Consistent Estimation of Structural Parameters in Regression Models with Adaptive Learning

Norbert Christopeit and Michael Massmann
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Norbert Christopeit: University of Bonn

No 10-077/4, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: In this paper we consider regression models with forecast feedback. Agents' expectations are formed via the recursive estimation of the parameters in an auxiliary model. The learning scheme employed by the agents belongs to the class of stochastic approximation algorithms whose gain sequence is decreasing to zero. Our focus is on the estimation of the parameters in the resulting actual law of motion. For a special case we show that the ordinary least squares estimator is consistent.

Keywords: Adaptive learning; forecast feedback; stochastic approximation; linear regression with stochastic regressors; consistency (search for similar items in EconPapers)
JEL-codes: C13 C22 D83 D84 (search for similar items in EconPapers)
Date: 2010-08-23
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20100077

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