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How Local are Spatial Density Externalities? evidence from square grid data

Author

Listed:
  • Andersson, Martin

    () (CIRCLE, Lund University)

  • Klaesson, Johan

    () (CEnSE, Jönköping International Business School)

  • P. Larsson, Johan

    () (CEnSE,Jönköping International Business School)

Abstract

We analyze the geographic scale at which density externalities operate and their attenuation with distance. Using square grid data at a fine spatial resolution, we find that a doubling of neighborhood density, measured as the density of 1 km2 squares, yields an increase in the overall wage-level of a square in the order of 3 percent. The density of the wider region to which the neighborhood belongs shows a significantly smaller effect. Highly educated workers gain more from proximity to others, and when we decrease the sizes of the squares the effect is still stronger for such workers. Density effects operate simultaneously at different spatial levels, and we argue that the neighborhood effects are more prone to capture localized non-market effects, such as knowledge spillovers driven by face-to-face interaction.

Suggested Citation

  • Andersson, Martin & Klaesson, Johan & P. Larsson, Johan, 2012. "How Local are Spatial Density Externalities? evidence from square grid data," Papers in Innovation Studies 2012/10, Lund University, CIRCLE - Center for Innovation Research.
  • Handle: RePEc:hhs:lucirc:2012_010
    as

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    File URL: http://wp.circle.lu.se/upload/CIRCLE/workingpapers/201210_Andersson.pdf
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    References listed on IDEAS

    as
    1. Henri L.F. de Groot & Jacques Poot & Martijn J. Smit, 2007. "Agglomeration, Innovation and Regional Development: Theoretical Perspectives and Meta-Analysis," Tinbergen Institute Discussion Papers 07-079/3, Tinbergen Institute.
    2. Olof Ejermo & Astrid Kander, 2011. "Swedish business research productivity," Industrial and Corporate Change, Oxford University Press, vol. 20(4), pages 1081-1118, August.
    3. Martin Andersson & Urban Gråsjö, 2009. "Spatial dependence and the representation of space in empirical models," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(1), pages 159-180, March.
    4. Henry G. Overman, 2004. "Can we learn anything from economic geography proper?," Journal of Economic Geography, Oxford University Press, vol. 4(5), pages 501-516, November.
    5. Kander, Astrid & Enflo, Kerstin & Schön, Lennart, 2007. "In Defense of Electricity as a General Purpose Technology," Papers in Innovation Studies 2007/6, Lund University, CIRCLE - Center for Innovation Research.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Johan Larsson, 2014. "The neighborhood or the region? Reassessing the density–wage relationship using geocoded data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(2), pages 367-384, March.
    2. Larsson, Johan P., 2013. "The Neighborhood or the Region? Untangling the density-productivity relationship using geocoded data," Working Paper Series in Economics and Institutions of Innovation 318, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    3. Sofia Wixe & Martin Andersson, 2017. "Which types of relatedness matter in regional growth? Industry, occupation and education," Regional Studies, Taylor & Francis Journals, vol. 51(4), pages 523-536, April.
    4. Sofia Wixe, 2015. "The Impact of Spatial Externalities: Skills, Education and Plant Productivity," Regional Studies, Taylor & Francis Journals, vol. 49(12), pages 2053-2069, December.
    5. Jean Dubé & Cédric Brunelle, 2014. "Dots to dots: a general methodology to build local indicators using spatial micro-data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 245-272, August.
    6. Wixe, Sofia, 2014. "Firm Knowledge, Neighborhood Diversity and Innovation," Working Paper Series in Economics and Institutions of Innovation 360, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.

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    More about this item

    Keywords

    spatial scale; density; productivity; spatial dependence; geo-coded data; external scale economies; agglomeration externalities; Sweden; Modifiable Areal Unit Problem (MAUP);
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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