The role of R&D expenditure and human capital in shaping economic growth: A time series analysis of Hong Kong

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Type of article: Research Article

Abstract
This study investigates the causal relationship between research and development (R&D) financing and economic growth in Hong Kong over the period 1998–2022. It examines both public and private R&D expenditures, along with the number of researchers involved in R&D, to evaluate their influence on GDP per capita. Utilizing advanced time series econometric techniques, including the Toda-Yamamoto causality approach and cointegration analysis, the results reveal a statistically significant unidirectional causality from R&D expenditure to GDP per capita (χ² = 26.443, p < 0.01) and from researchers in R&D to GDP per capita (χ² = 38.164, p < 0.01). Additionally, feedback effects were observed, with GDP per capita also causing R&D expenditure (χ² = 17.471, p < 0.01), and R&D expenditure influencing the number of researchers (χ² = 6.718, p < 0.01). These findings highlight the dynamic interplay between financial inputs and human capital in R&D and underscore the importance of sustained investment and a skilled research workforce in fostering long-term economic growth. The evidence supports the strategic role of R&D policy in enhancing productivity and promoting economic sustainability in knowledge-based economies.

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    • Figure 1. Trends in economic development: GDP per capita, R&D expenditure, and researcher growth
    • Figure 2. Visualizing growth dynamics: Log-transformed trends of LGDPPC, LRDE, and LRRD
    • Figure 3. Procedural flowchart for conducting the Toda-Yamamoto Granger causality test
    • Figure 4. The inverse roots of the AR characteristic polynomial
    • Table 1. Overview of studies on R&D, human capital, and economic growth
    • Table 2. Statistical overview of the variables
    • Table 3. Unit root tests
    • Table 4. Var lag order selection criteria
    • Table 5. VAR residual serial correlation LM tests
    • Table 6. VAR residual diagnostic tests
    • Table 7. Johansen cointegration test
    • Table 8. Toda-Yamamoto Granger causality test
    • Conceptualization
      Zeynab Giyasova, Muslum Mursalov
    • Data curation
      Zeynab Giyasova, Jeyhun Hajiyev, Nelson Amowine
    • Investigation
      Zeynab Giyasova, Muslum Mursalov, Nelson Amowine
    • Methodology
      Zeynab Giyasova
    • Project administration
      Zeynab Giyasova, Muslum Mursalov, Jeyhun Hajiyev
    • Software
      Zeynab Giyasova
    • Visualization
      Zeynab Giyasova
    • Writing – original draft
      Zeynab Giyasova
    • Formal Analysis
      Muslum Mursalov, Jeyhun Hajiyev, Nelson Amowine, Gunay Panahova
    • Supervision
      Muslum Mursalov, Jeyhun Hajiyev, Nelson Amowine, Gunay Panahova
    • Writing – review & editing
      Muslum Mursalov, Jeyhun Hajiyev, Nelson Amowine, Gunay Panahova
    • Resources
      Jeyhun Hajiyev, Gunay Panahova
    • Validation
      Jeyhun Hajiyev, Nelson Amowine, Gunay Panahova
    • Funding acquisition
      Gunay Panahova
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