Maximal Uniform Convergence Rates In Parametric Estimation Problems
AbstractThis paper considers parametric estimation problems with independent, identically,non-regularly distributed data. It focuses on rate-effciency, 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.
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 26 (2010)
Issue (Month): 02 (April)
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Other versions of this item:
- Walter Beckert & Daniel McFadden, 2004. "Maximal Uniform Convergence Rates in Parametric Estimation Problems," Birkbeck Working Papers in Economics and Finance 0405, Birkbeck, Department of Economics, Mathematics & Statistics.
- Walter Beckert & Daniel McFadden, 2005. "Maximal uniform convergence rates in parametric estimation problems," CeMMAP working papers CWP06/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Walter Beckert & Daniel McFadden, 2007. "Maximal uniform convergence rates in parametric estimation problems," CeMMAP working papers CWP28/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Newey, W.K., 1989.
"Uniform Convergence In Probability And Stochastic Equicontinuity,"
342, Princeton, Department of Economics - Econometric Research Program.
- Newey, Whitney K, 1991. "Uniform Convergence in Probability and Stochastic Equicontinuity," Econometrica, Econometric Society, vol. 59(4), pages 1161-67, July.
- Bruce E. Hansen, 1996.
"Sample Splitting and Threshold Estimation,"
Boston College Working Papers in Economics
319., Boston College Department of Economics, revised 12 May 1998.
- Horowitz, Joel L., 1993. "Optimal Rates of Convergence of Parameter Estimators in the Binary Response Model with Weak Distributional Assumptions," Econometric Theory, Cambridge University Press, vol. 9(01), pages 1-18, January.
- repec:cup:etheor:v:9:y:1993:i:1:p:1-18 is not listed on IDEAS
- Harry J. PAARSCH, 1994.
"A Comparison of Estimators for Empirical Models of Auctions,"
Annales d'Economie et de Statistique,
ENSAE, issue 34, pages 143-157.
- Paarsch, H.J., 1992. "A Comparison of estimators for Empirical Models of Auction," UWO Department of Economics Working Papers 9210, University of Western Ontario, Department of Economics.
- Klein, R.W. & Spady, R.H., 1991.
"An Efficient Semiparametric Estimator for Binary Response Models,"
70, Bell Communications - Economic Research Group.
- Klein, Roger W & Spady, Richard H, 1993. "An Efficient Semiparametric Estimator for Binary Response Models," Econometrica, Econometric Society, vol. 61(2), pages 387-421, March.
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