The Journal of Economic Inequality

, Volume 17, Issue 3, pp 319–335 | Cite as

Heritability of lifetime earnings

  • Ari Hyytinen
  • Pekka IlmakunnasEmail author
  • Edvard Johansson
  • Otto Toivanen
Open Access


Using twenty years of earnings data on Finnish twins, we find that about 40% of the variance of women’s and little more than half of men’s lifetime labour earnings are linked to genetic factors. The contribution of the shared environment is negligible. We show that the result is robust to using alternative definitions of earnings, to adjusting for the role of education, and to measurement errors in the measure of genetic relatedness.


Earnings inequality Heritability Twins Genetics 



We would like to thank anonymous referees, Anders Björklund, Markus Jäntti, Jaakko Kaprio, Tomi Kyyrä, Tuomas Pekkarinen, Roope Uusitalo, as well as seminar participants at the Summer Meeting of the Finnish Economists (Jyväskylä), EALE Conference (Bonn), EEA Conference (Gothenburg), VATT (Helsinki), and SOFI (Stockholm) for useful comments. The usual caveat applies. We are thankful to Professor Jaakko Kaprio (University of Helsinki) for access to the twins data (Older Finnish Twin Cohort Study of the Department of Public Health in the University of Helsinki), to Statistics Finland for access to the register data (Finnish Longitudinal Employer-Employee Data FLEED), and to the Research Services unit of Statistics Finland for linking of the data sets. The Ethics Committee of Statistics Finland has given permission to use the data and all data work has been carried out following the terms and conditions of confidentiality of Statistics Finland.


Open access funding provided by Aalto University. This research has been financially supported by the Academy of Finland (project 127796), the Strategic Research Council (project Work, Inequality, and Public Policy, 293120), Jenny and Antti Wihuri Foundation, and Palkansaajasäätiö Foundation. The opinions expressed in the article are those of the authors and do not necessarily reflect the views of the funding sources.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

