The University of Southampton
University of Southampton Institutional Repository

A method of estimating the average derivative: the multivariate case

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.
215
University of Southampton
Banerjee, Anurag N.
4f772e58-24c0-4266-ba41-18f70a6108c4
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.

Text
0215.pdf - Other
Download (387kB)

More information

Published date: 2002

Identifiers

Local EPrints ID: 33397
URI: http://eprints.soton.ac.uk/id/eprint/33397
PURE UUID: 74e97888-6ba5-4756-8b2c-e5a93f4f0dc0

Catalogue record

Date deposited: 18 May 2006
Last modified: 15 Mar 2024 07:43

Export record

Contributors

Author: Anurag N. Banerjee

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×