Journal of Public Economics 37 (1988) 291-304. North-Holland WHY FREE RIDE? Strategies and Learning in Public Goods Experiments James ANDREONI* The Unit;ersity qf Wisconsin-Madison, Madison, WI 53706. USA Received May 1987, revised version received August 1988 Laboratory experiments on free riding have produced mixed results. Free riding is seldom observed with single-shot games; however, it is often approximated in finitely repeated games. There are two prevailing hypotheses for why this is so: strategies and learning. This paper discusses these hypotheses and presents an experiment that examines both. 1. Introduction The free riding hypothesis has been the subject of laboratory experiments for more than a decade. While the extent of free riding has often varied across experiments, three observations are consistently replicated. First, there is no significant evidence of free riding in single-shot games. Marwell and Ames (1981) for instance, found that subjects generally provide the public good at levels halfway between the Pareto efficient level and the free riding level. Second, when subjects play a repeated game, provision of the public good ‘decays’ toward the free riding level with each repetition. This decay phenomenon is observed when subjects know the length of the game for sure [Isaac, Walker and Thomas (1984), Isaac and Walker (1988)], and also when they do not [Isaac, McCue and Plott (1985), Kim and Walker (1984)]. Third, free riding is often approximated after subjects play several trials, although exact free riding is seldom realized. These observations appear to provide mixed support for free riding. It seems clear that the free riding incentives are important - subjects consis- tently attain outcomes that are closer to the free riding levels than the Pareto efficient levels. On the other hand, the exact predictions of the model are seldom confirmed. The phenomenon of decay is particularly pronounced. *Thanks to Theodore Bergstrom, Robyn Dawes, Mark Isaac, Gerald Marwell, Michael McKee, Thomas Palfrey. Hal Varian, James M. Walker and some referees for helpful comments. I am especially grateful for the advice and assistance of John H. Miller. 004772727;88.!S3.50 &:I 1988, Elsevier Science Publishers B.V. (North-Holland)292 J. Andreoni, Why free ride? Repetition appears to be necessary for subjects to approach free riding behavior. Naturally, researchers have looked for explanations of these results. The two hypotheses that are most often proposed are strategies and learning. The learning hypothesis holds that a single shot of the game is not sufficient to allow subjects to learn the incentives. Repeated play allows such learning, and hence learning could explain decay. However, this test of learning is confounded by the fact that repetition allows subjects to signal future moves to each other. This is the basis for the strategies hypothesis. In a repeated game it may be rational for subjects to develop multiperiod strategies that allow for some cooperative behavior, even after the free riding incentives are learned. If this is the case, then these strategies may be responsible for decay. This paper discusses a laboratory experiment designed to examine the strategies and learning hypotheses directly. Section 2 describes the hypoth- eses in detail, and indicates how they are tested. The results of the experiment are given in section 3, with a discussion in section 4. The evidence from the experiment suggests, first, that a hypothesis of rational strategic play cannot be supported, and second, that learning may play little or no role in explaining the phenomenon of decay. Moreover, the data are consistent with other predictions based on theories of non-standard behavior, such as altruism, social norms, or bounded rationality.’ The evidence suggests greater consideration of such non-standard behavior in both theoretical and experimental research. 2. Strategies and learning 2.1. Theory and evidence The experiment reported in this paper is typical of most public goods experiments. It consists of a simple public goods game that is iterated 10 times. Every iteration operates as follows. Five subjects form a group. Each subject in the group is given a budget of 50 ‘tokens’. The tokens can be redeemed for cash only when they are ‘invested’ in either a private good (called an ‘Individual Exchange’) or a public good (called a ‘Group Exchange’). A token in the private good earns one cent for the person who invests it. However, earnings from the public good depend on what the group as a whole invents. Each token in the public good earns one half cent for the person investing it, as well as one half cent for each other member of the group. Subjects always move simultaneously, and cannot communicate at any point in the experiment. Subjects are only told the total amount of the public good for their own group. Specific contributions of other individuals, ’ For examples of such theories see Margolis (1982), Sugden (1984), Frank (1985), Palfrey and Rosenthal (1987), and Andreoni (1987).J. Andreoni, Why free ride? 293 and outcomes of other groups, are not known. For ease of reference, the precise details of the experiment are summarized in the appendix.’ With the payoffs just described, the equilibrium and efticiency conditions are easily calculated. Investing a token in the public good has a private return of one half cent, while it has a social return of 2.5 cents. Hence, it is Pareto efficient for all subjects to invest all tokens in the public good. On the other hand, since the private return from the private good exceeds the private return from the public
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