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  1. Ashenfelter, O., Krueger, A.: Estimates of the economic return to schooling from a new sample of twins. Am. Econ. Rev. 84, 1157–1173 (1994)Google Scholar
  2. Ashenfelter, O., Rouse, C.: Income, schooling and ability: evidence from a new sample of identical twins. Q. J. Econ. 113, 253–284 (1998)CrossRefGoogle Scholar
  3. Autor, D., Figlio, D. Karbownik, K., Roth, J., Wasserman, M., Family disadvantage and the gender gap in behavioral and educational outcomes. NBER Working Paper No. 22267 (2016)Google Scholar
  4. Barnea, A., Cronqvist, H., Siegel, S.: Nature or nurture: what determines investor behavior? J. Financ. Econ. 98, 583–604 (2010)CrossRefGoogle Scholar
  5. Behrman, S., Taubman, P.: Is schooling “mostly in the genes?” Nature-nurture decomposition using data on relatives. J. Polit. Econ. 97, 1427–1446 (1989)Google Scholar
  6. Benjamin, D.J., Cesarini, D., Chabris, C.F., Glaeser, E.L., Laibson, D.I., Gudnason, V., Harris, T.B., Launer, L.J., Purcell, S., Smith, A.V., Johannesson, M., Magnusson, P.K.E., Beauchamp, J.P., Christakis, N.A., Atwood, C.S., Hebert, B., Freese, J., Hauser, R.M., Hauser, T.S., Grankvist, A., Hultman, C.M., Lichtenstein, P.: The promises and pitfalls of genoeconomics. Annu. Rev. Econ. 4, 627–662 (2012)CrossRefGoogle Scholar
  7. Bertrand, M.: New perspectives on gender. In: Ashenfelter, O., Card, D. (eds.) Handbook of Labor Economics, vol. Volume 4B, pp. 1543–1590. Elsevier, Amsterdam (2011)Google Scholar
  8. Bingley, P., Cappelari, L., Alike in many ways: Intergenerational and sibling correlations of brothers’ earnings. IZA Discussion Paper No. 6987 (2012)Google Scholar
  9. Bishop, D.V.M.: DeFries-Fulker analysis of twin data with skewed distributions: cautions and recommendations from a study of children’s use of verb inflections. Behav. Genet. 35, 479–490 (2005)CrossRefGoogle Scholar
  10. Björklund, A., Jäntti, M.: Intergenerational income mobility and the role of family background. In: Salverda, W., Nolan, B., Smeeding, T.M. (eds.) The Oxford Handbook of Economic Inequality, pp. 491–521. Oxford University Press, Oxford (2009)Google Scholar
  11. Björklund, A., Jäntti, M.: How important is family background for labor-economic outcomes? Labour Econ. 19, 465–474 (2012)CrossRefGoogle Scholar
  12. Björklund, A., Jäntti, M., Solon, G.: Influences of nature and nurture on earnings variation: a report on a study of various sibling types in Sweden. In: Bowles, S., Gintis, H., Osborne, M. (eds.) Unequal Chances: Family Background and Economic Success, pp. 145–164. Russell Sage Foundation, New York (2005)Google Scholar
  13. Björklund, A., Lindahl, M., Plug, E.: The origins of intergenerational associations: lessons from Swedish adoption data. Q. J. Econ. 121, 999–1028 (2006)CrossRefGoogle Scholar
  14. Björklund, A., Jäntti, M., Solon, G., Nature and nurture in the intergenerational transmission of socioeconomic status: Evidence from Swedish children and their biological and rearing parents. BE J. Econ. Anal. Poli.: Advances 7, Article 4 (2007)Google Scholar
  15. Björklund, A., Jäntti, M., Lindquist, M.: Family background and income during the rise of the welfare state: brother correlations in income for Swedish men born 1932-1968. J. Public Econ. 93, 671–680 (2009)CrossRefGoogle Scholar
  16. Björklund, A., Roine, J., Waldenström, D.: Intergenerational top income mobility in Sweden: capitalist dynasties in the land of equal opportunity? J. Public Econ. 96, 474–484 (2012)CrossRefGoogle Scholar
  17. Black, S.E., Devereux, P.J.: Recent developments in intergenerational mobility. In: Ashenfelter, O., Card, D. (eds.) Handbook of Labour Economics, vol. 4B, pp. 1487–1541. Elsevier, Amsterdam (2011)Google Scholar
  18. Böckerman, P., Viinikainen, J., Vainiomäki, J., Hintsanen, M., Pitkänen, N., Lehtimäki, T., Pehkonen, J., Rovio, S., Raitakari, O.: Stature and long-term labor market outcomes: evidence using Mendelian randomization. Econ. Hum. Biol. 24, 18–29 (2017)CrossRefGoogle Scholar
