Beckert, Walter and McFadden, D.L. (2010) Maximal uniform convergence rates in parametric estimation problems. Econometric Theory 26 (2), pp. 469-500. ISSN 0266-4666.
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Abstract
This paper considers parametric estimation problems with independent, identically nonregularly distributed data. It focuses on rate efficiency, in the sense of maximal possible convergence rates of stochastically bounded estimators, as an optimality criterion, largely unexplored in parametric estimation. Under mild conditions, the Hellinger metric, defined on the space of parametric probability measures, is shown to be an essentially universally applicable tool to determine maximal possible convergence rates. These rates are shown to be attainable in general classes of parametric estimation problems.
Metadata
| Item Type: | Article |
|---|---|
| Keyword(s) / Subject(s): | parametric estimators, uniform convergence, Hellinger distance, Locally Asymptotically Quadratic (LAQ) Families |
| School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
| Research Centres and Institutes: | Commodities Finance Centre |
| Depositing User: | Administrator |
| Date Deposited: | 08 Dec 2010 11:51 |
| Last Modified: | 02 Aug 2023 16:54 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/2912 |
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