We introduce a new class of in nite horizon altruistic stochastic OLG models with capital and labor, but without commitment between the generations. Under mild regularity conditions, for economies with either bounded or unbounded state spaces, continuous monotone Markov perfect Nash equilibrium...

Dynamic stochastic general equilibrium models with ex-post heterogeneity due to idiosyncratic risk have to be solved numerically. This is a nontrivial task as the cross-sectional distribution of endogenous variables becomes an element of the state space due to aggregate risk. Existing global...

The paper develops a dynamical systems approach to study asset bubbles in OLG economies with stochastic production. We derive necessary and sufficient conditions for bubbly equilibria to exist and chracterize the maximum sustainable bubble. Even if they exist, bubbles are temporary and the...

The paper examines a class of random dynamical systems related to the classical von Neumann and Gale models of economic dynamics. Such systems are defined in terms of multivalued operators in spaces of random vectors, possessing certain properties of convexity and homogeneity. We establish a...

This paper presents the logarithmic stochastic tracing procedure, a homotopy method for the computation and selection of stationary equilibria of any finite discounted stochastic game. It generalizes both the logarithmic tracing procedure (Harsanyi and Selten, 1988), which is defined only for...

We introduce a notion of subgames for stochastic timing games and the related notion of subgame-perfect equilibrium in possibly mixed strategies. While a good notion of subgame-perfect equilibrium for continuous-time games is not available in general, we argue that our model is the appropriate...

We consider a model of stochastic evolution under general noisy best response protocols, allowing the probabilities of suboptimal choices to depend on their payoff consequences. Our analysis focuses on behavior in the small noise double limit: we first take the noise level in agents' decisions...