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Generalized Empirical Likelihood Inference For Nonlinear And Time Series Models Under Weak Identification

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  • Otsu, Taisuke

Abstract

This paper studies robust inference methods for nonlinear moment restriction models with weakly identified parameters in time series contexts. Our methods are based on generalized empirical likelihood with kernel smoothing. The proposed test statistics, which follow the standard 2 limiting distributions, are robust to weak identification and dependent data.The author is deeply grateful to Bruce Hansen, John Kennan, and Gautam Tripathi for their guidance and time. Comments from a coeditor and two anonymous referees substantially helped this revision. The author also thanks Allan Gregory, Patrik Guggenberger, Philip Haile, Hiroyuki Kasahara, Matthew Kim, Yuichi Kitamura, and seminar participants at Queen s University, University of Wisconsin, and the 2003 North America Summer Meeting of the Econometric Society for helpful discussions and suggestions. Financial support from the Alice Gengler Wisconsin Distinguished Graduate Fellowship and Wisconsin Alumni Research Foundation Dissertation Fellowship is gratefully acknowledged.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 22 (2006)
Issue (Month): 03 (June)
Pages: 513-527

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Handle: RePEc:cup:etheor:v:22:y:2006:i:03:p:513-527_06

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Cited by:
  1. Gong, Yun & Peng, Liang & Qi, Yongcheng, 2010. "Smoothed jackknife empirical likelihood method for ROC curve," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1520-1531, July.
  2. Andrews, Donald W.K. & Guggenberger, Patrik, 2010. "Applications of subsampling, hybrid, and size-correction methods," Journal of Econometrics, Elsevier, vol. 158(2), pages 285-305, October.
  3. Donald W.K. Andrews & Patrik Guggenberger, 2007. "Hybrid and Size-Corrected Subsample Methods," Cowles Foundation Discussion Papers 1606, Cowles Foundation for Research in Economics, Yale University.
  4. Moreira, Marcelo J. & Porter, Jack R. & Suarez, Gustavo A., 2009. "Bootstrap validity for the score test when instruments may be weak," Journal of Econometrics, Elsevier, vol. 149(1), pages 52-64, April.
  5. Martins, Luis F. & Gabriel, Vasco J., 2009. "New Keynesian Phillips Curves and potential identification failures: A Generalized Empirical Likelihood analysis," Journal of Macroeconomics, Elsevier, vol. 31(4), pages 561-571, December.
  6. Alain Guay & Jean-Fran├žois Lamarche, 2008. "The Information Content of Implied Probabilities to Detect Structural Change," Cahiers de recherche 0833, CIRPEE.
  7. Patrik Guggenberger & Richard Smith, 2005. "Generalized empirical likelihood tests in time series models with potential identification failure," CeMMAP working papers CWP01/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  8. Patrik Guggenberger, . "Applications of Subsampling, Hybrid, and Size-Correction Methods (joint with D.W.K. Andrews), 2005, this version May 2007," UCLA Economics Online Papers 414, UCLA Department of Economics.
  9. 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.

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