A method of estimating the average derivative: the multivariate case
AbstractThe 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.
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Bibliographic InfoPaper provided by Economics Division, School of Social Sciences, University of Southampton in its series Discussion Paper Series In Economics And Econometrics with number 0215.
Date of creation: 01 Jan 2002
Date of revision:
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- Banerjee, Anurag, 2007. "A method of estimating the average derivative," Journal of Econometrics, Elsevier, vol. 136(1), pages 65-88, January.
- Ahn, Hyungtaik, 1997. "Semiparametric Estimation of a Single-Index Model with Nonparametrically Generated Regressors," Econometric Theory, Cambridge University Press, vol. 13(01), pages 3-31, February.
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