The Journal of Technology Transfer

, Volume 43, Issue 3, pp 792–814 | Cite as

Optimization in R&D intensity and tax on corporate profits for supporting labor productivity of nations

  • Mario CocciaEmail author


The purpose of this study is to analyze the rates of R&D investments and taxes levied on profits of firms that can optimize the labour productivity of nations. Statistical evidence, based on OECD data, reveals that (very) high rates of R&D intensity and tax on corporate profits do not maximize the labour productivity of nations. In particular, the models here suggest that the R&D intensity equal to about 2.5% and tax on corporate profits equal to 3.1% of the GDP seem to maximize the labour productivity of countries. Beyond these optimal thresholds, the labor productivity begins to decrease. These results can be explained by the curvilinear relationship between labour productivity and R&D intensity, and between labour productivity and tax on corporate profits. Some factors and environmental determinants of these results are discussed. These findings can clarify whenever possible, some sources of labor productivity and suggest a research and industrial policy of optimal rates of R&D intensity and tax on corporate profits (as percentage of GDP) directed to support competitive advantage, technological innovation and wealth creation of nations over time.


Productivity R&D investment R&D intensity Tax on corporate profits Labour Curvilinear relation Innovation Optimization Technology transfer OECD countries 

JEL Classification

C00 J24 O32 O47 H21 H25 



I gratefully acknowledge financial support from the CNR - National Research Council of Italy for my visiting at Arizona State University (Grants 0072373-2014 and 0003005-2016) where this research started in 2014. The author thanks two anonymous referees and editors of The Journal of Technology Transfer for helpful comments and suggestions The author declares that he has no relevant or material financial interests that relate to the research discussed in this paper.


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© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Center for Social Dynamics and Complexity (CSDC)Arizona State UniversityTempeUSA
  2. 2.CNR – National Research Council of ItalyMoncalieriItaly

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