Weighted Minimum Mean-Square Distance from Independence Estimation
AbstractIn this paper we introduce a family of semi-parametric estimators, suggested by Manski's minimum mean-square distance from independence estimator. We establish the strong consistency, asymptotic normality and consistency of bootstrap estimates of the sampling distribution and the asymptotic variance of these estimators.
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Bibliographic InfoPaper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1288.
Length: 31 pages
Date of creation: Feb 2001
Date of revision:
Publication status: Published in Econometrica (September 2002), 70(5): 2035-2051
Note: CFP 1042
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Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Phone: (203) 432-3702
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Web page: http://cowles.econ.yale.edu/
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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
Other versions of this item:
- Donald J. Brown & Marten H. Wegkamp, 2002. "Weighted Minimum Mean-Square Distance from Independence Estimation," Econometrica, Econometric Society, vol. 70(5), pages 2035-2051, September.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2001-05-16 (All new papers)
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