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Bivariate Probit Models for Analysing how “Knowledge” Affects Innovation and Performance in Small and Medium Sized Firms

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  • FARACE, Salvatore

    (CELPE - Centre of Labour Economics and Economic Policy, University of Salerno - Italy)

  • MAZZOTTA, Fernanda

    (CELPE - Centre of Labour Economics and Economic Policy, University of Salerno - Italy)

Abstract

This paper examines the determinants of innovation and its effects on small- and medium-sized firms We use the data from the OPIS databank, which provides a survey on a representative sample of firms from a province of the Southern Italy. We want to study whether small and medium sized firms can have a competitive advantage using their innovative capabilities, regardless of their sectoral and size limits. The main factor influencing the likelihood of innovation is knowledge, which is acquired through different ways. The econometric methodology consists of two bivariate models in order to estimate the probability of increased sales conditioned to the probability of innovation. We found that knowledge positively influences the probability of innovation; at the same time, knowledge has also a positive indirect effect on the increase of sales through innovation.

Suggested Citation

  • FARACE, Salvatore & MAZZOTTA, Fernanda, 2011. "Bivariate Probit Models for Analysing how “Knowledge” Affects Innovation and Performance in Small and Medium Sized Firms," CELPE Discussion Papers 120, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    • Handle: RePEc:sal:celpdp:0120
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    References listed on IDEAS

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    1. Zoltan J. Acs & David B. Audretsch & Maryann P. Feldman, 2008. "R&D Spillovers and Recipient Firm Size," Chapters, in: Entrepreneurship, Growth and Public Policy, chapter 8, pages 88-94, Edward Elgar Publishing.
    2. Zoltan J. Acs & David B. Audretsch, 2008. "Innovation in Large and Small Firms: An Empirical Analysis," Chapters, in: Entrepreneurship, Growth and Public Policy, chapter 1, pages 3-15, Edward Elgar Publishing.
    3. Sergio Destefanis, 2001. "Differenziali Territoriali di Produttivita' ed Efficienza negli Anni '90: i Livelli e l'Andamento," CELPE Discussion Papers 59, CELPE - CEnter for Labor and Political Economics, University of Salerno, Italy.
    4. Zoltan Acs & David Audretsch, 1990. "Innovation and Small Firms," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262011131, April.
    5. Abernathy, William J. & Clark, Kim B., 1985. "Innovation: Mapping the winds of creative destruction," Research Policy, Elsevier, vol. 14(1), pages 3-22, February.
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    Cited by:

    1. Ornella Wanda Maietta, 2014. "Innovation Systems Research in the Italian Food Industry," CSEF Working Papers 358, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.

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    More about this item

    Keywords

    innovation; small and medium sized firms; human capital; networks; bivariate probit;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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