1. The Nature and Nurture of Generosity What can we learn from behavioral genetics?
René Bekkers
Center for Philanthropic Studies
VU University Amsterdam
Evolutionary and Social Psychology Seminar
December 19, 2016

2. Thanks
To the McArthur Foundation for funding the MIDUS data collection.
Colleagues who gave feedback: Dorret Boomsma, Dinand Webbink, Sara Konrath, Paul van Lange, Daniëlle Posthuma.
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4. Three questions
How alike are twins in the United States with respect to prosocial behavior?
Are differences among twins in giving and volunteering related to differences in education and religion?
If so, what explains these relationships?
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5. Prosocial behavior Formal: philanthropy Informal: helping Money Time
Financial
Care
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6. Prosocial behavior Formal: philanthropy Informal: helping Money Time
Financial
Care
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7. Number of publications per year about philanthropy by academic discipline (1899-2009)
Source: Bekkers & Dursun (2013), based on Bekkers & Wiepking (2011). ‘A Literature Review of Empirical Studies of Philanthropy: Eight Mechanisms that Drive Charitable Giving’. Nonprofit and Voluntary Sector Quarterly, 40(5): Available at
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8. Ubiquitous correlates of philanthropy
Religion:
Affiliation (yes>no)
Denomination (Protestant>Catholic)
Participation (church attendance)
Education:
Level achieved
The variance between fields of study is small
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9. Where do the correlations originate?
The more general research questions:
Why are religion and education correlated with prosocial behavior?
To what extent are these relationships the result of environmental influences?
Are these relationships causal?
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10. Selection and causation
Education
Behavior
IQ,
Other factors
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11. All selection, no causation
Education
Behavior
IQ,
Other factors
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12. Selection and Causation
Education
Factors X 1…n
Participation
About 60%?
IQ, parental income, social science classes, college plans, extraversion, openness to experience
Bekkers, R. & Ruiter, S. (2008). ‘Education and voluntary association participation: Evidence for selection and causation’. Paper presented at the 103d ASA Annual Meeting, Boston, August 2, 2008.
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13. Selection, causation, mediation
Mediating variable
Education
Behavior
IQ, other factors
Another mediating variable
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14. December 19, 2016
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15. Three ‘theories’ on philanthropy
Philanthropy varies between social groups
because the resources of group members vary;
because the social values of groups vary;
because members of different groups have different self-identities.
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17. The ideal experiment would randomize education
VWO = higher secondary education (≤ gymnasium)
VMBO = lower vocational education
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18. Monozygotic twins
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19. The unique environmental influence of education
Note that shared environmental influences are also excluded by design in this analysis
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20. What behavioral geneticists do: the ACE model
Additive genetic effects
Typically 40-60% C
Common (shared) environmental effects
Typically less than 10% (often zero) E
Unique (non-shared) environmental effects (including measurement error)
Typically 30-50%
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21. Note
The first law of behavior genetics, as formulated by Eric Turkheimer (2000):
“All human behavioral traits are heritable”
Eva Krapohl in a recent interview in The Atlantic:
“Heritability describes what is; it does not predict what could be”
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22. December 19, 2016
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23. ACE mediated effects model
Religiousness C
Prosocial behavior E A C E
Total effect on prosocial behavior
10.2
27.6
62.3
Mediated by religiousness
7.5
(73.5%)
13.6
(49.3%)
2.9
(4.7%)
Koenig et al., 2007; n= 165 MZ and 100 DZ twin pairs
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24. Biometric model fitting
Fit statistics of various biometric models are compared to identify the best-fitting model.
Models depend on assumptions such as the Equal Environments Assumption.
The EEA is often disputed theoretically.
Empirical tests show it is often violated.
The resulting bias, however, seems to be minor (see Felson, Soc.Sc.Res., 2014).
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25. What molecular geneticists do
Genome Wide Association Studies (GWAS): identify ‘candidate genes’ that could explain variance in some outcome variable.
Typically, individual genes like OXTR and DRD4 explain tiny fractions of variance (<1%).
Typically, all single nucleotide polymorphisms (SNPs) combined explain less variance (16% of education) than estimated in biometric models (35%) – ‘missing heritability’ problem.
Reuter et al. (2013, Frontiers in Human Neuroscience): “The DRD4 gene consists of 3400 base pairs (bp), is located at chromosome 11p15.5, and codes for the dopamine D4 receptor.” doi: /fnhum
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26. Geneticists analyzed 2,165,398 single nucleotide polymorphisms and found NONE tellling us who is a friendly person
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27. Where is the social science?
In the variance explained by shared and unique environmental factors.
Let us rule out genetic effects by looking at monozygotic twins only.
Any difference between MZ twins must have roots in the unique environment.
This choice avoids problems with the EEA.
Note that MZ twins also share 100% of shared environmental effects.
