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A Shortcut to LAD Estimator Asymptotics

Published online by Cambridge University Press:  11 February 2009

P.C.B. Phillips
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Abstract

Using generalized functions of random variables and generalized Taylor series expansions, we provide quick demonstrations of the asymptotic theory for the LAD estimator in a regression model setting. The approach is justified by the smoothing that is delivered in the limit by the asymptotics, whereby the generalized functions are forced to appear as linear functionals wherein they become real valued. Models with fixed and random regressors, and autoregressions with infinite variance errors are studied. Some new analytic results are obtained including an asymptotic expansion of the distribution of the LAD estimator.

Type
Research Article
Information
Econometric Theory , Volume 7 , Issue 4 , December 1991 , pp. 450 - 463
Copyright
Copyright © Cambridge University Press 1991

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