Advertisement

Cognitive ability and corruption: rule of law (still) matters

  • Mohammad Reza FarzaneganEmail author
Article

Abstract

This study shows that the “longer time horizon” argument proposed by Potrafke (Econ Lett, 2012.  https://doi.org/10.1016/j.econlet.2019.02.026) with regard to the negative effect of a higher national average cognitive ability on corruption holds only for countries with a relatively high quality of legal systems. Using a sample of 94 countries from around the world, our cross-country regression analyses show the moderating role of rule of law in the final effects of cognitive abilities on corruption. The results are robust after using different indicators of corruption, rule of law and cognitive skills.

Keywords

Corruption Intelligence Cognitive Rule of law 

JEL Classification

A13 D91 E71 D73 E02 

Notes

Acknowledgements

I am grateful to two anonymous referees for their helpful and constructive comments. I also thank the CESifo and Niklas Potrafke in Munich for hosting me while working on this paper.

Compliance with ethical standards

Conflict of interest

The author declares that he has no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

References

  1. Acemoglu D, Johnson S, Robinson JA (2001) The colonial origins of comparative development: an empirical investigation. Am Econ Rev 91:1369–1401CrossRefGoogle Scholar
  2. Acemoglu D, Johnson S, Robinson JA (2005) Institutions as the fundamental cause of long-run growth. In: Aghion P, Durlauf SN (eds) Handbook of economic growth. Elsevier, Amsterdam, pp 385–472Google Scholar
  3. Ades A, Di Tella R (1999) Rents, competition, and corruption. Am Econ Rev 89:982–993CrossRefGoogle Scholar
  4. Alesina A, Giuliano P, Nunn N (2013) On the origins of gender roles: women and the plough. Q J Econ 128:469–530CrossRefGoogle Scholar
  5. Andersen TB, Dalgaard C-J, Selaya P (2016) Climate and the emergence of global income differences. Rev Econ Stud 83:1334–1363CrossRefGoogle Scholar
  6. Ang JB, Fredriksson PG, Luqman bin Nurhakim A, Tay EH (2018) Sunlight, disease, and institutions. Kyklos 71:374–401CrossRefGoogle Scholar
  7. Badinger H, Nindl E (2014) Globalisation and corruption, revisited. World Econ 37:1424–1440CrossRefGoogle Scholar
  8. Collier P (2014) Rent-seeking, living standards and inequality. Social Europe. https://www.socialeurope.eu/rent-seeking. Accessed 1 April 2019
  9. Dimant E, Tosato G (2018) Causes and effects of corruption: what has past decade’s empirical research taught us? A survey. J Econ Surv 32:335–356CrossRefGoogle Scholar
  10. Dreher A (2006) Does globalization affect growth? Evidence from a new index of globalization. Appl Econ 38:1091–1110CrossRefGoogle Scholar
  11. Farzanegan MR, Thum M (2018) Does oil rents dependency reduce the quality of education? Empir Econ.  https://doi.org/10.1007/s00181-018-1548-y Google Scholar
  12. Farzanegan MR, Witthuhn S (2017) Corruption and political stability: does the youth bulge matter? Eur J Polit Econ 49:47–70CrossRefGoogle Scholar
  13. Gallagher RP, Lee TK (2006) Adverse effects of ultraviolet radiation: a brief review. Prog Biophys Mol Biol 92:119–131CrossRefGoogle Scholar
  14. Hall RE, Jones CI (1999) Why do some countries produce so much more output per worker than others? Q J Econ 114:83–116CrossRefGoogle Scholar
  15. IMF (2016) Corruption: costs and mitigating strategies. International Monetary Fund, SDN 16/05, Washington, DCGoogle Scholar
  16. Jones G, Potrafke N (2014) Human capital and national institutional quality: are TIMSS, PISA, and national average IQ robust predictors? Intelligence 46:148–155CrossRefGoogle Scholar
  17. Kalonda-Kanyama I, Kodila-Tedika O (2012) Quality of institutions: does intelligence matter? Economic Research Southern Africa (ERSA) working paper 308, Cape TownGoogle Scholar
  18. Kodila-Tedika O (2014) Governance and intelligence: empirical analysis from African data. J Afr Dev 16:83–97Google Scholar
