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Molecular Genetics and Economics

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Author Info

  • Jonathan P. Beauchamp
  • David Cesarini
  • Magnus Johannesson
  • Matthijs J. H. M. van der Loos
  • Philipp D. Koellinger
  • Patrick J. F. Groenen
  • James H. Fowler
  • J. Niels Rosenquist
  • A. Roy Thurik
  • Nicholas A. Christakis

Abstract

The costs of comprehensively genotyping human subjects have fallen to the point where major funding bodies, even in the social sciences, are beginning to incorporate genetic and biological markers into major social surveys. How, if at all, should economists use and combine molecular genetic and economic data from these surveys? What challenges arise when analyzing genetically informative data? To illustrate, we present results from a "genome-wide association study" of educational attainment. We use a sample of 7,500 individuals from the Framingham Heart Study; our dataset contains over 360,000 genetic markers per person. We get some initially promising results linking genetic markers to educational attainment, but these fail to replicate in a second large sample of 9,500 people from the Rotterdam Study. Unfortunately such failure is typical in molecular genetic studies of this type, so the example is also cautionary. We discuss a number of methodological challenges that face researchers who use molecular genetics to reliably identify genetic associates of economic traits. Our overall assessment is cautiously optimistic: this new data source has potential in economics. But researchers and consumers of the genoeconomic literature should be wary of the pitfalls, most notably the difficulty of doing reliable inference when faced with multiple hypothesis problems on a scale never before encountered in social science.

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Bibliographic Info

Article provided by American Economic Association in its journal Journal of Economic Perspectives.

Volume (Year): 25 (2011)
Issue (Month): 4 (Fall)
Pages: 57-82

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Handle: RePEc:aea:jecper:v:25:y:2011:i:4:p:57-82

Note: DOI: 10.1257/jep.25.4.57
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References

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  1. David Cesarini & Christopher T. Dawes & Magnus Johannesson & Paul Lichtenstein & Björn Wallace, 2009. "Genetic Variation in Preferences for Giving and Risk Taking," The Quarterly Journal of Economics, MIT Press, vol. 124(2), pages 809-842, May.
  2. Matthijs Loos & Philipp Koellinger & Patrick Groenen & Cornelius Rietveld & Fernando Rivadeneira & Frank Rooij & André Uitterlinden & Albert Hofman & A. Thurik, 2011. "Candidate gene studies and the quest for the entrepreneurial gene," Small Business Economics, Springer, vol. 37(3), pages 269-275, October.
  3. Anderson, Michael L., 2008. "Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1481-1495.
  4. Barnea, Amir & Cronqvist, Henrik & Siegel, Stephan, 2010. "Nature or Nurture: What Determines Investor Behavior?," SIFR Research Report Series 72, Institute for Financial Research.
  5. Nicos Nicolaou & Scott Shane & Georgina Adi & Massimo Mangino & Juliette Harris, 2011. "A polymorphism associated with entrepreneurship: evidence from dopamine receptor candidate genes," Small Business Economics, Springer, vol. 36(2), pages 151-155, February.
  6. Weili Ding & Steven F. Lehrer & J. Niels Rosenquist & Janet Audrain-McGovern, 2006. "The Impact of Poor Health on Education: New Evidence Using Genetic Markers," NBER Working Papers 12304, National Bureau of Economic Research, Inc.
  7. John Cawley & Euna Han & Edward C. Norton, 2011. "The validity of genes related to neurotransmitters as instrumental variables," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 884-888, 08.
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Cited by:
  1. Jan-Emmanuel De Neve & Nicholas A. Christakis & James H. Fowler & Bruno S. Frey, 2010. "Genes, Economics, and Happiness," CREMA Working Paper Series 2010-24, Center for Research in Economics, Management and the Arts (CREMA).
  2. David Cesarini & Magnus Johannesson & Patrik K. E. Magnusson & Björn Wallace, 2012. "The Behavioral Genetics of Behavioral Anomalies," Management Science, INFORMS, vol. 58(1), pages 21-34, January.
  3. Vanessa Mertins & Andrea B. Schote & Jobst Meyer, 2013. "Variants of the Monoamine Oxidase A Gene (MAOA) Predict Free-riding Behavior in Women in a Strategic Public Goods Experiment," IAAEU Discussion Papers 201302, Institute of Labour Law and Industrial Relations in the European Union (IAAEU).
  4. Stenberg, Anders, 2013. "Interpreting estimates of heritability – A note on the twin decomposition," Economics & Human Biology, Elsevier, vol. 11(2), pages 201-205.
  5. Björklund, Anders & Jäntti, Markus, 2012. "How important is family background for labor-economic outcomes?," Labour Economics, Elsevier, vol. 19(4), pages 465-474.
  6. Maczulskij, Terhi, 2013. "Employment sector and pay gaps: Genetic and environmental influences," Labour Economics, Elsevier, vol. 23(C), pages 89-96.
  7. Chew, Soo Hong & Ebstein, Richard P. & Zhong, Songfa, 2013. "Sex-hormone genes and gender difference in ultimatum game: Experimental evidence from China and Israel," Journal of Economic Behavior & Organization, Elsevier, vol. 90(C), pages 28-42.
  8. Terhi Maczulskij, 2012. "Employment sector and pay gaps: genetic and environmental influences," ERSA conference papers ersa12p755, European Regional Science Association.
  9. López Ulloa, Beatriz Fabiola & Moller, Valerie & Sousa-Poza, Alfonso, 2013. "How Does Subjective Well-Being Evolve with Age? A Literature Review," IZA Discussion Papers 7328, Institute for the Study of Labor (IZA).

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