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"On the Robust Estimation of Econometric Models," Annals of Economic and Social Measurement, October 1974, 667-677.
pdf file (673KB).

Abstract

The computational aspects of obtaining robust estimates of a general nonlinear econometric model are described, and some results of estimating a particular model are presented. When robust estimators are considered as weighted-least-squares estimators, it clearly appears feasible, by a combination of solving unconstrained optimization problems and iterating, to obtain robust estimates of econometric models. In estimating the particular model, the robust estimators performed well in terms of prediction accuracy.
Comments

This paper discusses how robust estimates of econometric models can be obtained. For the example my forecasting model--1971#5--was estimated by six extimators, four of them robust estimators, and the estimators were compared in terms of predictive accuracy.

The discussion of the computation of the LAD and 2SLAD estimators in Chapter 6, Section 6.5.4, in 1984#2 is based on this paper. The discussion of the LAD and 2SLAD estimators in Chapter 6, Sections 6.3.5 and 6.3.6, in 1984#2 is an extension of the discussion in this paper. The 2SLAD estimator in Section 6.3.6 for q = 1.0 is the estimator suggested at the bottom of page 670 of this paper.

The LAD and 2SLAD estimators are programmed into the Fair-Parke program. The commands are simply LAD and 2SLAD.