Linking R&D and Productivity in South Africa: The Moderating Role of Human Skills
Round 1
Reviewer 1 Report
Comments and Suggestions for Authors This interesting study takes the theme Linking R&D and Productivity in South Africa: The Moderating Role of Human Skills; however, some aspects still need to be modified and completed. For example, in this study, we examine the impact of research and development (R&D). We find that R&D effects are larger in technology-intensive areas. We introduce five lags to mitigate endogeneity as productivity. Don't say 'we' in a scientific article; it needs to be changed. (Romer, 1990; Aghion & Howitt, 1992). You (1979), Grossman and Helpman (1991), Romer (1990). This is supported by Keller (2009), there are still many references that are not updated, it should be replaced with the last 5 years, except in the explanation of grand theory or in the literature review, which uses early or old research. Could you explain and provide examples of the GAP phenomenon challenging Productivity in South Africa? Research GAP Linking R&D on Productivity should be strengthened and provide a basis and theory that supports why Human Skills can be used as a moderator. In line with theoretical expectations and empirical findings in the productivity 149 literature, we include a set of control variables in the model to account for additional in-150 dustry-level characteristics that may influence productivity outcomes. In essence, we in-151 consist of controls to isolate the effect of R&D stock on productivity while accounting 152 for other relevant drivers of industry performance…each paragraph contains at least one reference, please strengthen it so that the writing becomes more scientific. Van Biesebroeck, 2005, Melitz (2003). (Aghion, Blundell, 162 Griffith, Howitt & Prantl, 2009). An operational definition table of variables and their reference sources is needed to make the discussion more informative and strong. If equipped with a descriptive data table, it would be better. In the discussion, it is necessary to update the supporting references: This finding is consistent with endogenous 427 growth theory, which posits that human capital enhances the productivity of innovation 428 by facilitating learning, adaptation, and diffusion (Lucas Jr, 1988; Romer, 1990). Can use the last 5 years of data.Author Response
Dear Editor,
We appreciate the efforts and comments raised by the reviewers. We found all suggestions useful in improving the quality of our work. Below are our responses to each comment raised.
Reviewer One
- This interesting study takes the theme Linking R&D and Productivity in South Africa: The Moderating Role of Human Skills; however, some aspects still need to be modified and completed. For example, in this study, we examine the impact of research and development (R&D). We find that R&D effects are larger in technology-intensive areas. We introduce five lags to mitigate endogeneity as productivity. Don't say 'we' in a scientific article; it needs to be changed.
Thank you for raising this. We have replaced ‘we’ with ‘the study’ throughout the manuscript.
- (Romer, 1990; Aghion & Howitt, 1992). You (1979), Grossman and Helpman (1991), Romer (1990). This is supported by Keller (2009), there are still many references that are not updated, it should be replaced with the last 5 years, except in the explanation of grand theory or in the literature review, which uses early or old research.
Thank you for raising this. We have added an empirical section with 2025 and 2024 articles. We opted to retain the old citations as they are key studies in this strand of literature.
- Could you explain and provide examples of the GAP phenomenon challenging Productivity in South Africa? Research GAP Linking R&D on Productivity should be strengthened and provide a basis and theory that supports why Human Skills can be used as a moderator.
We have added a contribution section in the paragraph as highlighted in yellow. We have also added a theoretical literature review section which discusses the theoretical link between R&D and how human capital moderates this relationship.
- In line with theoretical expectations and empirical findings in the productivity 149 literature, we include a set of control variables in the model to account for additional in-150 industry-level characteristics that may influence productivity outcomes. In essence, we in-151 consist of controls to isolate the effect of R&D stock on productivity while accounting 152 for other relevant drivers of industry performance…each paragraph contains at least one reference, please strengthen it so that the writing becomes more scientific. Van Biesebroeck, 2005, Melitz (2003). (Aghion, Blundell, 162 Griffith, Howitt & Prantl, 2009).
Thank you for raising this. We have corrected this accordingly by adding more supportive and recent studies on this section. The additions are highlighted in blue.
- An operational definition table of variables and their reference sources is needed to make the discussion more informative and strong. If equipped with a descriptive data table, it would be better. In the discussion, it is necessary to update the supporting references: This finding is consistent with endogenous 427 growth theory, which posits that human capital enhances the productivity of innovation 428 by facilitating learning, adaptation, and diffusion (Lucas Jr, 1988; Romer, 1990). Can use the last 5 years of data.
Thank you for raising this. We have added an operational table in appendix and referenced it in text as highlighted in yellow in the data description section. The descriptive statistics table was included in the initial submission as the first table in appendix. Regarding the latest references, we have updated our literature to incorporate the latest citations.
Reviewer 2 Report
Comments and Suggestions for AuthorsThe abstract does not mention the econometric approach used.
The introduction states that its purpose is “to examine the moderating role of human capital in the relationship between R &D and productivity in South Africa”; however, this formulation remains excessively generic and does not crystallize into an operational research question that precisely delineates “to what extent” or “under what conditions” this moderating effect is expected. Nor is there an integrative theoretical framework that explicates the mechanisms through which human capital would transform R &D investment into productivity gains, leaving the causal logic implicit and scattered. Added to this is the absence of a systematic discussion of other potential interaction factors, such as corporate ownership structure, integration into global value chains, or digital intensity, that could simultaneously intervene and, consequently, confound or nuance the effects attributed solely to human capital.
