A method of estimating the average derivative: the multivariate case
A method of estimating the average derivative: the multivariate case
The paper uses local linear regression to estimate the "direct" Average Derivative \delta = E(D[m(x)]), where m(x) is the regression function. The estimate of \delta is the weighted average of local slope estimates. We prove the asymptotic normality of the estimate under conditions which are different from the conditions used by Heardle-Stoker (H-S) (1989). Using Monte-Carlo simulation experiments we give some small sample results comparing our estimator with the H-S estimator under our conditions for asymptotic normality.
University of Southampton
Banerjee, Anurag N.
4f772e58-24c0-4266-ba41-18f70a6108c4
2002
Banerjee, Anurag N.
4f772e58-24c0-4266-ba41-18f70a6108c4
Banerjee, Anurag N.
(2002)
A method of estimating the average derivative: the multivariate case
(Discussion Papers in Economics and Econometrics, 215)
Southampton, UK.
University of Southampton
25pp.
Record type:
Monograph
(Discussion Paper)
Abstract
The paper uses local linear regression to estimate the "direct" Average Derivative \delta = E(D[m(x)]), where m(x) is the regression function. The estimate of \delta is the weighted average of local slope estimates. We prove the asymptotic normality of the estimate under conditions which are different from the conditions used by Heardle-Stoker (H-S) (1989). Using Monte-Carlo simulation experiments we give some small sample results comparing our estimator with the H-S estimator under our conditions for asymptotic normality.
More information
Published date: 2002
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Local EPrints ID: 33397
URI: http://eprints.soton.ac.uk/id/eprint/33397
PURE UUID: 74e97888-6ba5-4756-8b2c-e5a93f4f0dc0
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Date deposited: 18 May 2006
Last modified: 15 Mar 2024 07:43
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Author:
Anurag N. Banerjee
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