TESTING SYMMETRY AND HOMOGENEITY IN THE AIDS WITH COINTEGRATED DATA USING FULLY-MODIFIED ESTIMATION AND THE BOOTSTRAP

Convential SUR estimation of the AIDS is shown to lead to small sample bias and distortions in the size of a Wald test for symmetry and homogeneity when the data are cointegrated. A fully-modified estimator is developed in an attempt to remedy these problems. It is shown that this estimator reduces the small sample bias but fails to eliminate the size distortion. Bootstrapping is shown to be ineffective as a method of removing small sample bias in both the conventional and fully modified estimators. Bootstrapping is effective however as a method of removing the size distortion and performs equally well in this respect with both estimators.


Issue Date:
2003
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/25845
Total Pages:
25
Series Statement:
Contributed Paper




 Record created 2017-04-01, last modified 2018-01-22

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