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The impact of research and development (R&D) on economic growth: new evidence from kernel-based regularized least squares

Author

Listed:
  • Jean-Joseph Minviel

    (UMRH - Unité Mixte de Recherche sur les Herbivores - UMR 1213 - VAS - VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Faten Ben Bouheni

    (Menlo College)

Abstract

Purpose Research and development (R&D) is increasingly considered to be a key driver of economic growth. The relationship between these variables is commonly examined using linear models and thus relies only on single-point estimates. Against this background, this paper provides new evidence on the impact of R&D on economic growth using a machine learning approach that makes it possible to go beyond single-point estimation. Design/methodology/approach The authors use the kernel regularized least squares (KRLS) approach, a machine learning method designed for tackling econometric models without imposing arbitrary functional forms on the relationship between the outcome variable and the covariates. The KRLS approach learns the functional form from the data and thus yields consistent estimates that are robust to functional form misspecification. It also provides pointwise marginal effects and captures non-linear relationships. The empirical analyses are conducted using a sample of 101 countries over the period 2000–2020. Findings The estimates indicate that R&D expenditure and high-tech exports positively and significantly influence economic growth in a non-linear manner. The authors also find a positive and statistically significant relationship between economic growth and greenhouse gas emissions. In both cases, the effects are higher for upper-middle-income and high-income countries. These results suggest that a substantial effort is needed to green economic growth. Internet access is found to be an important factor in supporting economic growth, especially in high-income and middle-income countries. Practical implications This paper contributes to underlining the importance of investing in R&D to support growth and shows that the disparity between countries is driven by the determinants of economic growth (human capital in R&D, high-tech exports, Internet access, economic freedom, unemployment rate and greenhouse gas emissions). Moreover, since the authors find that R&D expenditure and greenhouse gas emissions are positively associated with economic growth, technological progress with green characteristics may be an important pathway for green economic growth. Originality/value This paper uses an innovative machine learning method to provide new evidence that innovation supports economic growth.

Suggested Citation

  • Jean-Joseph Minviel & Faten Ben Bouheni, 2022. "The impact of research and development (R&D) on economic growth: new evidence from kernel-based regularized least squares," Post-Print hal-03786777, HAL.
  • Handle: RePEc:hal:journl:hal-03786777
    DOI: 10.1108/JRF-11-2021-0177
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    Citations

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    Cited by:

    1. Joachim Wagner, 2024. "Cloud computing and extensive margins of exports: Evidence for manufacturing firms from 27 EU countries," Journal of Information Economics, Anser Press, vol. 2(1), pages 102-111, March.
    2. Wagner, Joachim, 2024. "Cloud computing and extensive margins of exports: Evidence for manufacturing firms from 27 EU countries," KCG Working Papers 34, Kiel Centre for Globalization (KCG).
    3. Joachim Wagner, 2024. "Estimation of empirical models for margins of exports with unknown non-linear functional forms: A Kernel-Regularized Least Squares (KRLS) approach Evidence from eight European countries," Working Paper Series in Economics 424, University of Lüneburg, Institute of Economics.
    4. Joachim Wagner, 2024. "Cloud Computing and Extensive Margins of Exports - Evidence for Manufacturing Firms from 27 EU Countries," Working Paper Series in Economics 427, University of Lüneburg, Institute of Economics.
    5. Wagner, Joachim, 2024. "Robots and extensive margins of exports: Evidence for manufacturing firms from 27 EU countries," KCG Working Papers 33, Kiel Centre for Globalization (KCG).
    6. Joachim Wagner, 2024. "Digitalization Intensity and Extensive Margins of Exports in Manufacturing Firms from 27 EU Countries - Evidence from Kernel-Regularized Least Squares Regression," Working Paper Series in Economics 428, University of Lüneburg, Institute of Economics.
    7. Joachim Wagner, 2024. "Robots and Extensive Margins of Exports - Evidence for Manufacturing Firms from 27 EU Countries," Working Paper Series in Economics 426, University of Lüneburg, Institute of Economics.
    8. Gu, Xiao & Badeeb, Ramez Abubakr & Ali, Shahid & Khan, Zeeshan & Zhang, Changyong & Uktamov, Khusniddin Fakhriddinovich, 2023. "Nonlinear impact of natural resources and risk factors on the U.S. economic growth," Resources Policy, Elsevier, vol. 82(C).

    More about this item

    Keywords

    Research and development; High-tech; Economic growth; KRLS estimates; Greenhouse gas emissions; Economic freedom; C14; O32; O47;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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