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External R&D, product and process innovation in European manufacturing companies

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Abstract

We assess the relationship between firms’ Research and Development expenditures over sales and innovation output, measured by three dummies indicating whether firms have introduced any product innovation, process innovation or both types of innovations together. In particular, we estimate the impact that external sources of R&D may have on different kind of innovations, differentiating between R&D supplied by universities and other research centers, on one side, and other companies, on the other. We base our empirical analysis on a large and representative sample of European manufacturing companies from France, Germany, Italy, Spain, and the UK. Treating R&D intensity as an endogenous variable, we find that (1) R&D intensity has a positive and significant effect on the probability to introduce product innovations, process innovations, or both innovations together; (2) the share of R&D acquired from external sources has a positive impact on process innovation, and on the probability to introduce product and process innovation together, but not on product innovation alone; (3) the share of external R&D supplied by universities has a positive and significant effect on product innovation, but no correlation has been found with process innovation, while R&D acquired from other companies have a positive impact on process innovation but not on product innovation.

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Notes

  1. The Oslo Manual (Oecd 2005) also includes organizational innovations (new business practices) and marketing innovations (concerning design, packaging, pricing, etc.).

  2. For recent surveys and discussions, see Barge-Gil and López (2014), and Aristei et al. (2016).

  3. EFIGE is the acronym of “European Firms in a Global Economy”: a project for internal policies and external competitiveness supported by the Directorate General Research of the European Commission through its 7th Framework Programme and coordinated by Bruegel.

  4. Returns to R&D investment in terms of productivity and revenues are estimated to take a longer time to come out. Even longer lags are estimated between private R&D and social returns (Hall et al. 2010).

  5. On this point, and for a description of other characteristics of the two part model, see Wooldridge (2010; Sect. 17.6).

  6. Unfortunately, firms' information about the region where they are located is not available for Hungary and Austria, thus the decision to exclude these Countries from the present analysis.

  7. All estimates are conducted using Stata cmp command (conditional mixed process estimator) developed by Roodman (2011), based on maximum simulated likelihood methods (Cappellari and Jenkins 2003).

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Authors and Affiliations

  1. Department of Economics (DiSEA), University of Sassari, Via Francesco Muroni 25, 07100, Sassari, Italy

    Giuseppe Medda

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  1. Giuseppe Medda
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Correspondence to Giuseppe Medda.

Appendix

Appendix

See Table 9.

Table 9 2 part model of determinants of R&D: first and second part estimates
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Medda, G. External R&D, product and process innovation in European manufacturing companies. J Technol Transf 45, 339–369 (2020). https://doi.org/10.1007/s10961-018-9682-4

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