Confusion and Reinforcement Learning in
Experimental Public Goods Games *
Ralph-C Bayer∣ Elke Renner^ and Rupert Sausgruber§
September 2009
Abstract
We use a limited information environment to mimic the state of confusion in an
experimental, repeated public goods game. The results show that reinforcement
learning leads to dynamics similar to those observed in standard public goods
games. However, closer inspection shows that individual decay of contributions in
standard public goods games cannot be fully explained by reinforcement learning.
According to our estimates, learning only accounts for 41 percent of the decay
in contributions in standard public goods games. The contribution dynamics of
subjects, who are identified as conditional cooperators, differ strongly from the
learning dynamics, while a learning model estimated from the limited information
treatment tracks behavior for subjects, who cannot be classified as conditional
cooperators, reasonably well.
Keywords: public goods experiments, learning, limited information, confusion,
conditional cooperation
JEL classification: C90, D83, H41.
*We are grateful for financial support by the Austrian Science Fund (FWF) under Projects No.
P17029 and S10307-G14 as well as by the Faculty of Profession Research Grant Scheme of the University
of Adelaide.
tSchool of Economics, University of Adelaide, Napier Building, SA 5005 Adelaide, Australia; E-mail:
[email protected]
* School of Economics, Sir Clive Granger Building, University Park, Nottingham NG7 2RD, United
Kingdom; E-mail: [email protected]
§Department of Economics, University of Copenhagen, DK-1455 Copenhagen K, Denmark; E-mail:
[email protected]