Partners versus Strangers: Random Rematching in Public Goods Experiments

How can an experimenter balance the desire to test a single-shot Nash equilibrium prediction with the need for repeated experience by subjects? Simply repeating the game with the same set of subjects may change the nature of equilibrium, since incomplete information about “types” can lead to reputation effects of the sort described by Kreps et al. (1982). A common way to deal with this has been to rematch subjects randomly into groups for each iteration of the game, hence forming a repeated single-shot design and avoiding the repeated-game effects. This raises the natural question: what is the effect of random rematching? The rematching of subjects in linear public goods experiments was introduced by Andreoni (1988). The first linear public goods experiments, by Marwell and Ames (1981), were single-shot games and produced little of the dominant strategy Nash equilibrium free riding they predicted. Subjects, it was argued, needed experience to learn the dominant strategy. Isaac and Walker (1988) replicated these games, but used a 10period, finitely repeated game. However, free riding was still not chosen, and repetition had only a small effect in increasing free riding. Was it reputation effects that kept subjects from adopting the single-shot dominant strategy? Andreoni (1988) tested this question by comparing a set of subjects who played in finitely repeated games with another set who played in a repeated single-shot. Players in the repeated game were called “Partners,” while those in the repeated single-shot game were called “Strangers.” If reputations matter, then Partners should cooperate more than Strangers. Surprisingly, Andreoni found just the opposite – Strangers cooperated significantly more than Partners. Since this time, many researchers have explored this anomalous result. This chapter will attempt to synthesize the various replications and studies that have addressed this puzzle.