Modeling expectations in systems with heterogeneous agents

Abstract:

Influence of endogenous rate of time preferences on dynamics of stochastic models with heterogeneous agents with use of algorithm of formation of expectations, related with learning agents by a trial and error method is considered. It is shown, that in models with endogenous rate of time preferences speed of a convergence of this algorithm considerably exceeds speed of a convergence of algorithm in models with constant rate of time preferences. Presence of a feedback for rate of time preferences leads to to decrease volatility of the researched variables.