It is shown that player mobility has important consequences for the long-run equilibrium distribution in dynamic evolutionary models of strategy adjustment, when updating is prone to small probability perturbations, i.e. “mistakes” or “mutations.” Ellison (1993) concluded that the effect on the matching process of localized “neighborhoods” was to strengthen the stability of risk-dominant outcomes, originally demonstrated by Kandori, Mailath, and Rob (1993) (KMR) and Young (1993). I consider a model in which players can choose the neighborhoods to which they belong. When strategies and locations are updated simultaneously, only efficient strategies survive. The robustness of this conclusion is emphasized in a general locational model in which strategy revision opportunities are allowed to arrive at a faster rate than opportunities to change locations. The efficient strategy persists in all cases in which the locational structure is non-trivial. Moreover, even as the relative frequency of player mobility approaches zero, the efficient strategy occurs with boundedly positive relative frequency. This result is in stark contrast to the conclusions of the previous models.
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- Kandori, Michihiro & Mailath, George J & Rob, Rafael, 1993.
"Learning, Mutation, and Long Run Equilibria in Games,"
Econometric Society, vol. 61(1), pages 29-56, January.
- M. Kandori & G. Mailath & R. Rob, 1999. "Learning, Mutation and Long Run Equilibria in Games," Levine's Working Paper Archive 500, David K. Levine.
- Kandori, M. & Mailath, G.J., 1991. "Learning, Mutation, And Long Run Equilibria In Games," Papers 71, Princeton, Woodrow Wilson School - John M. Olin Program.
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