Arbeitspapier
Estimating Structural Parameters in Regression Models with Adaptive Learning
This paper investigates the asymptotic properties of the ordinary least squares (OLS) estimator of structural parameters in a stylised macroeconomic model in which agents are boundedly rational and use an adaptive learning rule to form expectations of the endogenous variable. In particular, when the learning recursion is subject to so-called decreasing gain sequences the model does not satisfy, in general, any of the sufficient conditions for consistent estimability available in the literature. The paper demonstrates that, for appropriate parameter sets, the OLS estimator nevertheless remains strongly consistent and asymptotically normally distributed.
- Language
-
Englisch
- Bibliographic citation
-
Series: Tinbergen Institute Discussion Paper ; No. 13-111/III
- Classification
-
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
-
non-stationary regression
strong consistency
asymptotic normality
bounded rationality
adaptive learning
- Event
-
Geistige Schöpfung
- (who)
-
Christopeit, Norbert
Massmann, Michael
- Event
-
Veröffentlichung
- (who)
-
Tinbergen Institute
- (where)
-
Amsterdam and Rotterdam
- (when)
-
2013
- Handle
- Last update
-
10.03.2025, 11:44 AM CET
Data provider
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