Center for Economic Research, Department of Economics, University of Minnesota
This paper describes several learning processes which converge, with probability one,
to the rational expectations (Bayesian-Nash) equilibrium of a stationary linear game. The
learning processes include a test for convergence to equilibrium, and a method for changing
the parameters of the process when nonconvergence is indicated. This self-stabilization
property eliminates the need to impose stability conditions on the economic environment.
Convergence to equilibrium is proved for two types of self-stabilizing learning mechanisms:
a centralized forecasting mechanism and a decentralized strategy adjustment process. For
a version of the decentralized process it is also shown that the publicly observable information,
on which learning is based, does not necessarily reveal anything about the economic
environment except the equilibrium.
Jordan, J.S., (1990), "Convergence to Rational Expectations in a Stationary Linear Game", Discussion Paper No. 258, Center for Economic Research, Department of Economics, University of Minnesota.
Jordan, James S..
Convergence to Rational Expectations in a Stationary Linear Game.
Center for Economic Research, Department of Economics, University of Minnesota.
Retrieved from the University of Minnesota Digital Conservancy,
Content distributed via the University of Minnesota's Digital Conservancy may be subject to additional license and use restrictions applied by the depositor.