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PSYCHOLOGY
Experiments investigating cooperative types in humans: A complement to evolutionary theory and simulations

Robert Kurzban ^* , , and Daniel Houser ^, 

^*Department of Psychology, University of Pennsylvania, 3720 Walnut Street, Philadelphia, PA 19104; and Interdisciplinary Center for Economic Science and Department of Economics, George Mason University, 4400 University Drive, MSN 1B2, Fairfax, VA 22030

Communicated by Elinor Ostrom, Indiana University, Bloomington, IN, November 29, 2004 (received for review January 22, 2004)

Unlike other species, humans cooperate in large, distantly related groups, a fact that has long presented a puzzle to biologists. The pathway by which adaptations for large-scale cooperation among nonkin evolved in humans remains a subject of vigorous debate. Results from theoretical analyses and agent-based simulations suggest that evolutionary dynamics need not yield homogeneous populations, but can instead generate a polymorphic population that consists of individuals who vary in their degree of cooperativeness. These results resonate with the recent increasing emphasis on the importance of individual differences in understanding and modeling behavior and dynamics in experimental games and decision problems. Here, we report the results of laboratory experiments that complement both theory and simulation results. We find that our subjects fall into three types, an individual's type is stable, and a group's cooperative outcomes can be remarkably well predicted if one knows its type composition. Reciprocal types, who contribute to the public good as a positive function of their beliefs about others' contributions, constitute the majority (63%) of players; cooperators and free-riders are also present in our subject population. Despite substantial behavioral differences, earnings among types are statistically identical. Our results support the view that our human subject population is in a stable, polymorphic equilibrium of types.

behavioral economics | cooperation | evolution | public goods

R.K. and D.H. contributed equally to this work.

^¶ Houser, Keane, and McCabe (17) provide a type classification algorithm that does not require one to specify the types of interest a priori.

^|| The R-squared values for the type regressions ranged from 0to 1, with a mean of 0.4.

^** The standard deviations of the earnings distributions for free-riders, cooperators, and reciprocators are 18, 19, and 24, respectively.

Each estimated model was statistically significant (P < 0.001) with pseudo R-squared 0.02.

Using the in-sample data, we ran a regression of the final contribution amount on an intercept and the group cooperativeness score. The coefficients' point estimates were 11 and 21, respectively, with only the 21 statistically significant (P < 0.001). The same regression run on the out-of-sample data generated coefficient estimates of 10 and 25, respectively, with only 25 statistically significant (P < 0.01). The null hypothesis that the models' parameters are jointly identical in the two cases cannot be rejected at standard significance levels (P = 0.59). The R-squared for both regressions is 0.22.

We ran pairwise, round-by-round t tests to investigate differences in mean contribution paths. Differences were statistically insignificant in all cases except rounds 1–8 between the score-2 and score-5 groups (P < 0.05).

To whom correspondence should be addressed. E-mail: kurzban{at}psych.upenn.edu.

© 2005 by The National Academy of Sciences of the USA

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