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Fourier DF unit root test for R&D intensity of G7 countries

Author

Listed:
  • Yifei Cai

    (JLU - Jilin University, MUST - Macau University of Science and Technology)

  • Jamel Saadaoui

    (BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - Université de Haute-Alsace (UHA) - Université de Haute-Alsace (UHA) Mulhouse - Colmar - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

According to the Schumpeterian endogenous growth theory, the efficacy of R&D is lowered by the proliferation of products. To be consistent with empirical data, the ratio between innovative activity and product variety (also called R&D intensity) must be stationary. From this perspective, our contribution investigates whether the R&D intensity series is stationary when structural breaks are considered. Our sample of G7 countries is examined over the period spanning from 1870 to 2016. Our results indicate that traditional unit root tests (ADF, DF-GLS and KPSS) conclude that the R&D intensity series are non-stationary, in contradiction with the Schumpeterian endogenous growth theory. The conclusions of these traditional unit root tests may be misleading, as they ignore the presence of structural breaks. Indeed, we use several types of Fourier Dickey-Fuller tests to consider the presence of structural breaks. In the Fourier Dickey-Fuller unit root tests using double frequency and fractional frequency, the R&D intensity is significantly stationary at least at the 5% level for Canada, France, Germany, Italy and Japan when a deterministic trend is included in the tests. Nevertheless, the R&D intensity is non-stationary for the US, even when we consider structural breaks.

Suggested Citation

  • Yifei Cai & Jamel Saadaoui, 2022. "Fourier DF unit root test for R&D intensity of G7 countries," Post-Print hal-04031334, HAL.
    • Handle: RePEc:hal:journl:hal-04031334
    DOI: 10.1080/00036846.2022.2038776
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    Cited by:

    1. Caglar, Abdullah Emre & Daştan, Muhammet & Avci, Salih Bortecine, 2024. "Persistence of disaggregate energy RD&D expenditures in top-five economies: Evidence from artificial neural network approach," Applied Energy, Elsevier, vol. 365(C).
    2. Kilinc-Ata, Nurcan & Proskuryakova, Liliana N., 2023. "Empirical analysis of the Russian power industry's transition to sustainability," Utilities Policy, Elsevier, vol. 82(C).

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