The methodology section requires stronger grounding: it employs a fixed five-year lag and a linear interaction term without explaining why that time horizon or functional form is appropriate, leaving it unclear whether the model captures technological diffusion, the maturation of R & D investment, or simply reflects an ad hoc choice. Likewise, when estimating the R & D stock using the perpetual-inventory method, the authors do not specify the depreciation rate applied or its source, a critical parameter that can materially affect the estimated dynamics.
In the “4. Discussion” section, the authors attempt to convey economic significance by noting “relatively low” elasticities (≈ 0.01 %–0.02 % for labor productivity), yet they fail to translate this magnitude into tangible impacts—for example, changes in value added, GDP, and so on. Without that contextualization, it is impossible to gauge the practical relevance of the results and, by extension, the validity of the policy recommendations that follow.
Section “5. Conclusions” should be strengthened by addressing the shortcomings highlighted in the Discussion. Moreover, the policy recommendations are overly generic and need to be specified through concrete instruments and measures.
Author Response
Dear Editor,
We appreciate the efforts and comments raised by the reviewers. We found all suggestions useful in improving the quality of our work. Below are our responses to each comment raised.
Reviewer Two
- The abstract does not mention the econometric approach used.
Thank you. We have included the econometric approach as highlighted in the revised manuscript.
- The introduction states that its purpose is “to examine the moderating role of human capital in the relationship between R &D and productivity in South Africa”; however, this formulation remains excessively generic and does not crystallize into an operational research question that precisely delineates “to what extent” or “under what conditions” this moderating effect is expected. Nor is there an integrative theoretical framework that explicates the mechanisms through which human capital would transform R &D investment into productivity gains, leaving the causal logic implicit and scattered. Added to this is the absence of a systematic discussion of other potential interaction factors, such as corporate ownership structure, integration into global value chains, or digital intensity, that could simultaneously intervene and, consequently, confound or nuance the effects attributed solely to human capital.
Thank you for raising this. In response, we have included a full theoretical framework that explains the link between R&D and productivity as well as the moderating factors.
- The methodology section requires stronger grounding: it employs a fixed five-year lag and a linear interaction term without explaining why that time horizon or functional form is appropriate, leaving it unclear whether the model captures technological diffusion, the maturation of R & D investment, or simply reflects an ad hoc choice.
Thank you for this insightful comment. As we justified between lines 138-148 of the first submission, the decision to apply a five-year lag is theoretically grounded in the innovation literature, which consistently notes that productivity effects of R&D are not immediate due to adjustment costs, learning-by-doing, and the time required for innovation absorption and diffusion (see Ravenscraft & Scherer, 1982; Blanco, Gu & Prieger, 2016). A five-year lag captures the medium-term horizon during which innovation typically matures and is internalized by industries. This lag structure is also in line with empirical studies such as Bogliacino and Pianta (2011), and Tetteh (2024), who examine lagged R&D effects using similar time frames.
- Likewise, when estimating the R & D stock using the perpetual-inventory method, the authors do not specify the depreciation rate applied or its source, a critical parameter that can materially affect the estimated dynamics.
Thank you for this important observation. We have revised the manuscript to explicitly state the depreciation rate used in constructing the R&D capital stock. This is highlighted in yellow shortly after equation 1.
- In the “4. Discussion” section, the authors attempt to convey economic significance by noting “relatively low” elasticities (≈ 0.01 %–0.02 % for labor productivity), yet they fail to translate this magnitude into tangible impacts—for example, changes in value added, GDP, and so on. Without that contextualization, it is impossible to gauge the practical relevance of the results and, by extension, the validity of the policy recommendations that follow.
Thank you for your insightful comment regarding the need to contextualize the estimated elasticities in terms of tangible economic impacts such as value added and GDP. Our choice to restrict ourselves to the magnitude of the elasticity rather than broader effects in terms of GVA, GDP etc. is guided by the desire to avoid overstating beyond the empirical evidence directly supported by our data.
- Section “5. Conclusions” should be strengthened by addressing the shortcomings highlighted in the Discussion. Moreover, the policy recommendations are overly generic and need to be specified through concrete instruments and measures.
Thank you for your valuable feedback regarding Section 5, the Conclusions. We appreciate your suggestion to strengthen this section by explicitly addressing the shortcomings discussed earlier in the paper. I have revised the Conclusions to clearly acknowledge these limitations and reflect on their implications for the study’s findings.
Regarding the policy recommendations, I understand your concern that they were too general. I have now refined this section to include more specific measures tailored to the context of the study. We believe these improvements enhance the clarity and practical relevance of the Conclusions. We look forward to any further suggestions you may have.
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsThe article entitled "Linking R&D and Productivity in South Africa: The Moderating Role of Human Skills" is, in my opinion, ready for publication. It meets the required academic standards and requires no further review. I recommend its final acceptance.