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Nonparametric Survey Response Errors

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  • Rosa L. Matzkin

Abstract

I present nonparametric methods to identify and estimate the biases associated with response errors. When applied to survey data, these methods can be used to analyze how observable and unobservable characteristics of the respondent, and characteristics of the design of the survey, affect errors in the responses. This provides a method to correct the biases that those errors generate, by using the estimated response errors to "undo" those biases. The results are useful also to design better surveys, since they point at characteristics of the design and of subpopulations of respondents that can provide identification of response errors. Several models are considered. Copyright 2007 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.

Suggested Citation

  • Rosa L. Matzkin, 2007. "Nonparametric Survey Response Errors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1411-1427, November.
    • Handle: RePEc:ier:iecrev:v:48:y:2007:i:4:p:1411-1427
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    Cited by:

    1. Hoderlein, Stefan & Winter, Joachim, 2010. "Structural measurement errors in nonseparable models," Journal of Econometrics, Elsevier, vol. 157(2), pages 432-440, August.
    2. Matzkin, Rosa L., 2016. "On independence conditions in nonseparable models: Observable and unobservable instruments," Journal of Econometrics, Elsevier, vol. 191(2), pages 302-311.
    3. Gutknecht, Daniel, 2011. "Nonclassical Measurement Error in a Nonlinear (Duration) Model," Economic Research Papers 270763, University of Warwick - Department of Economics.

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