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You’ve earned it: estimating the impact of human capital on social preferences

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Abstract

We combine data from a randomized evaluation and a laboratory experiment to measure the causal impact of human capital on respect for earned property rights, a component of social preferences with important implications for economic growth and development. We find that higher academic achievement reduces the willingness of young Kenyan women to appropriate others’ labor income, and shifts players toward a 50–50 split norm in a modified dictator game. This study demonstrates that education may have long-run impacts on social preferences, norms and institutions beyond the human capital directly produced.

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Notes

  1. See also Inkeles and Smith (1974). More generally, Easterlin (1981) argues that the introduction of mass primary education has preceded industrialization in most developed economies. Goldin and Katz (2008) trace out how the expansion of public education contributed to the economic and social transformation of U.S. society.

  2. Barr et al. (2012) use public goods games to measure the impact of a school committee monitoring intervention in Uganda; while Fearon et al. (2009) use similar experiments to measure the impact of a post-conflict community development initiative in Liberia. Paluck et al. (2009) demonstrate that randomized experiments can be used to demonstrate the efficacy of policies explicitly intended to change cultural norms.

  3. Friedman et al. (2011) use a similar identification strategy to explore the impact of the GSP on political attitudes, knowledge, and behavior.

  4. See Henrich et al. (2010b) for an overview of the ways in which subjects in western university experimental labs are not representative of humanity in general.

  5. Cherry (2001), Cherry et al. (2002), and List and Cherry (2008) conduct similar earnings treatments. Fahr and Irlenbusch (2000), Konow (2000), and Cappelen (2007) also explore distributional preferences governing earned income.

  6. Building on Locke (1980[1690]), Gintis (2007) models “preinstitutional” property rights as the equilibrium result of the interaction between the endowment effect and possession. Following Fahr and Irlenbusch (2000), we refer to the entitlement effect generated by our design as an “earned property right.”

  7. The design is quite similar to a trust game involving real effort rather than investment, except that receivers can only generate payoffs for themselves by “trusting” their labor income to the dictator.

  8. Prior to the introduction of free primary education, the gross primary enrollment rate was approximately 90 %. See Lucas and Mbiti (2012) for an extended discussion of the abolition of school fees in Kenya.

  9. The exams are not required, and students must pay a fee of between 1 and 2 USD to participate in each practice exam.

  10. A parallel randomized experiment was simultaneously conducted in neighboring Teso district (Kremer et al. 2009), but since it is unclear whether the scholarship increased human capital in this district, in part due to program implementation difficulties there, follow-up surveys were only conducted in the Busia district. For that reason, we only have actual KCPE scores for Busia students, and we focus only on that experiment in this paper.

  11. Only those girls who were enrolled in standards 5 and 6 in treatment schools in January 2001 were eligible for scholarships. This restriction was imposed to avoid creating incentives for girls to transfer from control to treatment schools.

  12. Administrative data on past KCPE scores is not publicly available from any centralized source. Because many girls took the KCPE exam in different years and might have changed schools, it was not feasible to collect hard copy records of KCPE scores for all the schools that GSP respondents might have attended.

  13. In our sample, GSP treatment is associated with an 8.3 % point increase in the likelihood of being in school, but the effect is not significant. This estimated impact is very similar to the 7.9 % point effect reported in Friedman et al. (2011).

  14. Ozier (2010) reports that scoring above the mean on the KCPE increases the probability of completing secondary school by 20 % points. Test scores are arguably more relevant as an indicator of quality, rather than quantity, of education: Barro (2001) and Hanushek and Kimko (2000) both find that test scores on internationally comparable exams are more predictive of future income growth rates than years of schooling.

  15. Unfortunately, Kenyan secondary schools do not conduct regular standardized tests that could be used to provide a more recent measure of academic achievement. Because those subjects attend secondary schools which vary in quality, grade point averages and class ranks would not be comparable.

