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Scientific output: labor or capital intensive? An analysis for selected countries

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Scientific research contributes to sustainable economic growth environments. Hence, policy-makers should understand how the different inputs—namely labor and capital—are related to a country’s scientific output. This paper addresses this issue by estimating output elasticities for labor and capital using a panel of 31 countries in nine years. Due to the nature of scientific output, we also use spatial econometric models to take into account the spillover effects from knowledge produced as well as labor and capital. The results show that capital elasticity is closer to the labor elasticity. The results suggest a decreasing return to scale production of scientific output. The spatial model points to negative spillovers from capital expenditure and no spillovers from labor or the scientific output.

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  5. One important discussion in the literature as described in Mueller (2016) is the lagged (delayed) effect of R&D investment on research outcome. In the “Appendix 2”, we present results using one year lagged on the explanatory variables.

  6. All the results presented in this paper uses linear models. However, Gantman (2012) points that one should consider count-data models when there is the possibility of skewed data, i.e., standard deviations larger than the means. We compared the negative binomial models with the linear models, and used the Akaike Information Criteria to determine that the linear models outperform the count data regression. These results are available upon request.

  7. Another robustness check performed was the analysis for unbalanced panels in all scenarios discussed. The results remain similar in terms of sign and significance of the estimated coefficients. These results are available upon request.


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This paper was the co-recipient of the Best Paper by Graduate Student in Economics Award at the 54th Annual Conference of the Academy of Economics and Finance - Charleston SC, 2017.

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Correspondence to Elham Erfanian.


Appendix 1

See Table 10.

Table 10 Counties in World Bank and OECD samples

Appendix 2: Results using lag variables

In this appendix, we address an important discussion in the production of scientific outcome, namely the delayed effect of investment in capital and labor on scientific output. As part of the production of scientific output, we know that to produce and publish articles time is important, as it can take several months, or years, to run an experiment, write the report and have it published. Therefore, we can expect a lag effect of capital and research investment on the output of scientific production.

Below we reproduce Tables 2, 3, 4, 5, 6, 7, 8 and 9 using a one year lag in our explanatory variables. Again, we will focus the analysis in model (4) with country and year fixed effects and the Spatial Durbin Model, both of which are our preferred models. Tables 11, 12, 13 and 14 present the non-spatial models and Tables 15, 16, 17 and 18 present the spatial models. Different then the results in the main text, now capital investment is positive across all models specifications but labor is not statistically significant, and when it is, it can be negative (Table 14—BE researchers). This is not a totally unexpected result, but in our opinion tells only part of the story as current researchers should be important in explaining current scientific productions.

Table 11 World Bank sample results—lagged
Table 12 OECD sample results—lagged
Table 13 OECD sample results, researchers—lagged
Table 14 OECD Sample results, disaggregated researchers—lagged
Table 15 World Bank sample spatial results, lagged
Table 16 OECD sample spatial results, lagged
Table 17 OECD sample spatial results, researchers, lagged
Table 18 OECD sample spatial results, disaggregated researchers, lagged

Therefore, combining both results should provide a better overall picture. In term of spatial spillovers we have mixed evidences: (1) for WB Sample positive spillover of researcher and negative spillover of capital; (2) OECD Sample: positive spillover of capital and negative spillover of labor cost but no statistical significance for either capital or labor when we use the number of researcher measures. Therefore, we cannot conclude if lagged researchers and capital influenced in neighboring countries. Nevertheless, the results seems consistent with the ones presented in the main text and help to tell a better story.

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Erfanian, E., B. Ferreira Neto, A. Scientific output: labor or capital intensive? An analysis for selected countries. Scientometrics 112, 461–482 (2017).

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