The zero-information-limit condition and spurious inference in weakly identified models
AbstractThe fact that weak instruments lead to spurious inference is now widely recognized. In this paper we ask whether spurious inference occurs more generally in weakly identified models. To distinguish between models where spurious inference will occur from those where it does not, we introduce the Zero-Information-Limit-Condition (ZILC). When ZILC holds, the information or precision of parameter estimates is overestimated. We discuss how ZILC applies to models encountered in practice and show that spurious inference does occur when ZILC holds.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 138 (2007)
Issue (Month): 1 (May)
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Web page: http://www.elsevier.com/locate/jeconom
Other versions of this item:
- Charles Nelson & Richard Startz, 2007. "The Zero-Information-Limit-Condition and Spurious Inference in Weakly Identified Models," Working Papers UWEC-2006-07-P, University of Washington, Department of Economics.
- Charles Nelson & Richard Startz, 2004. "The Zero-Information-Limit Condition and Spurious Inference in Weakly Identified Models," Working Papers UWEC-2004-03-FC, University of Washington, Department of Economics.
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- Xu Cheng, 2014. "Uniform Inference in Nonlinear Models with Mixed Identification Strength," PIER Working Paper Archive 14-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Juan Urquiza, 2011. "Income Asymmetries and the Permanent Income Hypothesis," Documentos de Trabajo 409, Instituto de Economia. Pontificia Universidad Católica de Chile..
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- Andrews, Donald W.K. & Cheng, Xu, 2013.
"Maximum likelihood estimation and uniform inference with sporadic identification failure,"
Journal of Econometrics,
Elsevier, vol. 173(1), pages 36-56.
- Donald W. K. Andrews & Xu Cheng, 2011. "Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure," Cowles Foundation Discussion Papers 1824, Cowles Foundation for Research in Economics, Yale University.
- Donald W. K. Andrews & Xu Cheng, 2011. "Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure," Cowles Foundation Discussion Papers 1824R, Cowles Foundation for Research in Economics, Yale University, revised Oct 2012.
- Jun Ma & Charles R. Nelson, 2008.
"Valid Inference for a Class of Models Where Standard Inference Performs Poorly: Including Nonlinear Regression, ARMA, GARCH, and Unobserved Components,"
UWEC-2008-06-R, University of Washington, Department of Economics, revised Sep 2008.
- Ma, Jun & Nelson, Charles R., 2010. "Valid Inference for a Class of Models Where Standard Inference Performs Poorly: Including Nonlinear Regression, ARMA, GARCH, and Unobserved Components," Economics Series 256, Institute for Advanced Studies.
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"Frequentist inference in weakly identified DSGE models,"
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- Guerron-Quintana, Pablo A. & Inoue, Atsushi & Kilian, Lutz, 2009. "Frequentist Inference in Weakly Identified DSGE Models," CEPR Discussion Papers 7447, C.E.P.R. Discussion Papers.
- Morley, James & Piger, Jeremy, 2008. "Trend/cycle decomposition of regime-switching processes," Journal of Econometrics, Elsevier, vol. 146(2), pages 220-226, October.
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