Keywords
least median of squares, reweighted least squares, partially adaptive estimation
Abstract
The small sample performance of least median of squares, reweighted least squares, least squares, least absolute deviations, and three partially adaptive estimators are compared using Monte Carlo simulations. Two data problems are addressed in the paper: (1) data generated from non-normal error distributions and (2) contaminated data. Breakdown plots are used to investigate the sensitivity of partially adaptive estimators to data contamination relative to RLS. One partially adaptive estimator performs especially well when the errors are skewed, while another partially adaptive estimator and RLS perform particularly well when the errors are extremely leptokurtotic. In comparison with RLS, partially adaptive estimators are only moderately effective in resisting data contamination; however, they outperform least squares and least absolute deviation estimators.
Original Publication Citation
A Comparison of Partially Adaptive and Reweighted Least Squares Estimation, with James McDonald and Whitney Newey, 2003, Econometric Reviews, 22, 115-134.
BYU ScholarsArchive Citation
Boyer, Brian H.; McDonald, James B.; and Newey, Whitney K., "A Comparison of Partially Adaptive and Reweighted Least Squares Estimation" (2003). Faculty Publications. 8934.
https://scholarsarchive.byu.edu/facpub/8934
Document Type
Peer-Reviewed Article
Publication Date
2003
Publisher
Econometric Reviews
Language
English
College
Marriott School of Business
Department
Finance
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