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A global analysis of the impact of research output on economic growth

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Abstract

The existing papers on the economic impact of research output have focussed on either a single country or bloc of selected countries. The aim of this paper is to examine the effect of research output on economic growth in 169 countries for the period, 1996–2013. A system GMM estimate, which provides for endogeneity, unobserved effects and small sample bias, is employed to test the relationship. Within the neoclassical framework, we use varieties of indicators to proxy research performance, and a few sensitivity analyses were also performed. Overall, the results show that research output has positive impact on economic growth, irrespective of whether the sample is for developing or developed countries. The policy implications of the findings are detailed in the body of the paper.

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Notes

  1. This idea has been criticised in some quarters including the Rosenberg (1994) that claimed that the model is longer valid.

  2. This is due to the fact that the dataset for the two series are not available for many countries in our sample. Moreover, there is no strong basis to think that depreciation rates will vary significantly across countries (Mankiw et al. 1992).

  3. The major concern with the two-step approach is that it tends to be biased downwards. We use the Windmeijer’s (2005) corrected standard errors, which correct for this deficiency.

  4. Due to the fact that some countries have negative population growth rate of more than 5 %, we use ignore the logarithm in the original model. In other words, we use the following \( (n + g + \delta ) \) to proxy Population Growth in the actual analysis.

  5. This is based on countries listed in World Bank’s developing and high-income economies (as of 1 July 2013). Countries such as Brunei, Slovakia and Qatar are not grouped under developing countries but high-income economies. In the analysis, these countries are counted among the developed countries.

  6. In the equation involving financial sector development, we use 2709 observations because of incomplete financial sector development dataset as 334 observations are missing.

  7. We thank an anonymous referee for bringing this point to our notice.

  8. The diagnostics test also suggests that the coefficients are jointly significant at 1 % level. In a bid to conserve space, this is not reported here.

  9. We are aware of studies such as Durham (2002) and Beck and Levine (2004) that have used longer interval such as 9-year interval. Such pattern cannot be followed in this analysis because GMM needs at least a time series dimension of 3 years.

  10. We are not using the lag term of research output in Table 2 (and therefore there is no column 10), because the averaged dataset is employed.

  11. We also conduct causality test, after knowing that all series are stationary at level. The findings show that there unidirectional causality from research output to economic growth in these countries. The results are available upon request.

  12. We thank an anonymous referee for bringing this point to our notice.

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Authors and Affiliations

  1. Faculty of Business, Multimedia University Malaysia, Room 4015, Melaka, Malaysia

    Sakiru Adebola Solarin & Yuen Yee Yen

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  1. Sakiru Adebola Solarin
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Correspondence to Sakiru Adebola Solarin.

Appendix

Appendix

See Table 3.

Table 3 List of countries
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Solarin, S.A., Yen, Y.Y. A global analysis of the impact of research output on economic growth. Scientometrics 108, 855–874 (2016). https://doi.org/10.1007/s11192-016-2002-6

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