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Averaging of moment condition estimators

  • Xiaohong Chen

    (Institute for Fiscal Studies and Yale University)

  • David T. Jacho-Chavez
  • Oliver Linton

    ()

    (Institute for Fiscal Studies and Cambridge University)

We establish the consistency and asymptotic normality for a class of estimators that are linear combinations of a set of v n- consistent estimators whose cardinality increases with sample size. A special case of our framework corresponds to the conditional moment restriction and the implied estimator in that case is shown to achieve the semiparametric efficiency bound. The proofs do not rely on smoothness of underlying criterion functions.

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File URL: http://www.cemmap.ac.uk/wps/cwp261212.pdf
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP26/12.

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Date of creation: Sep 2012
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Handle: RePEc:ifs:cemmap:26/12
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  1. Rilstone, Paul & Ullah, Aman, 2005. "Corrigendum to "The second-order bias and mean squared error of nonlinear estimators": [Journal of Econometrics 75(2) (1996) 369-395]," Journal of Econometrics, Elsevier, vol. 124(1), pages 203-204, January.
  2. Barbara Rossi & Atsushi Inoue, 2010. "Testing for Weak Identification in Possibly Nonlinear Models," Working Papers 10-92, Duke University, Department of Economics.
  3. Yulia Kotlyarova & Victoria Zinde-Walsh, 2006. "Non And Semi-Parametric Estimation In Models With Unknown Smoothness," Departmental Working Papers 2006-15, McGill University, Department of Economics.
  4. Marcia M. A. Schafgans & Victoria Zinde-Walsh, 2010. "Smoothness adaptive average derivative estimation," Econometrics Journal, Royal Economic Society, vol. 13(1), pages 40-62, 02.
  5. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
  6. Francesco Bravo & Juan Carlos Escanciano & Taisuke Otsu, 2011. "A Simple Test for Identification in GMM under Conditional Moment Restrictions," Cowles Foundation Discussion Papers 1789, Cowles Foundation for Research in Economics, Yale University.
  7. Rilstone, Paul & Srivastava, V. K. & Ullah, Aman, 1996. "The second-order bias and mean squared error of nonlinear estimators," Journal of Econometrics, Elsevier, vol. 75(2), pages 369-395, December.
  8. Manuel A. Domínguez & Ignacio N. Lobato, 2004. "Consistent Estimation of Models Defined by Conditional Moment Restrictions," Econometrica, Econometric Society, vol. 72(5), pages 1601-1615, 09.
  9. Hansen, Lars Peter, 1985. "A method for calculating bounds on the asymptotic covariance matrices of generalized method of moments estimators," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 203-238.
  10. Koenker, Roger & Machado, Jose A. F., 1999. "GMM inference when the number of moment conditions is large," Journal of Econometrics, Elsevier, vol. 93(2), pages 327-344, December.
  11. Amemiya, Takeshi, 1974. "The nonlinear two-stage least-squares estimator," Journal of Econometrics, Elsevier, vol. 2(2), pages 105-110, July.
  12. Chen, Xiaohong & Pouzo, Demian, 2009. "Efficient estimation of semiparametric conditional moment models with possibly nonsmooth residuals," Journal of Econometrics, Elsevier, vol. 152(1), pages 46-60, September.
  13. Guido Kuersteiner & Ryo Okui, 2010. "Constructing Optimal Instruments by First-Stage Prediction Averaging," Econometrica, Econometric Society, vol. 78(2), pages 697-718, 03.
  14. Donald, Stephen G. & Imbens, Guido W. & Newey, Whitney K., 2003. "Empirical likelihood estimation and consistent tests with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 117(1), pages 55-93, November.
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