Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/87485
Authors: 
Christopeit, Norbert
Massmann, Michael
Year of Publication: 
2013
Series/Report no.: 
Tinbergen Institute Discussion Paper 13-151/III
Abstract: 
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.
Subjects: 
least-squares regression
stochastic regressors
strong consistency
minimal sufficient condition
adaptive learning
JEL: 
C22
C51
D83
Document Type: 
Working Paper

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