Learning dynamics for mechanism design: An experimental comparison of public goods mechanisms

doi:10.1016/j.jet.2005.03.002

Journal of Economic Theory

Volume 129, Issue 1, July 2006, Pages 114-149

https://doi.org/10.1016/j.jet.2005.03.002 Get rights and content

Abstract

In a repeated-interaction public goods economy, incomplete information and dynamic behavior may affect the realized outcomes of mechanisms known to be efficient in a complete information one-shot game. An experimental test of five public goods mechanisms indicates that subjects with private information appear to best respond to recent observations. This provides predictions about which mechanisms will generate convergence to their efficient equilibrium allocations. These predictions match the experimental result that globally stable efficient mechanisms realize the highest efficiency in practice. The simplicity of the suggested best response model makes it useful in predicting stability of mechanisms not yet tested.

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This paper studies the extent to which simply asking group members to report their demand-type promotes cooperation in a public goods experiment with private, unobservable incentives. The design uses a simple public goods game, in which group members differ in both their dominant strategy contributions and socially optimal contributions. Treatments are conducted in which individuals either do not report their private payoff information, report only to group members, report to group members who can punish them, or report to a binding mechanism that charges them the socially optimal contribution for someone of their reported type. In all cases, messages are non-verifiable and participants are told that they are free to lie. When participants are able to report their type, either to their group members or to a binding mechanism, they contribute more. When reporting to a mechanism, there is a positive effect initially that fades with repetition, while reporting to group members is particularly effective at sustaining cooperation over time. Further, the misreporting of type is less frequent, considered more dishonest, and punished more harshly than free-riding. Consistent with work showing that weak punishment can backfire, the punishment mechanism is underutilized in this environment and its presence negates the positive effect of sharing information.
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Examples include the renovation of infrastructure, a clean environment, or a yearly street party. Healy (2006) finds in his meta-study that agents' behavior in multiple experiments on repeated public good mechanisms can be well described by myopic adjustment processes. In a later study, Healy and Mathevet (2012) construct what they call contractive mechanisms that have Nash equilibria that are stable according to a variety of dynamic adjustment processes.
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Learning dynamics for mechanism design: An experimental comparison of public goods mechanisms

Abstract

J. Public Econ.

Econ. Lett.

Games Econ. Behav.

Math. Soc. Sci.

Games Econ. Behav.

Experiments with the pivot process for providing public goods

Public Choice

The invariably stable coweb model

Rev. Econ. Stud.

The matrix multiplier and distributed lags

Econometrica

Distributed lags and economic theory

Rev. Econ. Stud.

Iterative solution of games by fictitious play

The stability of an experimental market with supply-response lag

The Southern Econ. J.

Incentive compatible mechanisms for pure public goods: A survey of experimental research

When does learning in games generate convergence to nash equilibria? The role of supermodularity in an experimental setting

Amer. Econ. Rev.

Learning and incentive-compatible mechanisms for public goods provision: An experimental study

J. Polit. Econ.

Multipart pricing of public goods

Public Choice

An Introduction to the Bootstrap