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Weighted Minimum Mean-Square Distance from Independence Estimation

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Abstract

In 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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File URL: http://cowles.econ.yale.edu/P/cd/d12b/d1288.pdf
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Bibliographic Info

Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1288.

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Length: 31 pages
Date of creation: Feb 2001
Date of revision:
Publication status: Published in Econometrica (September 2002), 70(5): 2035-2051
Handle: RePEc:cwl:cwldpp:1288

Note: CFP 1042
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Keywords: Semiparametric estimation; simultaneous equations models; empirical processes; extremum estimators;

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Cited by:
  1. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
  2. Xiaohong Chen & Oliver Linton & Ingrid Van Keilegom, 2003. "Estimation of Semiparametric Models when the Criterion Function is not Smooth," STICERD - Econometrics Paper Series /2003/450, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  3. Gaurab Aryal & Isabelle Perrigne & Quang Vuong, 2011. "Identification of Insurance Models with Multidimensional Screening," ANU Working Papers in Economics and Econometrics 2011-538, Australian National University, College of Business and Economics, School of Economics.
  4. Du, Zaichao, 2014. "Testing for serial independence of panel errors," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 248-261.

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