Johansen's reduced rank maximum likelihood (ML) estimator for cointegration parameters in vector error correction models is known to produce occasional extreme outliers. Using a small monetary system and German data we illustrate the practical importance of this problem. We also consider an alternative generalized least squares (GLS) system estimator which has better properties in this respect. The two estimators are compared in a small simulation study. It is found that the GLS estimator can indeed be an attractive alternative to ML estimation of cointegration parameters.
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Paper provided by European University Institute in its series Economics Working Papers with number
ECO2004/20.
Length: Date of creation: 2004 Date of revision: Handle: RePEc:eui:euiwps:eco2004/20
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