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Decomposition of Variables and Correlated Measurement Errors

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  • Lach, Saul

Abstract

This paper examines the bias in the OLS estimators when the regressors have measurement errors correlated in a particular manner. When a variable is decomposed into two components but only one of them is observed with error, the induced measurement error in the other component is identical but has the opposite sign. This specific correlation pattern enables us to assess the direction of the bias in the OLS estimators from observed data. In the standard EIV case this would require knowledge of the relative variances of the measurement errors. Examples of this type of decomposition in applied work are presented. Copyright 1993 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

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  • Lach, Saul, 1993. "Decomposition of Variables and Correlated Measurement Errors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 34(3), pages 715-725, August.
    • Handle: RePEc:ier:iecrev:v:34:y:1993:i:3:p:715-25
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    Cited by:

    1. Woods, James & Fuller, Cody, 2014. "Estimating base temperatures in econometric models that include degree days," Energy Economics, Elsevier, vol. 45(C), pages 166-171.
    2. Willasen, Y., 1998. "Deriving Bounds on the Structural Vector when the Measurement Errors are Correlated: An Elaboration of the Frisch/Reiersol Approach," Memorandum 06/1998, Oslo University, Department of Economics.

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