A Comparison of Ordinary Least Squares and Least Absolute Error Estimation

Andrew A. Weiss

Econometric Theory, 1988, vol. 4, issue 3, 517-527

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.

Date: 1988
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