  19. Böhlmark, A., Lindquist, M.: Life-cycle variations in the association between current and lifetime income: replication and extension for Sweden. J. Labor Econ. 24, 879–896 (2006)CrossRefGoogle Scholar
  20. Bowles, S., Gintis, H.: The inheritance of inequality. J. Econ. Perspect. 16, 3–30 (2002)CrossRefGoogle Scholar
  21. Branigan, A.R., McCallum, K.J., Freese, J.: Variation in the heritability of educational attainment: an international meta-analysis. Soc. Forces. 92, 109–140 (2013)CrossRefGoogle Scholar
  22. Cesarini, D., Essays on genetic variation and economic behavior. Ph.D thesis, MIT (2010)Google Scholar
  23. Cesarini, D., Dawes, C., Johannesson, M., Lichtenstein, P., Wallace, B.: Genetic variation in preferences for giving and risk taking. Q. J. Econ. 124, 809–842 (2009)CrossRefGoogle Scholar
  24. Cesarini, D., Johannesson, M., Lichtenstein, P., Sandewall, Ö., Wallace, B.: Genetic variation in financial decision making. J. Financ. 65, 1725–1754 (2010)CrossRefGoogle Scholar
  25. Chetty, R., Hendren, N., Kline, P., Saez, E., Turner, N.: Is the United States still a land of opportunity? Recent trends in intergenerational mobility. Am. Econ. Rev. 104(Papers and Proceedings, 141–147 (2014)CrossRefGoogle Scholar
  26. Chetty, R., Hendren, N., Lin, F., Majerovitz, J., Scuderi, B.: Childhood environment and gender gaps in adulthood. Am. Econ. Rev. 106 (Papers and Proceedings, 282–288 (2016)CrossRefGoogle Scholar
  27. Cronqvist, H., Siegel, S.: The origins of savings behavior. J. Polit. Econ. 123, 123–169 (2015)CrossRefGoogle Scholar
  28. DeFries, J., Fulker, D.: Multiple regression analysis of twin data. Behav. Genet. 15, 467–473 (1985)CrossRefGoogle Scholar
  29. Goldberger, A.: Heritability. Economica. 46, 327–347 (1979)CrossRefGoogle Scholar
  30. Goldin, C.: A grand gender convergence: its last chapter. Am. Econ. Rev. 104, 1091–1119 (2014)CrossRefGoogle Scholar
  31. Haider, S., Solon, G.: Life-cycle variation in the association between current and lifetime earnings. Am. Econ. Rev. 96, 1308–1320 (2006)CrossRefGoogle Scholar
  32. Harding, D., Jencks, C., Lopoo, L.M., Mayer, S.M.: The changing effect of family bacground on the incomes of American adults. In: Bowles, S., Gintis, H., Osborne, M. (eds.) Unequal Chances: Family Background and Economic Success, pp. 100–144. Russell Sage Foundation, New York (2005)Google Scholar
  33. Heckman, J., Stixrud, J., Urzua, S.: The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior. J. Labor Econ. 24, 411–482 (2006)CrossRefGoogle Scholar
  34. Hyytinen, A., Ilmakunnas, P., Toivanen, O.: The returns to entrepreneurship puzzle. Labour Econ. 20, 57–67 (2013)CrossRefGoogle Scholar
  35. Isacsson, G.: Estimates of the return to schooling in Sweden from a large sample of twins. Labour Econ. 6, 471–489 (1999)CrossRefGoogle Scholar
  36. Jäntti, M., Jenkins, S.P.: Income mobility. In: Atkinson, A.B., Bourguignon, F. (eds.) Handbook of Income Distribution, vol. 2, pp. 807–935. Elsevier, Amsterdam (2015)Google Scholar
  37. Jäntti, M., Österbacka, E., Raaum, O., Eriksson, T., Björklund, A.: Brother correlations in earnings in Denmark, Finland, Norway and Sweden compared to the United States. J. Popul. Econ. 15, 757–772 (2002)CrossRefGoogle Scholar
  38. Johnson, W., Krueger, R.F.: Genetic effects on physical health: lower at higher income levels. Behav. Genet. 35, 579–590 (2005)CrossRefGoogle Scholar
  39. Kaprio, J.: The Finnish twin cohort study: an update. Twin Res. Hum. Genet. 16, 157–162 (2013)CrossRefGoogle Scholar
  40. Kaprio, J., Koskenvuo, M.: Genetic and environmental factors in complex diseases: the older Finnish twin cohort. Twin Res. 5, 358–365 (2002)CrossRefGoogle Scholar
