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Stability of Social Preferences and Learning in Public Goods Games

We examine the stability of social preferences in linear public goods games across different costs to cooperate and duration of interaction. Using laboratory experiments, we collect decisions from the same individual on conditional contributions in one-shot games and contributions in finitely (or indefinitely) repeated games at different relative costs of cooperation (i.e. the marginal per capita return (MPCR) to the public good). The generated data are used in a structural estimation of social preferences that accounts for decision error and cooperation costs. We find that, while the cost to cooperate changes behavior in predictable ways (e.g. when it is less costly to cooperate, individuals cooperate more), it also significantly changes the underlying distribution of estimated social preferences. That is, preferences are not stable as cooperation costs change. However, preferences are identical across one-shot and repeated games, and we do not find a significant effect of the type of repetition, finite or indefinite, on belief formation or social preferences. Contribution dynamics in the repeated game are best explained by a payoff-based reinforcement learning model, rather than a belief learning model with social preferences. Finally, using simulations, we show that for repeated games social preferences matter only insofar as they determine first round contributions and thereafter decisions are consistent with payoff-based reinforcement learning. JEL Codes: H41, C92, D83, C63