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Measuring Intersectoral Knowledge Spillovers: An Application Of Sensitivity Analysis To Italy

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  • Giovanni Cerulli
  • Bianca Poti`

Abstract

R&D spillovers are unanimously considered as one of the main driving forces of technical change, innovation and economic growth. This paper aims at measuring interindustry R&D spillovers. We apply an 'uncertainty-sensitivity analysis' to the Italian input-output table of intermediate goods split into 31 economic sectors for the year 2000. The value added of using this methodology is the opportunity of distinguishing between spillover effects induced by productive linkages (the Leontief forward multipliers) and those activated by R&D investments, capturing the uncertain and non-linear nature of the relations between spillovers and factors affecting them.

Suggested Citation

  • Giovanni Cerulli & Bianca Poti`, 2009. "Measuring Intersectoral Knowledge Spillovers: An Application Of Sensitivity Analysis To Italy," Economic Systems Research, Taylor & Francis Journals, vol. 21(4), pages 409-436.
    • Handle: RePEc:taf:ecsysr:v:21:y:2009:i:4:p:409-436
    DOI: 10.1080/09535310903569216
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    Cited by:

    1. Yeo, Yeongjun & Lee, Jeong-Dong, 2020. "Revitalizing the race between technology and education: Investigating the growth strategy for the knowledge-based economy based on a CGE analysis," Technology in Society, Elsevier, vol. 62(C).
    2. Cerina, Fabio & Mureddu, Francesco, 2014. "Is agglomeration really good for growth? Global efficiency, interregional equity and uneven growth," Journal of Urban Economics, Elsevier, vol. 84(C), pages 9-22.
    3. Eduardo Gonçalves & Fernando Salgueiro Perobelli & Inácio Fernandes Araújo, 2017. "Estimating intersectoral technology spillovers for Brazil," The Journal of Technology Transfer, Springer, vol. 42(6), pages 1377-1406, December.
    4. Zuzana Smeets Kristkova & Cornelis Gardebroek & Michiel van Dijk & Hans van Meijl, 2017. "The impact of R&D on factor-augmenting technical change – an empirical assessment at the sector level," Economic Systems Research, Taylor & Francis Journals, vol. 29(3), pages 385-417, July.
    5. Fabrizio Fusillo & Sandro Montresor & Giuseppe Vittucci Marzetti, 2021. "The global network of embodied R&D flows," Discussion Paper series in Regional Science & Economic Geography 2021-05, Gran Sasso Science Institute, Social Sciences, revised Apr 2021.
    6. João Gabriel Pio & Eduardo Gonçalves & Claúdio R. F. Vasconcelos, 2021. "Technology Spillovers Through Exports: Empirical Evidence for the Chinese Case," Journal of Industry, Competition and Trade, Springer, vol. 21(3), pages 423-443, September.

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    More about this item

    Keywords

    R&D spillovers; Input-output models; Sensitivity analysis; Monte Carlo simulations;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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