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Innovation and Co-location


  • Satyasiba Das
  • Håkon Finne


Abstract Here we attempt to advance the understanding of the impact of co-locative factors on regional innovation performance. The objectives are to answer what role co-location plays in explaining differences in regional innovation performance and what methodological improvements can compensate for the shortcomings of existing econometric analyses. The study is based on register data from the Business Register of Statistics Norway and the patent data from the Norwegian Patent Office for the period 1995–2003, aggregated to 161 labour market regions of Norway. A Bayesian spatial autoregressive (heteroscedastic) estimation procedure is applied. The results confirm the role of various co-locative factors in the spatial distribution of innovation.

Suggested Citation

  • Satyasiba Das & Håkon Finne, 2008. "Innovation and Co-location," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(2), pages 159-194.
  • Handle: RePEc:taf:specan:v:3:y:2008:i:2:p:159-194 DOI: 10.1080/17421770801996649

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    References listed on IDEAS

    1. Rikard Forslid & Gianmarco I.P. Ottaviano, 2003. "An analytically solvable core-periphery model," Journal of Economic Geography, Oxford University Press, vol. 3(3), pages 229-240, July.
    2. Ottaviano, Gianmarco I. P., 2001. "Monopolistic competition, trade, and endogenous spatial fluctuations," Regional Science and Urban Economics, Elsevier, vol. 31(1), pages 51-77, February.
    3. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    4. Baldwin, Richard E. & Krugman, Paul, 2004. "Agglomeration, integration and tax harmonisation," European Economic Review, Elsevier, vol. 48(1), pages 1-23, February.
    5. Currie, Martin & Kubin, Ingrid, 2006. "Chaos in the core-periphery model," Journal of Economic Behavior & Organization, Elsevier, vol. 60(2), pages 252-275, June.
    6. Forslid, Rikard, 1999. "Agglomeration with Human and Physical Capital: an Analytically Solvable Case," CEPR Discussion Papers 2102, C.E.P.R. Discussion Papers.
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    Cited by:

    1. Karsten Rusche & Uwe Kies & Andreas Schulte, 2011. "Measuring spatial co-agglomeration patterns by extending ESDA techniques," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 31(1), pages 11-25, June.

    More about this item


    New Economic Geography; growth and development; spatial econometrics; C21; O18; O31; R11; R12;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • 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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