  41. Kaprio, J., Koskenvuo, M., Artimo, M., Sarna, S., Rantasalo, I., The Finnish twin registry: Baseline characteristics. Section I. Materials, methods, representativeness and results for variables special to twin studies. Department of Public Health, University of Helsinki, Series M 47 (1979)Google Scholar
  42. Killingsworth, M.R., Heckman, J.J.: Female labor supply: a survey. In: Ashenfelter, O.C., Layard, R. (eds.) Handbook of Labor Economics, vol. 1, pp. 103–204. Amsterdam, Elsevier (1986)CrossRefGoogle Scholar
  43. Kohler, H., Rodgers, G.: DF-analyses of heritability with double-entry twin data: asymptotic standard errors and efficient estimation. Behav. Genet. 31, 179–192 (2001)CrossRefGoogle Scholar
  44. LaBuda, M.C., DeFries, J.C., Fulker, D.W.: Multiple regression analysis of twin data obtained from selected samples. Genet. Epidemiol. 3, 425–433 (1986)CrossRefGoogle Scholar
  45. Landersø, R., Heckman, J.J.: The Scandinavian fantasy: The sources of intergenerational mobility in Denmark and the U.S. Scand. J. Econ. 119, 178–230 (2017)CrossRefGoogle Scholar
  46. Lucas, R.E.B., Pekkala Kerr, S.: Intergenerational income immobility in Finland: contrasting roles for parental earnings and family income. J. Popul. Econ. 26, 1057–1094 (2013)CrossRefGoogle Scholar
  47. Manski, C.: Genes, eyeglasses, and social policy. J. Econ. Perspect. 25, 83–94 (2011)CrossRefGoogle Scholar
  48. Mazumder, B.: Fortunate sons: new estimates of intergenerational mobility in the United States using social security earnings data. Rev. Econ. Stat. 87, 235–255 (2005)CrossRefGoogle Scholar
  49. Miller, P., Mulvey, C., Martin, N.: What do twins studies reveal about the economic returns to education? A comparison of Australian and U.S. findings. Am. Econ. Rev. 85, 586–599 (1995)Google Scholar
  50. Miller, P., Mulvey, C., Martin, N.: Multiple regression analysis of the occupational status of twins: a comparison of economic and behavioral genetic models. Oxford B. Econ. Stat. 58, 227–239 (1996)CrossRefGoogle Scholar
  51. Miller, P., Mulvey, C., Martin, N.: Family characteristics and the returns to schooling: evidence on gender differences from a sample of Australian twins. Economica. 64, 137–154 (1997)CrossRefGoogle Scholar
  52. Miller, P., Mulvey, C., Martin, N.: Genetic and environmental contributions to educational attainment in Australia. Econ. Educ. Rev. 20, 211–224 (2001)CrossRefGoogle Scholar
  53. Miller, P., Mulvey, C., Martin, N.: The returns to schooling: estimates from a sample of young Australian twins. Labour Econ. 13, 571–587 (2006)CrossRefGoogle Scholar
  54. Moffitt, R.A., Gottschalk, P.: Trends in the transitory variance of male earnings: methods and evidence. J. Hum. Resour. 47, 204–236 (2012)Google Scholar
  55. Nicolaou, N., Shane, S., Cherkas, L., Hunkin, J., Spector, T.: Is the tendency to engage in entrepreneurship genetic? Manag. Sci. 54, 167–179 (2008)CrossRefGoogle Scholar
  56. Nilsen, Ø.A., Vaage, K., Aakvik, A., Jacobsen, K.: Intergenerational earnings mobility revisited: estimates based on lifetime earnings. Scand. J. Econ. 114, 1–23 (2012)CrossRefGoogle Scholar
  57. Ørstavik, R.E., Czajkowski, N., Røysamb, E., Knudsen, G.P., Tambs, K., Reichborn-Kjennerud, T.: Sex differences in genetic and environmental influences on educational attainment and income. Twin Res. Hum. Genet. 17, 516–525 (2014)CrossRefGoogle Scholar
  58. Pekkarinen, T., Uusitalo, R., Pekkala Kerr, S.: School tracking and intergenerational income mobility: evidence from the Finnish comprehensive school reform. J. Public Econ. 93, 965–973 (2009)CrossRefGoogle Scholar
  59. Piketty, T., Saez, E.: Income inequality in the United States, 1913–1998. Q. J. Econ. 118, 1–41 (2003)CrossRefGoogle Scholar
  60. Plomin, R.: Commentary: why are children in the same family so different? Non-shared environment three decades after. Int. J. Epidemiol. 40, 582–592 (2011)CrossRefGoogle Scholar
