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The Zero-Information-Limit Condition and Spurious Inference in Weakly Identified Models

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Author Info
Charles Nelson
Richard Startz

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Abstract

The 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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Paper provided by University of Washington, Department of Economics in its series Working Papers with number UWEC-2004-03-FC.

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Date of creation: Feb 2004
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Publication status: Forthcoming in Journal of Econometrics
Handle: RePEc:udb:wpaper:uwec-2004-03-fc

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  1. 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," Working Papers UWEC-2008-06-R, University of Washington, Department of Economics, revised Sep 2008. [Downloadable!]
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This page was last updated on 2009-11-24.


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