Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/64507 
Year of Publication: 
2009
Series/Report no.: 
Working Paper No. 660
Publisher: 
University of California, Economics Department, Santa Cruz, CA
Abstract: 
We report experiments designed to test between Nash equilibria that are stable and unstable under learning. The 'TASP' (Time Average of the Shapley Polygon) gives a precise prediction about what happens when there is divergence from equilibrium under fictitious play like learning processes. We use two 4 x 4 games each with a unique mixed Nash equilibrium; one is stable and one is unstable under learning. Both games are versions of Rock-Paper-Scissors with the addition of a fourth strategy, Dumb. Nash equilibrium places a weight of 1/2 on Dumb in both games, but the TASP places no weight on Dumb when the equilibrium is unstable. We also vary the level of monetary payoffs with higher payoffs predicted to increase instability. We find that the high payoff unstable treatment differs from the others. Frequency of Dumb is lower and play is further from Nash than in the other treatments. That is, we find support for the comparative statics prediction of learning theory, although the frequency of Dumb is substantially greater than zero in the unstable treatments.
Subjects: 
games
experiments
TASP
learning
unstable
mixed equilibrium
fictitious play
JEL: 
C72
C73
C92
D83
Document Type: 
Working Paper

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