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A Comparison of Ordinary Least Squares and Least Absolute Error Estimation

Published online by Cambridge University Press:  18 October 2010

Andrew A. Weiss
Andrew A. Weiss*
Affiliation:
University of Southern California
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Abstract

In a linear-regression model with heteroscedastic errors, we consider two tests: a Hausman test comparing the ordinary least squares (OLS) and least absolute error (LAE) estimators and a test based on the signs of the errors from OLS. It turns out that these are related by the well-known equivalence between Hausman and the generalized method of moments tests. Particular cases, including homoscedasticity and asymmetry in the errors, are discussed.

Type
Brief Report
Information
Econometric Theory , Volume 4 , Issue 3 , December 1988 , pp. 517 - 527
Copyright
Copyright © Cambridge University Press 1988 

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References

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