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28. The problem
“…families whose unobservable characteristics cause them to have a high likelihood of volunteering are also more likely to educate their children, so the relationship between schooling and volunteering is just a correlation caused by an excluded common cause.”
John Gibson (2001)
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29. This is not my idea
In 2001, New Zealand economist John Gibson published a study of volunteering among 85 identical twin pairs.
Though education in the pooled sample is associated with more volunteering, pairwise comparisons reveal the opposite.
The twin with more years of education was found to volunteer fewer hours.
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30. The implication
Genetic effects cause a positive association between education and volunteering.
Unique environmental effects of education on volunteering are negative in this sample.
One interpretation of the negative effect is that it is the result of the opportunity cost of volunteering, potentially amplified by a decision making process within the household.
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31. Related literature
The twin fixed effects model has been used in economics to estimate the influence of schooling on income since the 1970s (Behrman & Taubman, 1976; Ashenfelter & Kreuger, 1994; Ashenfelter & Rouse, 1998; Isacsson, 1999; Miller, Mulvey & Martin, 1995; Bonjour et al., 2003).
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32. Environment mediation model
Religiousness E
Prosocial behavior
Education
Note that this is a unique environment mediation model
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33. The MIDUS data
Two wave longitudinal panel survey on Midlife in the United States (1995 and 2005) sponsored by the McArthur Foundation.
The RDD sample selection procedure included twin screening questions.
Only English-speaking respondents aged living in the US who were physically and mentally able to complete the interview were allowed to participate.
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34. Assessing zygosity
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35. Are twins different at all?
Yes – here’s the discordance table:
Education
Religious affiliation MZ
55%
50% DZ
64%
53%
Proportions of respondents from the same twin pair not reporting exactly the same level of education and religious affiliation
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36. ACE model results A C E Education 29.8 38.6 31.5
Strength of religiosity
22.8
32.7
39.3
Frequency of church attendance
46.7
53.3
Amount donated ($)
33.7
66.3
Hours volunteered
15.8
84.2
Financial assistance to friends / family
17.7
82.3
Hours helping friends / family
26.6
73.5
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37. ACE model for volunteer hours
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38. ACE model for volunteer hours
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39. ACE model for volunteer hours
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40. ACE model for volunteer hours
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41. ACE model for volunteer hours
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42. ACE model for volunteer hours
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43. Remember
“Heritability describes what is; it does not predict what could be”.
These are the results of educational careers and systems for those in midlife in the US.
“All human behavioral traits are heritable”.
25% is not much compared to 75% for IQ.
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44. The higher educated give more
These differences are massive: amounts donated in the top category are nine times the amount donated in the lowest category
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45. The higher educated volunteer more
Again, large differences – 4 to 6 times
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46. The religious give more
Religious giving is included in this figure. Excluding donations to religion, the differences are much smaller.
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47. The religious volunteer more
This figure includes volunteering for religious organizations.
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48. Two basic regression models
Between effects model: ignores the twin pair structure, replicates bivariate analyses. Includes genetic + shared and unique environmental effects (ACE).
Within MZ twin fixed effects model: does the higher educated / more religious twin of an MZ pair give and volunteer more than the less educated / religious co-twin? Includes only unique environmental effects.
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49. Regressors Church attendance (times per year)
Religious affiliation: none (reference), Catholic, Protestant, Other (0-1)
Level of education (1-12)
Strength of religiosity (z-standardized)
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50. Education and giving
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52. Two further models
Reduced form within MZ twin model: excludes religious denomination dummies, retaining education, church attendance and strength of religiosity.
Mediated reduced form within MZ twin model: adds social responsibility, prosocial self-identity, household income, and assets.
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53. Education and giving among MZs
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54. Education estimates on total giving
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55. Education and volunteering
***
***
*** p <.001
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56. Church attendance and giving
***
***
***
***
***
***
***
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57. Church attendance and volunteering
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58. Strength of religiosity and giving
(*)
(*) p <.10
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59. Religiosity and volunteering
***
***
***
*** ** *
*** p <.001
** p <.01;
* p < .05;
(*) p < .10
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62. Conclusions
The association between the level of education and giving and volunteering is due to genetic or shared environmental effects.
The association between religiosity and charitable giving is due to unique environmental effects, but it is limited to church contributions.
Religiosity nurtures volunteering, also beyond religious organizations.
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63. Mediation
Education hardly mediates unique environmental influences on giving or volunteering.
Religion mediates unique environmental influences on giving but not on volunteering.
Education effects are partly mediated by income and assets.
Religiosity effects are not mediated by prosocial self-identity, nor by prosocial values.
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64. Or vice versa Perhaps volunteering nurtures religiosity.
Or perhaps an omitted (shared?) environmental effect nurtures volunteering and religiosity.
We cannot infer causality from the twin fixed effects model.
