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Bias from Classical and Other Forms of Measurement Error

Author

Listed:
  • Hyslop, Dean R
  • Imbens, Guido W

Abstract

We consider the implications of an alternative to the classical measurement-error model, in which the observed, mismeasured data are optimal predictions of the true values, given some information set. In this model, any measurement error is uncorrelated with the reported value and, by necessity, correlated with the true value of interest. In a regression model, such measurement error in the regressor does not lead to bias, whereas measurement error in the dependent variable leads to bias toward 0. In general, the measurement-error model, together with the information set, is critical for determining the bias in econometric estimates.

Suggested Citation

  • Hyslop, Dean R & Imbens, Guido W, 2001. "Bias from Classical and Other Forms of Measurement Error," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 475-481, October.
  • Handle: RePEc:bes:jnlbes:v:19:y:2001:i:4:p:475-81
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    References listed on IDEAS

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    1. David Card & Dean Hyslop, 1997. "Does Inflation "Grease the Wheels of the Labor Market"?," NBER Chapters,in: Reducing Inflation: Motivation and Strategy, pages 71-122 National Bureau of Economic Research, Inc.
    2. Angrist, Joshua D. & Krueger, Alan B., 1999. "Empirical strategies in labor economics," Handbook of Labor Economics,in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 23, pages 1277-1366 Elsevier.
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    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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