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) |
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| 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: | 11 Dec 2024 18:27 |
| URI: | http://eprints.lse.ac.uk/id/eprint/2092 |
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