Adaptive learning of rational expectations using neural networks
type: Item
instance of: scholarly article
title: Adaptive learning of rational expectations using neural networks
zbMATH Open document ID: 0951.62093
DOI: 10.1016/S0165-1889(99)00034-2
publication date: 2000-06-04T00:00:00Z
review text: This paper investigates how adaptive learning of rational expectations may be modeled with the help of neural networks. Necessary conditions for the convergence of the learning process towards (approximate) rational expectations are derived using a simple nonlinear cobweb model. The results obtained are similar to results obtained within the framework of linear models using recursive least squares learning procedures. In general, however, convergence of a learning process based on a neural network may imply that the resulting expectations are not even local minimizers of the mean-squared prediction error.
Mathematics Subject Classification ID: 62P20
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 1454351
zbMATH Keywords: adaptive learning
zbMATH Keywords: neural networks
zbMATH Keywords: nonlinear cobweb model
author: Maik Heinemann
MaRDI profile type: Publication
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published in: Journal of Economic Dynamics and Control
description: scientific article; zbMATH DE number 1454351