Nonparametric estimation with aggregated data

Linton, Oliver and Whang, Yoon-Jae (2002) Nonparametric estimation with aggregated data. Econometric Theory, 18 (2). pp. 420-468. ISSN 1469-4360

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Abstract

We introduce a kernel-based estimator of the density function and regression function for data that have been grouped into family totals. We allow for a common intrafamily component but require that observations from different families be independent. We establish consistency and asymptotic normality for our procedures. As usual, the rates of convergence can be very slow depending on the behavior of the characteristic function at infinity. We investigate the practical performance of our method in a simple Monte Carlo experiment.

Item Type:	Article
Official URL:	http://uk.cambridge.org/journals/ect/
Additional Information:	Copyright © 2002 Cambridge University Press. LSE has developed LSE Research Online so that users may access research output of the School. Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Users may download and/or print one copy of any article(s) in LSE Research Online to facilitate their private study or for non-commercial research. You may not engage in further distribution of the material or use it for any profit-making activities or any commercial gain. You may freely distribute the URL (http://eprints.lse.ac.uk) of the LSE Research Online website.
Divisions:	Financial Markets Group STICERD Economics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	17 Feb 2008
Last Modified:	11 Dec 2024 22:32
URI:	http://eprints.lse.ac.uk/id/eprint/320

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