  61. Plomin, R., Kovas, Y.: Generalist genes and learning disabilities. Psychol. Bull. 131, 592–617 (2005)CrossRefGoogle Scholar
  62. Plomin, R., Shakeshaft, N.G., McMillan, A., Trzaskowski, M.: Nature, nurture, and expertise. Intelligence. 45, 46–59 (2014)CrossRefGoogle Scholar
  63. Plug, E., Vijverberg, V.: Schooling, family background, and adoption: is it nature or is it nurture? J. Polit. Econ. 111, 611–641 (2003)CrossRefGoogle Scholar
  64. Posthuma, D., Beem, A.L., de Geus, E.J.C., van Baal, G.C.M., von Hjelmborg, J.B., Iachine, I., Boomsma, D.I.: Theory and practice in quantitative genetics. Twin Res. 6, 361–376 (2003)CrossRefGoogle Scholar
  65. Rodgers, J., Kohler, H.: Reformulating and simplifying the DF analysis model. Behav. Genet. 35, 211–217 (2005)CrossRefGoogle Scholar
  66. Rodgers, J., McGue, H.: A simple algebraic demonstration of the validity of the DeFries-Fulker analysis in unselected samples with multiple kinship levels. Behav. Genet. 24, 259–262 (1994)CrossRefGoogle Scholar
  67. Rodgers, J., Kohler, H., Kyvik, K., Christiansen, K.: Modelling of human fertility: findings from a contemporary Danish twin study. Demography. 38, 29–42 (2001)CrossRefGoogle Scholar
  68. Sacerdote, B.: The nature and nurture of economic outcomes. Am. Econ. Rev. 92(Papers and Proceeedings, 344–348 (2002)CrossRefGoogle Scholar
  69. Sacerdote, B.: How large are the effects from changes in family environment? A study of Korean American adoptees. Q. J. Econ. 122, 119–157 (2007)CrossRefGoogle Scholar
  70. Sacerdote, B.: Nature and nurture effects on children's outcomes: what have we learned from studies of twins and adoptees? In: Benhabib, J., Bisin, A., Jackson, M.O. (eds.) Handbook of Social Economics, pp. 1–30. Elsevier, Amsterdam (2011)Google Scholar
  71. Schnittker, J.: Happiness and success: genes, families, and the psychological effects of socioeconomic position and social support. Am. J. Sociol. 114, 233–259 (2008)CrossRefGoogle Scholar
  72. Shakeshaft, N.G., Trzaskowski, M., McMillan, A., Krapohl, E., Simpson, M.A., Reichenberg, A., Cederlöf, M., Larsson, H., Lichtenstein, P., Plomin, R.: Thinking positively: the genetics of high intelligence. Intelligence. 48, 123–132 (2015)CrossRefGoogle Scholar
  73. Simonson, I., Sela, A.: On the heritability of consumer decision making: an exploratory approach for studying genetic effects on judgment and choice. J. Consum. Res. 37, 951–966 (2011)CrossRefGoogle Scholar
  74. Solon, G.: Intergenerational mobility in the labor market. In: Ashenfelter, O.C., Card, D. (eds.) Handbook of Labor Economics, vol. 3A, pp. 1761–1800. Elsevier, Amsterdam (1999)Google Scholar
  75. Stenberg, A.: Interpreting estimates of heritability – a note on the twin decomposition. Econ. Hum. Biol. 11, 201–205 (2013)CrossRefGoogle Scholar
  76. Taubman, P.: The determinants of earnings: genetics, family, and other environments: a study of white male twins. Am. Econ. Rev. 66, 858–870 (1976)Google Scholar
  77. Visscher, P.M., Medland, S.E., Ferreira, M.A.R., Morley, K.I., Zhu, G., Cornes, B.K., Montgomery, G.W., Martin, N.G.: Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings. PLoS Genet. 2(3), e41 (2006)CrossRefGoogle Scholar
  78. Waller, N.: A DeFries and Fulker regression model for genetic nonadditivity. Behav. Genet. 24, 149–153 (1994)CrossRefGoogle Scholar

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Authors and Affiliations

  • Ari Hyytinen
    • 1
    • 2
  • Pekka Ilmakunnas
    • 2
    • 3
    Email author
  • Edvard Johansson
    • 4
  • Otto Toivanen
    • 2
    • 5
  1. 1.Department of EconomicsHanken School of EconomicsHelsinkiFinland
  2. 2.Finland and Helsinki GSEHelsinkiFinland
  3. 3.Aalto University School of BusinessEspooFinland
  4. 4.Faculty of Social Sciences, Business and EconomicsÅbo Akademi UniversityTurkuFinland
  5. 5.Aalto University School of BusinessHelsinkiFinland

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