Arbeitspapier
A Note on an Estimation Problem in Models with Adaptive Learning
This paper provides an example of a linear regression model with predetermined stochastic regressors for which the sufficient condition for strong consistency of the ordinary least squares estimator by Lai & Wei (1982, Annals of Statistics) is not met. Nevertheless, the estimator is strongly consistent, as shown in a companion paper, cf. Christopeit & Massmann (2013b). This is intriguing because the Lai & Wei condition is the best currently available and is referred to as “in some sense the weakest possible”. Moreover, the example discussed in this paper arises naturally in a class of macroeconomic models with adaptive learning, the estimation of which has recently gained popularity amongst researchers and policy makers.
- Language
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Englisch
- Bibliographic citation
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Series: Tinbergen Institute Discussion Paper ; No. 13-151/III
- Classification
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Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Model Construction and Estimation
Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- Subject
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least-squares regression
stochastic regressors
strong consistency
minimal sufficient condition
adaptive learning
- Event
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Geistige Schöpfung
- (who)
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Christopeit, Norbert
Massmann, Michael
- Event
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Veröffentlichung
- (who)
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Tinbergen Institute
- (where)
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Amsterdam and Rotterdam
- (when)
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2013
- Handle
- Last update
-
10.03.2025, 11:42 AM CET
Data provider
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Christopeit, Norbert
- Massmann, Michael
- Tinbergen Institute
Time of origin
- 2013
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