Learning dynamics for mechanism design: An experimental comparison of public goods mechanisms |
| |
Authors: | Paul J Healy |
| |
Institution: | Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA |
| |
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. |
| |
Keywords: | C72 C91 D83 H41 |
本文献已被 ScienceDirect 等数据库收录! |
|