A simple message for autocorrelation correctors : don't
Journal of econometrics, 1995, Vol. 69, No. 1, pp. 267-288
MIZON, Grayham E., A simple message for autocorrelation correctors : don't, Journal of econometrics, 1995, Vol. 69, No. 1, pp. 267-288 - https://hdl.handle.net/1814/71327
Retrieved from Cadmus, EUI Research Repository
Though the practice of 'correcting for residual autocorrelation' has long been critized, it is still commonly advocated and followed. A simple example shows that even when a linear regression model has first-order autoregressive errors, it is possible for autoregressive least squares estimation (e.g., Cochrane-Orcutt) to yield inconsistent estimates. This dramatically illustrates that 'autocorrelation correction' is invalid in general, and cannot be justified on the grounds of 'robustifying' estimation against the presence of residual serial correlation, Invalid common factors in I(1) systems also have adverse effects on inference. A 'general-to-specific modelling strategy applied to the observed modelled variables avoids these difficulties.
First published online: 07 April 2000
Cadmus permanent link: https://hdl.handle.net/1814/71327
Full-text via DOI: 10.1016/0304-4076(94)01671-L
Earlier different version: http://hdl.handle.net/1814/478
Version: The article is a published version of EUI ECO WP; 1993/37
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