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A Spatial Analysis of R&D: the Role of Industry Proximity

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  • OA. Carboni

Abstract

This paper employs individual firm data in order to check the existence of industry-spatial effects alongside other microeconomic determinants of R&D investment. Spatial proximity is defined by a measure of firms’ industry distance based on trade intensity between sectors. The spatial model specified here refers to the combined spatial autoregressive model with autoregressive disturbances (SARAR). In modelling the outcome for each location as dependent on a weighted average of the outcomes of other locations, outcomes are determined simultaneously. The results of the spatial two stage least square estimation suggest that in their R&D decision firms benefit from spillovers originating from neighbouring industries.

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Bibliographic Info

Paper provided by Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia in its series Working Paper CRENoS with number 201204.

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Date of creation: 2012
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Handle: RePEc:cns:cnscwp:201204

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Keywords: spatial weights; spatial dependence; spatial models; r&d;

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References

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  1. Wolfgang Keller, 1997. "Trade and the Transmission of Technology," Development and Comp Systems, EconWPA 9707001, EconWPA.
  2. Donald S. Siegel & Catherine J. Morrison Paul, 1999. "Scale Economies and Industry Agglomeration Externalities: A Dynamic Cost Function Approach," American Economic Review, American Economic Association, American Economic Association, vol. 89(1), pages 272-290, March.
  3. Jeffrey I. Bernstein & M. Ishaq Nadiri, 1986. "Research and Development and Intraindustry Spillovers: An Empirical Application of Dynamic Duality," NBER Working Papers 2002, National Bureau of Economic Research, Inc.
  4. Glenn Ellison & Edward L. Glaeser & William Kerr, 2007. "What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns," NBER Working Papers 13068, National Bureau of Economic Research, Inc.
  5. OA. Carboni, 2009. "An Empirical investigation of the Determinants of R&D Cooperation," Working Paper CRENoS 200909, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  6. Giovanni Peri, 2005. "Determinants of Knowledge Flows and Their Effect on Innovation," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 308-322, May.
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Cited by:
  1. Cardamone, Paola, 2014. "R&D, spatial proximity and productivity at firm level: evidence from Italy," MPRA Paper 57149, University Library of Munich, Germany.
  2. OA. Carboni & C. Detotto, 2013. "The economic consequences of crime in Italy," Working Paper CRENoS 201303, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

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