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On the robustness of R&D

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  • Kul Luintel
  • Mosahid Khan
  • Konstantinos Theodoridis

Abstract

Alternative models of productivity predict a range of its determinants besides that of research and development (R&D). We investigate the robustness of R&D vis-à-vis a dozen productivity determinants in a panel of 16 Organisation for Economic Co-operation and Development countries through panel cointegration, bootstrap simulations and extensive sensitivity tests. Domestic knowledge stocks, international knowledge diffusion and human capital remain robust across all measures. The cross-country differences in accumulated knowledge stocks and human capital appear to explain productivity differences across countries. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Kul Luintel & Mosahid Khan & Konstantinos Theodoridis, 2014. "On the robustness of R&D," Journal of Productivity Analysis, Springer, vol. 42(2), pages 137-155, October.
    • Handle: RePEc:kap:jproda:v:42:y:2014:i:2:p:137-155
    DOI: 10.1007/s11123-013-0360-0
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    Cited by:

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    2. Thomas H.W. Ziesemer, 2021. "Mission-oriented R&D and growth," Journal of Applied Economics, Taylor & Francis Journals, vol. 24(1), pages 460-477, January.
    3. Thomas H. W. Ziesemer, 2022. "Foreign R&D spillovers to the USA and strategic reactions," Applied Economics, Taylor & Francis Journals, vol. 54(37), pages 4274-4291, August.
    4. Ziesemer, Thomas, 2019. "Japan's productivity and GDP growth: The role of GBAORD, public and foreign R&D," MERIT Working Papers 2019-029, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Thomas H. W. Ziesemer, 2024. "Mission-oriented R&D and growth of Japan 1988–2016: a comparison with private and public R&D," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 33(2), pages 218-247, February.
    6. Dierk Herzer, 2022. "An Empirical Note on the Long-Run Effects of Public and Private R&D on TFP," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(4), pages 3248-3264, December.
    7. Thanh Le & Ngoc Vu Bich & Sau Mai & Ha Nguyen & Hung Bui, 2023. "Financial Development and International R&D Spillovers Through Trade: Evidence From Developing Countries," SAGE Open, , vol. 13(1), pages 21582440231, March.
    8. Luintel, Kul B. & Khan, Mosahid, 2017. "Ideas production and international knowledge spillovers: Digging deeper into emerging countries," Research Policy, Elsevier, vol. 46(10), pages 1738-1754.
    9. Thomas H. W. Ziesemer, 2021. "The Effects of R&D Subsidies and Publicly Performed R&D on Business R&D: A Survey," Hacienda Pública Española / Review of Public Economics, IEF, vol. 236(1), pages 171-205, March.
    10. Ballestar, María Teresa & Díaz-Chao, Ángel & Sainz, Jorge & Torrent-Sellens, Joan, 2020. "Knowledge, robots and productivity in SMEs: Explaining the second digital wave," Journal of Business Research, Elsevier, vol. 108(C), pages 119-131.
    11. Camiña, Ester & Díaz-Chao, Ángel & Torrent-Sellens, Joan, 2020. "Automation technologies: Long-term effects for Spanish industrial firms," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    12. Elkhan Richard Sadik‐Zada, 2021. "Natural resources, technological progress, and economic modernization," Review of Development Economics, Wiley Blackwell, vol. 25(1), pages 381-404, February.
    13. THW Ziesemer, 2020. "Japan’s Productivity and GDP Growth: The Role of Private, Public and Foreign R&D 1967–2017," Economies, MDPI, vol. 8(4), pages 1-25, September.
    14. Tarancón, Miguel-Ángel & Gutiérrez-Pedrero, María-Jesús & Callejas, Fernando E. & Martínez-Rodríguez, Isabel, 2018. "Verifying the relation between labor productivity and productive efficiency by means of the properties of the input-output matrices. The European case," International Journal of Production Economics, Elsevier, vol. 195(C), pages 54-65.
    15. Ziesemer, Thomas, 2019. "The impact of mission-oriented R&D on domestic and foreign private and public R&D, total factor productivity and GDP," MERIT Working Papers 2019-047, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    16. Le, Thanh & Pham, Hanh & Mai, Sau & Vu, Ngoc, 2022. "Frontier academic research, industrial R&D and technological progress: The case of OECD countries," Technovation, Elsevier, vol. 114(C).
    17. Venturini, Francesco, 2015. "The modern drivers of productivity," Research Policy, Elsevier, vol. 44(2), pages 357-369.

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    More about this item

    Keywords

    R&D capital stock; Multifactor productivity; Heterogeneity; Panel cointegration; Bootstrap simulations; C2; O3; O4;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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