INTRODUCTION

The use of dynamic stochastic models in economics has grown very quickly during the last fifteen years. The importance of this type of models became evident in macro-economics after the paper of Lucas (1972); he argued that the basic relations that were taken as given in traditional macro-economic models (whether Keynesian or Monetarist), such as the money demand function, the consumption function, the investment function, were not invariant to the very type of policy intervention that those models were designed to analyse. Furthermore, these relations were often mutually inconsistent. The way around this problem was to study models where objects like preferences of consumers, production technology, information dissemination, etc. were fixed, and where a well-specified concept of equilibrium determined the outcome of the model. The research programme, then, was to analyse the equilibrium of the model under different environments (for example, under different policy rules) in order to study the effect of changes in the economic environment or policy interventions, taking consumption function, money demand, etc. as endogenous. Nowadays, dynamic stochastic models of equilibrium are being used in virtually all fields of economics.

One crucial element of how dynamic models behave is the assumption about how agents form their expectations. Nowadays, the standard assumption is that agents behave as if they had rational expectations. This avoids ad hoc assumptions about expectations that would not be likely to stay constant under policy changes if agents were rational. Furthermore, many recent papers argue that, in many models, the rational expectations equilibrium can be justified as the limit of a learning process.