institute.
  4. Gerald A. Carlino & Jake Carr & Robert M. Hunt & Tony E. Smith, 2010. "The agglomeration of R&D labs," Working Papers 10-33, Federal Reserve Bank of Philadelphia.
  5. Hans-Friedrich Eckey & Reinhold Kosfeld & Alexander Werner, 2012. "Bivariate K functions as instruments to analyze inter-industrial concentration processes," Jahrbuch für Regionalwissenschaft, Springer, vol. 32(2), pages 133-157, September.
  6. Eric Marcon & Florence Puech, 2009. "Measures of the Geographic Concentration of Industries: Improving Distance-Based Methods," Working Papers halshs-00372617, HAL.
  7. Arnab Bhattacharjee & Taps Maiti & Dennis Petrie, 2014. "Spatial structures of health outcomes and health behaviours in Scotland: Evidence from the Scottish Health Survey," SEEC Discussion Papers 1401, Spatial Economics and Econometrics Centre, Heriot Watt University.
  8. Arbia, Giuseppe & Espa, Giuseppe & Giuliani, Diego & Mazzitelli, Andrea, 2010. "Detecting the existence of space-time clustering of firms," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 311-323, September.
  9. Barlet, M. & Briant, A. & Crusson, L., 2013. "Location patterns of service industries in France: A distance-based approach," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 338-351.
  10. Arbia, G. & Espa, G. & Giuliani, D. & Mazzitelli, A., 2012. "Clusters of firms in an inhomogeneous space: The high-tech industries in Milan," Economic Modelling, Elsevier, vol. 29(1), pages 3-11.
  11. Laura de Dominicis & Giuseppe Arbia & Henri L.F. de Groot, 2007. "The Spatial Distribution of Economic Activities in Italy," Tinbergen Institute Discussion Papers 07-094/3, Tinbergen Institute.
  12. Eric Marcon & Florence Puech, 2012. "A typology of distance-based measures of spatial concentration," Working Papers halshs-00679993, HAL.
  13. Giuseppe Espa & Giuseppe Arbia & Diego Giuliani, 2013. "Conditional versus unconditional industrial agglomeration: disentangling spatial dependence and spatial heterogeneity in the analysis of ICT firms’ distribution in Milan," Journal of Geographical Systems, Springer, vol. 15(1), pages 31-50, January.
  14. HAEDO, Christian & MOUCHART, Michel, 2012. "A stochastic independence approach for different measures of concentration and specialization," CORE Discussion Papers 2012025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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