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Exponential Tilting with Weak Instruments: Estimation and Testing

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  • MEHMET CANER

    (UNIVERSITY OF PITTSBURGH)

Abstract

This article analyses exponential tilting estimator with weak instruments in a nonlinear framework. Our paper differs from the previous literature in the context of consistency proof. Tests that are robust to the identification problem are also analysed. These are Anderson-Rubin and Kleibergen types of test statistics. We also conduct a simulation study wherein we compare empirical likelihood and continuous updating-based tests with exponential tilting (ET)-based ones. The designs involve GARCH(1,1) and contaminated structural errors. We find that ET-based Kleibergen test has the best size among these competitors. Copyright (c) Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2010.

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Paper provided by EconWPA in its series Econometrics with number 0509017.

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Date of creation: 12 Sep 2005
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Handle: RePEc:wpa:wuwpem:0509017

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  1. Kocherlakota, Narayana R., 1990. "On tests of representative consumer asset pricing models," Journal of Monetary Economics, Elsevier, vol. 26(2), pages 285-304, October.
  2. Whitney Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  3. Guggenberger, Patrik & Smith, Richard J., 2005. "Generalized Empirical Likelihood Estimators And Tests Under Partial, Weak, And Strong Identification," Econometric Theory, Cambridge University Press, vol. 21(04), pages 667-709, August.
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Cited by:
  1. Mehmet Caner, 2006. "Near Exogeneity and Weak Identification in Generlized Empirical Likelihood estimators : Fixed and Many Moment Asymptotics," Working Papers 212, University of Pittsburgh, Department of Economics, revised Jan 2006.
  2. Patrik Buggenberger & Richard Smith, 2003. "Generalized empirical likelihood estimators and tests under partial, weak and strong identification," CeMMAP working papers CWP08/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  3. Guggenberger, Patrik & Ramalho, Joaquim J.S. & Smith, Richard J., 2012. "GEL statistics under weak identification," Journal of Econometrics, Elsevier, vol. 170(2), pages 331-349.
  4. Donald W.K. Andrews & James H. Stock, 2005. "Inference with Weak Instruments," Cowles Foundation Discussion Papers 1530, Cowles Foundation for Research in Economics, Yale University.
  5. Alain Guay & Jean-Fran├žois Lamarche, 2008. "The Information Content of Implied Probabilities to Detect Structural Change," Cahiers de recherche 0833, CIRPEE.
  6. Paul Levine & Luis F. Martins & Vasco J. Gabriel, 2006. "Robust Estimates of the New Keynesian Phillips Curve," School of Economics Discussion Papers 0206, School of Economics, University of Surrey.
  7. Richard Smith, 2005. "Weak instruments and empirical likelihood: a discussion of the papers by DWK Andrews and JH Stock and Y Kitamura," CeMMAP working papers CWP13/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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