This paper examines theoretically, using a two-country real-business-cycle model, the effects of capital-market liberalization when there is limited participation in national financial markets. It is assumed that workers cannot smooth consumption as well as do stockholders, and therefore,...

Most studies of optimal monetary policy under learning rely on optimality conditions derived for the case when agents have rational expectations. In this paper, we derive optimal monetary policy in an economy where the Central Bank knows, and makes active use of, the learning algorithm agents...

This paper provides a formal definition of emergence, operative in multi-agent framework and which make sense from both a cognitive and an economics point of view. The first part discuses the ontological and epistemic dimension of emergence and provides a complementary set of definitions....

This paper considers the behavior of the exchange rate in a very simple artificial currency market with two currencies and artificial agents who evolve their forecast rules over time via a genetic algorithm. I consider two simple forecast rules, one linear and the other non-linear. Under the...

We have developed an agent-based computational model, extension of an analytical model1 that studies the structure of coalitions of B-to-C web sites, when Internet buyers incur search costs for finding the good that matches their preferences, and coalitions of sites reduce this cost through...

While under recursive least squares learning the dynamics of the economy converges to rational expectations equilibria (REE) which are E–stable, some recent examples propose that E–stability is not a sufficient condition for learnability. In this paper, we provide some further...

We examine optimal policy in an open-economy model with uncertainty and learning, where monetary policy actions affect the economy through the real exchange rate channel. Our results show that the degree of caution or activism in optimal policy depends on whether central banks are in coordinated...

We provide sufficient conditions and necessary conditions for stability of an economy under structural mixed recursive least squares/stochastic gradient heterogeneous learning of agents with possibly different degrees of inertia. We have found a unifying condition which is sufficient for...

In this paper we perform an in—depth investigation of relative merits of two adaptive learning algorithms with constant gain, Recursive Least Squares (RLS) and Stochastic Gradient (SG), using the Phelps model of monetary policy as a testing ground. The behavior of the two learning...