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:	2012
Authors:	Christopeit, Norbert ; Massmann, Michael
Publisher:	Amsterdam and Rotterdam : Tinbergen Institute
Subject:	Regression \| Stochastischer Prozess \| Prognoseverfahren \| Methode der kleinsten Quadrate \| linear regression \| least-squares \| consistency \| stochastic regressors \| adaptive learning \| decreasing gain

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Series:	Tinbergen Institute Discussion Paper ; 12-109/III
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	74000462X [GVK] hdl:10419/87248 [Handle] RePEc:dgr:uvatin:20120109 [RePEc]
Classification:	C13 - Estimation ; C22 - Time-Series Models ; D83 - Search, Learning, Information and Knowledge ; D84 - Expectations; Speculations
Source:	EconStor

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010326230