But we can look at changes in religiosity and volunteering between the three waves.
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65. …and?
Respondents who quit volunteering between the first and the second wave are less frequently attending church and report lower strength of religiosity in the second wave than in the first wave.
Respondents who started volunteering are more frequently attending church in the second wave.
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66. The measurement error problem
Could differential measurement error explain the pattern of results?
That is unlikely. The test-retest correlation of education is higher (.87) than that of the frequency of church attendance (.72). It is similar to strength of religiosity (.84).
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67. The variance problem
Could a differential lack of variance explain the pattern of results?
That is unlikely. MZ twins are more likely to be discordant with respect to education (55%) than with respect to religion (50%).
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68. Future directions
Replicate this finding using data from other samples of twins, in the US and beyond.
Add wave 2 and 3 measures.
Examine other dependent variables using this method: trust, subjective well being, prosocial values...
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69. René Bekkers Center for Philanthropic Studies VU University Amsterdam
Blog:

70. References
Bekkers, R. & Dursun, E. (2013). “A Brief History of Research on Philanthropy.”
Felson, J. (2014). “What can we learn from twin studies? A comprehensive evaluation of the equal environments assumption.” Social Science Research, 43:
Gibson, J. (2001). “Unobservable Family Effects and the Apparent External Benefits of Education.” Economics of Education Review, 20:
Koenig, L.B., McGue, M., Krueger, R.F., Bouchard, T.J. (2007). “Religiousness, Antisocial Behavior, and Altruism: Genetic and Environmental Mediation.” Journal of Personality, 75:
Reuter, M., Felten, A., Penz, S., Mainzer, A., Markett, S. & Montag, C. (2013). “The influence of dopaminergic gene variants on decision making in the ultimatum game.” Frontiers in Human Neuroscience, 7: 1-8.
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71. More references
Ashenfelter, O., & Krueger, A. (1994). “Estimates of the economic return to schooling from a new sample of twins.” American Economic Review, 84, 1157–1173.
Ashenfelter, O., & Rouse, C. (1998). “Income, schooling and ability: Evidence from a new sample of identical twins.” Quarterly Journal of Economics, 113, 153–284.
Behrman, J. & Taubman, P. (1976). “Intergenerational Transmission of Income and Wealth.” American Economic Review, 66:
Behrman, J. & Rosenzweig, M.R. (1999). “Ability biases in schooling returns and twins: a test and new estimates.” Economics of Education Review, 18:
Bonjour, D., Cherkas, L., Haskel, J., Hawkes, D., & Spector, T. (2003). “Returns to Education: Evidence from UK Twins.” American Economic Review, 93:
Isacsson, G. (1999). “Estimates of the Return to Schooling in Sweden from a Large Sample of Twins.” Labour Economics, 6:
Miller, P., Mulvey, C. & Martin, N. (1995). “What Do Twins Studies Reveal About the Economic Returns to Education? A Comparison of Australian and U.S. Findings." American Economic Review, 85:
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72. Measures
Donations. Donations to organizations were measured with the following question: “On average, about how many dollars per month do you or your family living with you contribute to each of the following people or organizations? If you contribute food, clothing, or other goods, include their dollar value. (If none, enter "0".)” After this introduction, donations to three categories of organizations were measured: (1) to religious groups; (2) to political organizations or causes; (3) to any other organizations, causes, or charities (including donations made through monthly payroll deductions)? Amounts donated per month were multiplied by 12 to obtain the total amount donated per year. The sum of these contributions is the variable for the total amount donated to organizations. A separate variable was created excluding donations to religion to see if the relationship between religion and philanthropy would also hold for ‘secular giving’. The test-retest correlation of the total amount donated measured in dollars is .25; for the logtransformed amounts the test-retest correlation is .44. For donations to organizations other than religion the test-retest correlation of the dollar amounts is .29; for the log-transformed amounts it is .39.
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73. Volunteering. The questions on volunteering in M1 and M2 asked about four types of formal volunteer work: ‘hospital, nursing home, or other health care-oriented work’, ‘school or other youth-related volunteer work’, ‘volunteer work for political organizations or causes’, and ‘volunteer work for any other organization, cause or charity’. While these questions did not explicitly identify religious organizations, respondents could report volunteering for religious organizations in the question about any ‘other’ organizations. A separate variable was created excluding potentially religious volunteering by computing the sum of hours volunteered in the first three types. The test-retest correlation of the total number of volunteer hours is .38; for the log-transformed hours the test-retest correlation is .46. For the hours volunteered in organizations other than religious organizations the test-retest correlation is .28; for the log-transformed variable it is .36.
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78. Informal prosocial behaviors
Perhaps Americans with less education know more people in need of support?
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79. Informal prosocial behaviors
Perhaps Americans who attend church less often know more people in need of financial assistance and support?
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