Strong Consistency of the Least-Squares Estimator in Simple Regression Models with Stochastic Regressors

Strong consistency of least squares estimators of the slope parameter in simple linear regression models is established for predetermined stochastic regressors. The main result covers a class of models which falls outside the applicability of what is presently available in the literature. An application to the identification of economic models with adaptive learning is discussed

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Year of publication:	2015
Authors:	Christopeit, Norbert
Other Persons:	Massmann, Michael (contributor)
Publisher:	[2015]: [S.l.] : SSRN
Subject:	Stochastischer Prozess \| Stochastic process \| Regressionsanalyse \| Regression analysis \| Kleinste-Quadrate-Methode \| Least squares method \| Schätztheorie \| Estimation theory \| Prognoseverfahren \| Forecasting model

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Extent:	1 Online-Ressource (25 p)
Series:	TI Discussion Paper 12-109/III
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments October 7, 2012 erstellt
Other identifiers:	10.2139/ssrn.2160829 [DOI]
Classification:	C13 - Estimation ; C22 - Time-Series Models ; D83 - Search, Learning, Information and Knowledge ; D84 - Expectations; Speculations
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10013036394