  16. Our design is identical to that used in Jakiela (2009), which was motivated by Ruffle (1998) and Fiona (2006). Hoffman et al. (1994), Cherry (2001), Cherry et al. (2002), and List and Cherry (2008) conduct dictator games in which subjects divide their own earned income between self and other; they find that the amount allocated to other is lower when the dictator’s endowment is earned. Bardsley (2008), List (2007), and Fisman et al. (2014) conduct modified dictator games which allow for both giving and taking.

  17. We also piloted the three other variants of the dictator game proposed in Jakiela (2009). However, we did not locate large enough numbers of potential participants to be able to carry out all four treatments. (Each session lasted approximately 3 h, and each subject participated in only one treatment.) We chose to focus on the treatment described here because it is in that treatment that Jakiela (2009) finds an association between education and allocation decisions. In any potential analysis of the pilot data from the other three treatments, we face a weak instrument problem in the first stage regression because of the limited sample size.

  18. We opted for a non-cognitive task so that output would reveal minimal information about education or innate intelligence. The task was inspired by Ariely et al. (2009), but adapted to a non-computerized environment. Other non-cognitive tasks which have been used in experimental settings include stuffing envelopes (Konow 2000; Falk and Ichino 2006) and cracking walnuts (Fahr and Irlenbusch 2000).

  19. Interestingly, Jakiela (2009) finds no evidence that subjects exert less effort when they expect that another may appropriate a portion of their earnings.

  20. Thus, all subjects make allocation decisions which might determine final payoffs—this was necessary because of our small sample size. In contrast to Andreoni and Miller (2002) and Fisman et al. (2007), subjects in our experiment do not receive two sets of tokens (one based on their own decision and one based on the decision of another subject). Instead, each subject within a matched pair makes an allocation decision, and one of the two decisions is randomly chosen to determine payouts, as in Cappelen (2007). The amount of money being allocated is determined by the effort level of the subject whose decision is not chosen to determine payouts.

  21. Even after omitting 15 subjects in the GSP treatment group who won the scholarship, we still observe a significant relationship between random assignment to the GSP treatment group and the amount allocated to other. Subjects in the GSP treatment group who did not win the scholarship allocate other an average of 33.9 % of the budget (p value from a test of equality with the mean allocation to other made by subjects in the GSP control group \(<0.001\)).

  22. Age controls include both age in 2008 (normalized) and an indicator for being in the first GSP cohort. Studies by Fehr et al. (August 2008), Almas et al. (2010), Bekkers (2007), and Fowler (2006) suggest that age is an important predictor of altruistic behaviors. Ethnicity controls are indicators for being a member of a minority ethnic group (Teso or Luo) and for belonging to a minority subgroup of the locally dominant Luhya ethnic group.

  23. This GSP treatment effect on test scores is larger than the roughly 0.2–0.3 standard deviations effect reported in Friedman et al. (2011) for the full GSP follow-up survey sample. Sampling variation is a likely explanation for the discrepancy, given our limited subsample of 101 lab subjects.

  24. Following Deaton (1997), we choose a reasonable bandwith by trial and error, since the figure is for illustrative purposes only.

  25. Beliefs were elicited through survey questions and not in an incentive-compatible manner. However, the average belief reported in the survey is not significantly associated with the average amount a subject allocated to her partner. Moreover, beliefs are substantially higher, on average, than actual allocations, despite potential self- and social- image motivations to underestimate others’ generosity. Thus we believe the beliefs data are reliable.

  26. A Hausman test rejects the equality of the IV and OLS coefficients with 90 % confidence (p value \(0.065\)) when the full set of controls is included in the regressions, as in column 3.

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Acknowledgments

We thank Raymond Fisman, Shachar Kariv, and numerous conference and seminar participants for helpful comments. Francois Gerard provided excellent research assistance. All errors are our own.

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Authors and Affiliations

  1. University of Maryland, College Park, MD, USA

    Pamela Jakiela

  2. University of California, Berkeley, CA, USA

    Edward Miguel & Vera L. te Velde

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  1. Pamela Jakiela
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Correspondence to Pamela Jakiela.

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Jakiela, P., Miguel, E. & te Velde, V.L. You’ve earned it: estimating the impact of human capital on social preferences. Exp Econ 18, 385–407 (2015). https://doi.org/10.1007/s10683-014-9409-9

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