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Convergence in models with bounded expected relative hazard rates

Oyarzun, Carlos and Ruf, Johannes (2014) Convergence in models with bounded expected relative hazard rates. Journal of Economic Theory, 154. pp. 229-244. ISSN 1095-7235

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Identification Number: 10.1016/j.jet.2014.09.014

Abstract

We provide a general framework to study stochastic sequences related to individual learning in economics, learning automata in computer sciences, social learning in marketing, and other applications. More precisely, we study the asymptotic properties of a class of stochastic sequences that take values in [0,1] and satisfy a property called “bounded expected relative hazard rates.” Sequences that satisfy this property and feature “small step-size” or “shrinking step-size” converge to 1 with high probability or almost surely, respectively. These convergence results yield conditions for the learning models in [13,35,7] to choose expected payoff maximizing actions with probability one in the long run.

Item Type: Article
Official URL: http://www.sciencedirect.com/science/journal/00220...
Additional Information: © 2014 Elsevier
Divisions: Mathematics
Subjects: Q Science > QA Mathematics
Sets: Departments > Mathematics
Date Deposited: 11 Oct 2017 11:26
Last Modified: 14 Dec 2017 11:34
URI: http://eprints.lse.ac.uk/id/eprint/84586

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