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The Path of R&D Efficiency over Time

Author

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  • Pilar Beneito

    (University of Valencia and ERI-CES)

  • María Engracia Rochina-Barrachina

    (University of Valencia)

  • Amparo Sanchis

    (University of Valencia)

Abstract

In this paper we investigate the pattern of R&D efficiency in terms of the number of product innovations achieved by firms over time. Embodied in the R&D capital stock, we distinguish among physical R&D capital and human R&D capital, and allow the latter to be subject to dynamic returns along firms’ R&D histories. We assume that firms’ innovation outcomes depend on the length of the period of time they have been investing in R&D and explore whether the interruption in this temporal sequence of engagement in R&D affects the rate of achievement of innovation outcomes. For this purpose, we estimate an innovation production function using a panel dataset of Spanish manufacturing firms for the period 1990-2006. Our results suggest that R&D activities exhibit dynamic returns that are increasing but at a decreasing rate, possibly due to exhaustion of innovation opportunities. In addition, our findings indicate that interruptions of R&D activities reduce R&D efficiency, probably due to organizational forgetting. However, spillover effects seem to exist between firms’ R&D spells since firms resuming R&D activities achieve innovation success rates above the innovation rates of their initial years of R&D activities.

Suggested Citation

  • Pilar Beneito & María Engracia Rochina-Barrachina & Amparo Sanchis, 2014. "The Path of R&D Efficiency over Time," Working Papers 1403, Department of Applied Economics II, Universidad de Valencia.
    • Handle: RePEc:eec:wpaper:1403
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    2. Labeaga, José M. & Martínez-Ros, Ester & Sanchis, Amparo & Sanchis, Juan A., 2021. "Does persistence in using R&D tax credits help to achieve product innovations?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    3. Martina Halaskova & Beata Gavurova & Kristina Kocisova, 2020. "Research and Development Efficiency in Public and Private Sectors: An Empirical Analysis of EU Countries by Using DEA Methodology," Sustainability, MDPI, vol. 12(17), pages 1-22, August.
    4. P. Beneito & M. E. Rochina-Barrachina & A. Sanchis, 2016. "Foreign capital, credit constraints and continuity of firms' R&D," Applied Economics Letters, Taylor & Francis Journals, vol. 23(3), pages 157-161, February.
    5. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    6. Mañez, J.A. & Love, J.H., 2020. "Quantifying sunk costs and learning effects in R&D persistence," Research Policy, Elsevier, vol. 49(7).
    7. García-Vega, María, 2022. "R&D restructuring during the Great Recession and young firms," International Journal of Industrial Organization, Elsevier, vol. 81(C).
    8. María García-Vega, 2020. "R&D restructuring during the Great Recession and young firms," Discussion Papers 2020-09, University of Nottingham, GEP.

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    More about this item

    Keywords

    R&D; dynamic returns; interruptions; product innovation; count data;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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