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

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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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  • OA Carboni, 2012. "A Spatial Analysis of R&D: the Role of Industry Proximity," Working Paper CRENoS 201204, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  • Handle: RePEc:cns:cnscwp:201204
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    Cited by:

    1. Paola Cardamone & Valeria Pupo & Fernanda Ricotta, 2014. "Assessing The Impact Of University Technology Transfer On Firms’ Innovation," Working Papers 201403, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    2. Anna M. Ferragina & Giulia Nunziante, 2018. "Are Italian firms performances influenced by innovation of domestic and foreign firms nearby in space and sectors?," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 45(3), pages 335-360, September.
    3. Oliviero A. Carboni & Claudio Detotto, 2016. "The economic consequences of crime in Italy," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 43(1), pages 122-140, January.
    4. Cardamone, Paola, 2014. "R&D, spatial proximity and productivity at firm level: evidence from Italy," MPRA Paper 57149, University Library of Munich, Germany.
    5. Arnab Bhattacharjee & Ornella Maietta & Fernanda Mazzotta, 2023. "Spatial agglomeration, innovation and firm survival for Italian manufacturing firms," Spatial Economic Analysis, Taylor & Francis Journals, vol. 18(3), pages 318-345, July.
    6. Oliviero A. Carboni & Giuseppe Medda, 2018. "R&D, export and investment decision: evidence from European firms," Applied Economics, Taylor & Francis Journals, vol. 50(2), pages 187-201, January.
    7. Claudia Cantabene & Iacopo Grassi, 2020. "R&D cooperation in SMEs: the direct effect and the moderating role of human capital," Applied Economics, Taylor & Francis Journals, vol. 52(28), pages 3090-3105, June.
    8. Oliviero A. Carboni & Giuseppe Medda, 2021. "Innovative activities and investment decision: evidence from European firms," The Journal of Technology Transfer, Springer, vol. 46(1), pages 172-196, February.
    9. Oliviero Carboni, 2013. "Spatial and industry proximity in collaborative research: evidence from Italian manufacturing firms," The Journal of Technology Transfer, Springer, vol. 38(6), pages 896-910, December.
    10. OA Carboni & G Medda, 2017. "Do Investment and Innovation Boost Export? An Analysis on European Firms," Working Paper CRENoS 201708, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

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    More about this item

    Keywords

    spatial weights; spatial dependence; spatial models; r&d;
    All these keywords.

    JEL classification:

    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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