Maximal Uniform Convergence Rates in Parametric Estimation Problems
AbstractThis paper considers parametric estimation problems with i.i.d. data. It focusses 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.
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Bibliographic InfoPaper provided by Birkbeck, Department of Economics, Mathematics & Statistics in its series Birkbeck Working Papers in Economics and Finance with number 0405.
Date of creation: Nov 2004
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Other versions of this item:
- Beckert, Walter & McFadden, Daniel L., 2010. "Maximal Uniform Convergence Rates In Parametric Estimation Problems," Econometric Theory, Cambridge University Press, vol. 26(02), pages 469-500, April.
- 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
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- 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.
- 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.
- 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.
- Newey, Whitney K, 1991.
"Uniform Convergence in Probability and Stochastic Equicontinuity,"
Econometric Society, vol. 59(4), pages 1161-67, July.
- Newey, W.K., 1989. "Uniform Convergence In Probability And Stochastic Equicontinuity," Papers 342, Princeton, Department of Economics - Econometric Research Program.
- repec:cup:etheor:v:9:y:1993:i:1:p:1-18 is not listed on IDEAS
- Klein, Roger W & Spady, Richard H, 1993.
"An Efficient Semiparametric Estimator for Binary Response Models,"
Econometric Society, vol. 61(2), pages 387-421, March.
- Klein, R.W. & Spady, R.H., 1991. "An Efficient Semiparametric Estimator for Binary Response Models," Papers 70, Bell Communications - Economic Research Group.
- 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.
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