Learning, signaling, and social preferences in public-good games

Authored by Marco A Janssen, T. K. Ahn

Date Published: 2006-12

Sponsors: United States National Science Foundation (NSF)

Platforms: Java

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

This study compares the empirical performance of a variety of learning models and theories of social preferences in the context of experimental games involving the provision of public goods. Parameters are estimated via maximum likelihood estimation. We also performed estimations to identify different types of agents and distributions of parameters. The estimated models suggest that the players of such games take into account the learning of others and are belief learners. Despite these interesting findings, we conclude that a powerful method of model selection of agent-based models on dynamic social dilemma experiments is still lacking.

Tags

Agent-based model Learning public goods laboratory experiments social preferences