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A New Approach to Estimation of the R&D-Innovation-Productivity Relationship

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  • Baum, Christopher F

    (Department of Economics, Boston College and Department of Macroeconomics, DIW Berlin)

  • Lööf, Hans

    (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology)

  • Nabavi, Pardis

    (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology)

  • Stephan, Andreas

    (Jönkoping International Business School and Centre of Excellence for Science and Innovation Studies.)

Abstract

We evaluate a Generalized Structural Equation Model (GSEM) approach to the estimation of the relationship between R&D, innovation and productivity that focuses on the potentially crucial heterogeneity across technology and knowledge levels. The model accounts for selectivity and handles the endogeneity of this relationship in a recursive framework. Employing a panel of Swedish firms observed in three consecutive Community Innovation Surveys, our maximum likelihood estimates show that many key channels of influence among the model's components differ meaningfully in their statistical significance and magnitude across sectors defined by different technology levels.

Suggested Citation

  • Baum, Christopher F & Lööf, Hans & Nabavi, Pardis & Stephan, Andreas, 2015. "A New Approach to Estimation of the R&D-Innovation-Productivity Relationship," Working Paper Series in Economics and Institutions of Innovation 408, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
  • Handle: RePEc:hhs:cesisp:0408
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    References listed on IDEAS

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    Cited by:

    1. Movahedi, Mohammad & Shahbazi, Kiumars & Gaussens, Olivier, 2017. "Innovation and willingness to export: Is there an effect of conscious self-selection?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW), vol. 11, pages 1-22.
    2. Dorothea Schäfer & Andreas Stephan & Jenniffer Solórzano Mosquera, 2017. "Family ownership: does it matter for funding and success of corporate innovations?," Small Business Economics, Springer, vol. 48(4), pages 931-951, April.
    3. Schäfer, Dorothea & Stephan, Andreas & Mosquera, Jenniffer Solórzano, 2015. "Innovation Capabilities and Financing Constraints of Family Firms," Working Paper Series in Economics and Institutions of Innovation 425, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    4. Audretsch, David & Hafenstein, Marian & Kritikos, Alexander S. & Schiersch, Alexander, 2018. "Firm Size and Innovation in the Service Sector," IZA Discussion Papers 12035, Institute of Labor Economics (IZA).
    5. Ferrando, Annalisa & Rossi, Stefania P. S. & Bonanno, Graziella, 2020. "Determinants of firms’ efficiency: do innovations and finance constraints matter? The case of European SMEs," Working Paper Series 2419, European Central Bank.
    6. Castelnovo, Paolo & Florio, Massimo & Forte, Stefano & Rossi, Lucio & Sirtori, Emanuela, 2018. "The economic impact of technological procurement for large-scale research infrastructures: Evidence from the Large Hadron Collider at CERN," Research Policy, Elsevier, vol. 47(9), pages 1853-1867.
    7. Marcel Ausloos & Francesca Bartolacci & Nicola G. Castellano & Roy Cerqueti, 2018. "Exploring how innovation strategies at time of crisis influence performance: a cluster analysis perspective," Papers 1808.05893, arXiv.org.
    8. Mohnen, Pierre, 2019. "R&D, innovation and productivity," MERIT Working Papers 2019-016, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    9. Marcel Ausloos & Francesca Bartolacci & Nicola G. Castellano & Roy Cerqueti, 2020. "Simple approaches on how to discover promising strategies for efficient enterprise performance, at time of crisis in the case of SMEs : Voronoi clustering and outlier effects perspective," Papers 2012.14297, arXiv.org.
    10. Eric J. Bartelsman & Martin Falk & Eva Hagsten & Michael Polder, 2019. "Productivity, technological innovations and broadband connectivity: firm-level evidence for ten European countries," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 9(1), pages 25-48, March.

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    More about this item

    Keywords

    R&D; Innovation; Productivity; Generalized Structural Equation Model; Community Innovation Survey;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe

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