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A Comparison of Ordinary Least Squares and Least Absolute Error Estimation

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  • Weiss, Andrew A.

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.

Suggested Citation

  • Weiss, Andrew A., 1988. "A Comparison of Ordinary Least Squares and Least Absolute Error Estimation," Econometric Theory, Cambridge University Press, vol. 4(3), pages 517-527, December.
    • Handle: RePEc:cup:etheor:v:4:y:1988:i:03:p:517-527_01
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