The finding that people vary in how they play economic games has led to the conclusion that people vary in their preference for fairness. Consequently, people have been divided into fair cooperators that make sacrifices for the good of the group and selfish free-riders that exploit the cooperation of others. This conclusion has been used to challenge evolutionary theory and economic theory and to guide social policy. We show that variation in behavior in the public-goods game is better explained by variation in understanding and that misunderstanding leads to cooperation.

Abstract

Economic experiments are often used to study if humans altruistically value the welfare of others. A canonical result from public-good games is that humans vary in how they value the welfare of others, dividing into fair-minded conditional cooperators, who match the cooperation of others, and selfish noncooperators. However, an alternative explanation for the data are that individuals vary in their understanding of how to maximize income, with misunderstanding leading to the appearance of cooperation. We show that (i) individuals divide into the same behavioral types when playing with computers, whom they cannot be concerned with the welfare of; (ii) behavior across games with computers and humans is correlated and can be explained by variation in understanding of how to maximize income; (iii) misunderstanding correlates with higher levels of cooperation; and (iv) standard control questions do not guarantee understanding. These results cast doubt on certain experimental methods and demonstrate that a common assumption in behavioral economics experiments, that choices reveal motivations, will not necessarily hold.