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Non-myopic learning in differential information economies: the core
Book chapter

Non-myopic learning in differential information economies: the core

Differential Information Economies, v 19, pp 465-480
01 Jan 2005

Abstract

Business & Economics Mathematics, Interdisciplinary Applications Science & Technology Economics Mathematics Physical Sciences Social Sciences
We study the process of learning in a differential information economy, with 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 behave non-myopically, i.e., they discount the future. We adopt a new equilibrium concept, the non-myopic core. A realized agreement in each period generates information that changes the underlying structure in the economy. The results we obtain serve as an extension to the results in Koutsougeras and Yannelis (1999) in a setting where agents behave non-myopically. In particular, 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 bounded rationality), is it possible to find a subsequence that converges to a non-myopic core allocation in a limit full information economy? 2) Given a non-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?

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Web of Science research areas
Economics
Mathematics, Interdisciplinary Applications
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