Non-myopic learning in differential information economies: the core

We study the process of learning in a differential information economy, wit h a continuum of states of nature that follow a Markov process. The economy extends over an infinite number of periods and we assume that the agents b ehave non-myopically, i.e., they discount the future. We adopt a new equili brium concept, the non-myopic core. A realized agreement in each period gen erates information that chan-es the underlying structure in the economy. Th e results we obtain serve as an extension to the results in Koutsougeras an d Yannelis (1999) in a setting where agents behave non-myopically. In parti cular, we examine the following two questions: 1) If we have a sequence of allocations that are in an approximate non-myopic core (we allow for bounde d rationality), is it possible to find a subsequence that converges to a no n-myopic core allocation in a limit full information economy? 2) Given a no n-myopic core allocation in a limit full information economy can we find a sequence of approximate non-myopic core allocations that converges to that allocation?.