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Response error in a transformation model with an application to earnings-equation estimation *

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  • Jason Abrevaya
  • Jerry A. Hausman

Abstract

This paper considers estimation of a transformation model in which the transformed dependent variable is subject to classical measurement error. We consider cases in which the transformation function is known and unspecified. In special cases (e.g. log and square-root transformations), least-squares or non-linear least-squares estimators are applicable. A flexible approximation approach (based on Taylor expansion) is proposed for a parametrized transformation function (like the Box--Cox model), and a semi-parametric approach (combining a semi-parametric linear-index estimator and non-parametric regression) is proposed for the case of an unspecified transformation function. The methods are applied to the estimation of earnings equations, using wage data from the Current Population Survey (CPS). Copyright Royal Economic Socciety 2004

Suggested Citation

  • Jason Abrevaya & Jerry A. Hausman, 2004. "Response error in a transformation model with an application to earnings-equation estimation *," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 366-388, December.
    • Handle: RePEc:ect:emjrnl:v:7:y:2004:i:2:p:366-388
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    Cited by:

    1. Sundström, David, 2016. "The Competition Effect in a Public Procurement Model: An error-in-variables approach," Umeå Economic Studies 920, Umeå University, Department of Economics, revised 17 Jun 2016.
    2. Amit Gandhi Gandhi & Zhentong Lu & Xiaoxia Shi, 2013. "Estimating demand for differentiated products with error in market shares," CeMMAP working papers 03/13, Institute for Fiscal Studies.
    3. Christoph Breunig & Stephan Martin, 2020. "Nonclassical Measurement Error in the Outcome Variable," Papers 2009.12665, arXiv.org, revised May 2021.
    4. Kenneth Benoit & Michael Laver & Slava Mikhaylov, 2009. "Treating Words as Data with Error: Uncertainty in Text Statements of Policy Positions," American Journal of Political Science, John Wiley & Sons, vol. 53(2), pages 495-513, April.
    5. Pitt, Mark M & Khandker, Shahidur R & Cartwright, Jennifer, 2006. "Empowering Women with Micro Finance: Evidence from Bangladesh," Economic Development and Cultural Change, University of Chicago Press, vol. 54(4), pages 791-831, July.

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