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Maximal uniform convergence rates in parametric estimation problems

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  • Walter Beckert
  • Daniel McFadden

    ()
    (Institute for Fiscal Studies and University of California, Berkeley)

Abstract

This paper considers parametric estimation problems with i.i.d. data. It focusses 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.

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File URL: http://cemmap.ifs.org.uk/wps/cwp0605.pdf
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Bibliographic Info

Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP06/05.

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Length: 20 pp.
Date of creation: Jun 2005
Date of revision:
Handle: RePEc:ifs:cemmap:06/05

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Postal: The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE
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Postal: The Institute for Fiscal Studies 7 Ridgmount Street LONDON WC1E 7AE
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Related research

Keywords: parametric estimators; uniform convergence; Hellinger distance; Locally Asymptotically Quadratic (LAQ) Families;

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  1. 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.
  2. Newey, Whitney K, 1991. "Uniform Convergence in Probability and Stochastic Equicontinuity," Econometrica, Econometric Society, vol. 59(4), pages 1161-67, July.
  3. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
  4. Klein, R.W. & Spady, R.H., 1991. "An Efficient Semiparametric Estimator for Binary Response Models," Papers 70, Bell Communications - Economic Research Group.
  5. repec:cup:etheor:v:9:y:1993:i:1:p:1-18 is not listed on IDEAS
  6. 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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