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An Alternative Way of ComputingEfficient Instrumental VariableEstimators

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Author Info

  • Xiaohong Chen
  • David T. Jacho-Chávez
  • Oliver Linton

Abstract

A new way of constructing efficient semiparametric instrumental variableestimators is proposed. The method involves the combination of a large number ofpossibly inefficient estimators rather than combining the instruments into anoptimal instrument function. The consistency and asymptotic normality isestablished for a class of estimators that are linear combinations of a set ofv?? ??consistent estimators whose cardinality increases with sample size. It is shown thatthe semiparametrically efficient estimator lies in this class. The proofs do not relyon smoothness of underlying criterion functions. Potential use of the estimator canovercome the undersized sample problem. in simultaneous equation systemestimation.

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File URL: http://sticerd.lse.ac.uk/dps/em/em536.pdf
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Bibliographic Info

Paper provided by Suntory and Toyota International Centres for Economics and Related Disciplines, LSE in its series STICERD - Econometrics Paper Series with number /2009/536.

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Date of creation: Jun 2009
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Handle: RePEc:cep:stiecm:/2009/536

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Web page: http://sticerd.lse.ac.uk/_new/publications/default.asp

Related research

Keywords: Instrumental Variables; Minimum Distance; Semiparametric Efficiency; Two-Stage Least Squares;

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Cited by:
  1. Lorenzo Ricci & David Veredas, 2012. "TailCoR," Banco de Espa�a Working Papers 1227, Banco de Espa�a.
  2. Carrasco, Marine, 2012. "A regularization approach to the many instruments problem," Journal of Econometrics, Elsevier, vol. 170(2), pages 383-398.
  3. Robert Engle & Neil Shephard & Kevin Shepphard, 2008. "Fitting vast dimensional time-varying covariance models," OFRC Working Papers Series 2008fe30, Oxford Financial Research Centre.

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