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Nonparametric estimation with aggregated data

Linton, Oliver and Whang, Yoon-Jae (2000) Nonparametric estimation with aggregated data. Econometrics; EM/2000/397 (EM/00/397). Suntory and Toyota International Centres for Economics and Related Disciplines, London, UK.

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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 intra-family component but require that observations from different families be in dependent. We establish consistency and asymptotic normality for our procedures. As usual, the rates of convergence can be very slow depending on the behaviour of the characteristic function at infinity. We investigate the practical performance of our method in a simple Monte Carlo experiment.

Item Type: Monograph (Discussion Paper)
Official URL: http://sticerd.lse.ac.uk
Additional Information: © 2000 the authors
Divisions: Financial Markets Group
Economics
STICERD
Subjects: H Social Sciences > HB Economic Theory
JEL classification: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C13 - Estimation
C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C24 - Truncated and Censored Models
Date Deposited: 27 Apr 2007
Last Modified: 13 Sep 2024 19:42
URI: http://eprints.lse.ac.uk/id/eprint/2092

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