  19. Lapatinas A, Litina A (2018) Intelligence and economic sophistication. Empir Econ.  https://doi.org/10.1007/s00181-018-1511-y Google Scholar
  20. León F (2018) Diminished UV radiation enhances national cognitive ability, wealth, and institutions through health and education. Personal Individ Differ 120:52–57CrossRefGoogle Scholar
  21. León F, Burga-León A (2015) How geography influences complex cognitive ability. Intelligence 50:221–227CrossRefGoogle Scholar
  22. Linetsky M, Raghavan CT, Johar K, Fan X, Monnier VM, Vasavada AR, Nagaraj RH (2014) UVA light-excited kynurenines oxidize ascorbate and modify lens proteins through the formation of advanced glycation end products implications for human lens aging and cataract formation. J Biol Chem 289:17111–17123CrossRefGoogle Scholar
  23. Litan, R.E., Hathaway, I., 2017. Is America encouraging the wrong kind of entrepreneurship? Harvard Business Review (June 13, 2017). https://hbr.org/2017/06/is-america-encouraging-the-wrong-kind-of-entrepreneurship
  24. Löfgren S (2017) Solar ultraviolet radiation cataract. Exp Eye Res 156:112–116CrossRefGoogle Scholar
  25. Lynn R, Meisenberg G (2010) National IQs calculated and validated for 108 nations. Intelligence 38:353–360CrossRefGoogle Scholar
  26. Lynn R, Vanhanen T (2002) IQ and the wealth of nations. Praeger, WestportGoogle Scholar
  27. Lynn R, Vanhanen T (2006) IQ and global inequality. Washington Summit Publishers, AugustaGoogle Scholar
  28. Lynn R, Vanhanen T (2012) National IQs: a review of their educational, cognitive, economic, political, demographic, sociological, epidemiological, geographic and climatic correlates. Intelligence 40:226–234CrossRefGoogle Scholar
  29. Marshall MG, Gurr TR, Jaggers K (2018) POLITY IV PROJECT: dataset users’ manual. Center for Systemic Peace, ViennaGoogle Scholar
  30. Norman CS (2009) Rule of law and the resource curse: abundance versus intensity. Environ Resour Econ 43:183–207CrossRefGoogle Scholar
  31. Potrafke N (2012) Intelligence and corruption. Econ Lett 114:109–112CrossRefGoogle Scholar
  32. Potrafke N (2019) Risk aversion, patience and intelligence: evidence based on macro data. Econ Lett.  https://doi.org/10.1016/j.econlet.2019.02.026 Google Scholar
  33. Rindermann H (2007) The g-factor of international cognitive ability comparisons: the homogeneity of results in PISA, TIMSS, PIRLS and IQ tests across nations. Eur J Personal 21:667–706CrossRefGoogle Scholar
  34. Rindermann H, Kodila-Tedika O, Christainsen G (2015) Cognitive capital, good governance, and the wealth of nations. Intelligence 51:98–108CrossRefGoogle Scholar
  35. Rodrik D, Subramanian A, Trebbi F (2004) Institutions rule: the primacy of institutions over geography and integration in economic development. J Econ Growth 9:131–165CrossRefGoogle Scholar
  36. Sliney DH (2011) Intraocular and crystalline lens protection from ultraviolet damage. Eye Contact Lens 37:250–258CrossRefGoogle Scholar
  37. Staiger D, Stock JH (1997) Instrumental variables regression with weak instruments. Econometrica 65:557–586CrossRefGoogle Scholar
  38. Stock JH, Yogo M (2005) Testing for weak instruments in linear IV regression. In: Andrews DWK, Stock JH (eds) Identification and inference for econometric models: essays in honor of Thomas Rothenberg. Cambridge University Press, Cambridge, pp 80–108CrossRefGoogle Scholar
  39. Treisman D (2000) The causes of corruption: a cross-national study. J Public Econ 76:399–457CrossRefGoogle Scholar
  40. WDI (2018) World development indicators. World Bank, WashingtonGoogle Scholar
  41. Welsch H (2008) The welfare costs of corruption. Appl Econ 40:1839–1849CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Philipps-Universität Marburg, Center for Near and Middle Eastern Studies (CNMS), School of Business and Economics, Economics of the Middle East Research GroupMarburgGermany

Personalised recommendations