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Understanding the spanish business innovation gap: the role of spillovers and firms’ absorptive capacity

Author

Listed:
  • Paloma López-García

    (Banco de España)

  • José Manuel Montero

    (Banco de España)

Abstract

This paper investigates whether the existence of knowledge spillovers, differences in the capacity of f rms to assimilate them and disparities in some human resource management practices are related with the decision to innovate of Spanish f rms. In order to do this, we employ data from the “Central de Balances” database, which covers both manufacturing and services f rms during the period 2003-2007, and use an estimator proposed by Wooldridge (2005) for dynamic random effects discrete choice models. The empirical exercise provides evidence on the positive link between spillovers and the innovative behaviour of companies, not just for the knowledge generated in the same industry, but also for that generated in the same region or by the public sector. Moreover, this link is stronger for those f rms with a higher capacity to absorb those spillovers. This ability not only works through f rms’ R&D capabilities, but also through such factors as the quality of the labour force, the share of temporary employment and the amount of resources spent in training. In addition to these factors, we f nd that innovation performance exhibits a high degree of inertia. Further, some other observed f rm characteristics, such as size, sales growth, export behaviour, sector capital intensity or f nancial structure variables, are also found to be relevant determinants of the likelihood of innovation.

Suggested Citation

  • Paloma López-García & José Manuel Montero, 2010. "Understanding the spanish business innovation gap: the role of spillovers and firms’ absorptive capacity," Working Papers 1015, Banco de España.
  • Handle: RePEc:bde:wpaper:1015
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    References listed on IDEAS

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    1. Dominique Guellec & Bruno Van Pottelsberghe de la Potterie, 2004. "From R&D to Productivity Growth: Do the Institutional Settings and the Source of Funds of R&D Matter?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 353-378, July.
    2. Bronwyn Hall, 2004. "The financing of research and development," Chapters, in: Anthony Bartzokas & Sunil Mani (ed.), Financial Systems, Corporate Investment in Innovation, and Venture Capital, chapter 2, Edward Elgar Publishing.
    3. Crepon, B. & Duguet, E. & Mairesse, J., 1998. "Research Investment, Innovation and Productivity: An Econometric Analysis at the Firm Level," Papiers d'Economie Mathématique et Applications 98.15, Université Panthéon-Sorbonne (Paris 1).
    4. Bruno Crepon & Emmanuel Duguet & Jacques Mairesse, 1998. "Research, Innovation And Productivity: An Econometric Analysis At The Firm Level," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 7(2), pages 115-158.
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    Cited by:

    1. Díaz, Antonia & Franjo, Luis, 2016. "Capital goods, measured TFP and growth: The case of Spain," European Economic Review, Elsevier, vol. 83(C), pages 19-39.
    2. Paloma Lopez-Garcia & Jose Manuel Montero, 2012. "Spillovers and absorptive capacity in the decision to innovate of Spanish firms: the role of human capital," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 21(7), pages 589-612, October.
    3. Tojeiro-Rivero, Damián, 2022. "What effect does the aggregate industrial R&D offshoring have on you? A multilevel study," Journal of International Management, Elsevier, vol. 28(2).

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    More about this item

    Keywords

    innovation; R&D; spillovers; absorptive capacity; skilled labour; temporary employment; dynamic RE probit model;
    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
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • J6 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • L00 - Industrial Organization - - General - - - General

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