The Nature and Nurture of Generosity What can we learn from behavioral genetics? René Bekkers Center for Philanthropic Studies VU University Amsterdam M&T Lunch, December 20, 2016

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. December 20, 2016 M&T Lunch

December 20, 2016 M&T Lunch

December 20, 2016 M&T Lunch

December 20, 2016 M&T Lunch

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? December 20, 2016 M&T Lunch

Prosocial behavior Formal: philanthropy Informal: helping Money Time Financial Care December 20, 2016 M&T Lunch

Prosocial behavior Formal: philanthropy Informal: helping Money Time Financial Care December 20, 2016 M&T Lunch

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): 924-973. Available at www.understandingphilanthropy.com December 20, 2016 M&T Lunch

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 December 20, 2016 M&T Lunch

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? December 20, 2016 M&T Lunch

Selection and causation Education Behavior IQ, Other factors December 20, 2016 M&T Lunch

All selection, no causation Education Behavior IQ, Other factors December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

Selection, causation, mediation Mediating variable Education Behavior IQ, other factors Another mediating variable December 20, 2016 M&T Lunch

December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

December 20, 2016 M&T Lunch

The ideal experiment would randomize education VWO = higher secondary education (≤ gymnasium) VMBO = lower vocational education December 20, 2016 M&T Lunch

Monozygotic twins December 20, 2016 M&T Lunch

The unique environmental influence of education Note that shared environmental influences are also excluded by design in this analysis December 20, 2016 M&T Lunch

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% December 20, 2016 M&T Lunch

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” December 20, 2016 M&T Lunch

December 20, 2016 M&T Lunch

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 December 20, 2016 M&T Lunch

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). December 20, 2016 M&T Lunch

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: 10.3389/fnhum.2013.00242 December 20, 2016 M&T Lunch

Geneticists analyzed 2,165,398 single nucleotide polymorphisms and found NONE tellling us who is a friendly person https://twitter.com/renebekkers/status/806922437250011136 December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

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) December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

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). December 20, 2016 M&T Lunch

Environment mediation model Religiousness E Prosocial behavior Education Note that this is a unique environment mediation model December 20, 2016 M&T Lunch

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 25-74 living in the US who were physically and mentally able to complete the interview were allowed to participate. December 20, 2016 M&T Lunch

Assessing zygosity December 20, 2016 M&T Lunch

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 December 20, 2016 M&T Lunch

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 December 20, 2016 M&T Lunch

ACE model for volunteer hours December 20, 2016 M&T Lunch

ACE model for volunteer hours December 20, 2016 M&T Lunch

ACE model for volunteer hours December 20, 2016 M&T Lunch

ACE model for volunteer hours December 20, 2016 M&T Lunch

ACE model for volunteer hours December 20, 2016 M&T Lunch

ACE model for volunteer hours December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

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 December 20, 2016 M&T Lunch

The higher educated volunteer more Again, large differences – 4 to 6 times December 20, 2016 M&T Lunch

The religious give more Religious giving is included in this figure. Excluding donations to religion, the differences are much smaller. December 20, 2016 M&T Lunch

The religious volunteer more This figure includes volunteering for religious organizations. December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

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) December 20, 2016 M&T Lunch

Education and giving December 20, 2016 M&T Lunch

December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

Education and giving among MZs December 20, 2016 M&T Lunch

Education estimates on total giving December 20, 2016 M&T Lunch

Education and volunteering *** *** *** p <.001 December 20, 2016 M&T Lunch

Church attendance and giving *** *** *** *** *** *** *** December 20, 2016 M&T Lunch

Church attendance and volunteering December 20, 2016 M&T Lunch

Strength of religiosity and giving (*) (*) p <.10 December 20, 2016 M&T Lunch

Religiosity and volunteering *** *** *** *** ** * *** p <.001 ** p <.01; * p < .05; (*) p < .10 December 20, 2016 M&T Lunch

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December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

…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. December 20, 2016 M&T Lunch

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). December 20, 2016 M&T Lunch

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%). December 20, 2016 M&T Lunch

Future directions Replicate this finding using data from other samples of twins, in the US and beyond. Examine other dependent variables using this method: trust, subjective well being, prosocial values... December 20, 2016 M&T Lunch

Schooling effects on income December 20, 2016 M&T Lunch

Education effects on religion December 20, 2016 M&T Lunch

René Bekkers Center for Philanthropic Studies VU University Amsterdam r.bekkers@vu.nl Blog: http://renebekkers.wordpress.com Twitter: @renebekkers

References Bekkers, R. & Dursun, E. (2013). “A Brief History of Research on Philanthropy.” http://www.understandingphilanthropy.com Felson, J. (2014). “What can we learn from twin studies? A comprehensive evaluation of the equal environments assumption.” Social Science Research, 43: 184-199. Gibson, J. (2001). “Unobservable Family Effects and the Apparent External Benefits of Education.” Economics of Education Review, 20: 225-233. 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: 265-290. 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. December 20, 2016 M&T Lunch

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: 436-440. Behrman, J. & Rosenzweig, M.R. (1999). “Ability biases in schooling returns and twins: a test and new estimates.” Economics of Education Review, 18: 159-167. Bonjour, D., Cherkas, L., Haskel, J., Hawkes, D., & Spector, T. (2003). “Returns to Education: Evidence from UK Twins.” American Economic Review, 93: 1799-1812. Isacsson, G. (1999). “Estimates of the Return to Schooling in Sweden from a Large Sample of Twins.” Labour Economics, 6: 471-489. 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: 586-599. December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

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. December 20, 2016 M&T Lunch

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Informal prosocial behaviors Perhaps Americans with less education know more people in need of support? December 20, 2016 M&T Lunch

Informal prosocial behaviors Perhaps Americans who attend church less often know more people in need of financial assistance and support? December 20, 2016 M&T Lunch

December 20, 2016 M&T Lunch

December 20, 2016 M&T Lunch