Abstract
This paper provides a new way to identify conditional cooperation in a real-time version of the standard voluntary contribution mechanism. We define contribution cycles as the number of contributors a player waits for before committing to a further contribution, and use a permutation test on contribution cycles to assign a measure of conditional cooperation to each group play. The validity of the measures is tested in an experiment. We find that roughly 20% of the plays exhibit dynamics of conditional cooperation. Moreover, notwithstanding a decline in contributions, conditional cooperation is found to be stable over time.
Highlights
It is a well-established stylized fact that individuals contribute voluntarily to public goods even when material self-interest would make free-riding the individually best option
The same mean cycle can reflect different level of conditional cooperation with different levels of heterogeneity in contributions. To capture this difference as well as to account for the absolute levels of contribution, we develop a second measure of conditional cooperation, which takes into account the various levels of conditional cooperation that are attainable with the observed contribution profile
In this paper we provided a new way of detecting conditional cooperation in a standard linear voluntary contribution mechanism
Summary
It is a well-established stylized fact that individuals contribute voluntarily to public goods even when material self-interest would make free-riding the individually best option. Contributions to public goods are often made over long periods of time with information spill-overs.2 This structure allows for different manifestations of conditional cooperation than those captured by the existing experimental paradigms. Fischbacher et al [1] introduced a further paradigm in which participants have to indicate how much they are willing to contribute for each possible value of the others’ average contributions. Those who submit a ‘contribution schedule’ that is monotonically increasing with the others’ average contribution are categorized as conditional cooperators. The method we introduce in this paper allows subjects to implement conditional strategies in a dynamic and transparent way, using actual information about others’ contributions.
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