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Nonparametric Bounds in the Presence of Item Nonresponse, Unfolding Brackets and Anchoring

Author

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  • Vazquez-Alvarez, R.

    (Tilburg University, Center For Economic Research)

  • Melenberg, B.

    (Tilburg University, Center For Economic Research)

  • van Soest, A.H.O.

    (Tilburg University, Center For Economic Research)

Abstract

Household surveys often suffer from nonresponse on variables such as income, savings or wealth.Recent work by Manski shows how bounds on conditional quantiles of the variable of interest can be derived, allowing for any type of nonrandom item nonresponse.The width between these bounds can be reduced using follow up questions in the form of unfolding brackets for initial item nonrespondents.Recent evidence, however, suggests that such a design is vulnerable to anchoring effects.In this paper Manski's bounds are extended to incorporate the information provided by the bracket respondents allowing for different forms of anchoring.The new bounds are applied to earnings in the 1996 wave of the Health and Retirement Survey.The results show that the categorical questions can be useful to increase precision of the bounds, even if anchoring is allowed for.

Suggested Citation

  • Vazquez-Alvarez, R. & Melenberg, B. & van Soest, A.H.O., 2001. "Nonparametric Bounds in the Presence of Item Nonresponse, Unfolding Brackets and Anchoring," Discussion Paper 2001-67, Tilburg University, Center for Economic Research.
  • Handle: RePEc:tiu:tiucen:cb4befff-4232-459b-ab68-281ea58113c6
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    References listed on IDEAS

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    1. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-323, May.
    2. Green, Donald & Jacowitz, Karen E. & Kahneman, Daniel & McFadden, Daniel, 1998. "Referendum contingent valuation, anchoring, and willingness to pay for public goods," Resource and Energy Economics, Elsevier, vol. 20(2), pages 85-116, June.
    3. Richard O‘Conor & Magnus Johannesson & Per-Olov Johansson, 1999. "Stated Preferences, Real Behaviour and Anchoring: Some Empirical Evidence," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 13(2), pages 235-248, March.
    4. Herriges, Joseph A. & Shogren, Jason F., 1996. "Starting Point Bias in Dichotomous Choice Valuation with Follow-Up Questioning," Journal of Environmental Economics and Management, Elsevier, vol. 30(1), pages 112-131, January.
    5. Horowitz, Joel L. & Manski, Charles F., 1998. "Censoring of outcomes and regressors due to survey nonresponse: Identification and estimation using weights and imputations," Journal of Econometrics, Elsevier, vol. 84(1), pages 37-58, May.
    6. Cameron Trudy Ann & Quiggin John, 1994. "Estimation Using Contingent Valuation Data from a Dichotomous Choice with Follow-Up Questionnaire," Journal of Environmental Economics and Management, Elsevier, vol. 27(3), pages 218-234, November.
    7. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
    8. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    9. Michael Lechner, 1999. "Nonparametric bounds on employment and income effects of continuous vocational training in East Germany," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 1-28.
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    Citations

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    Cited by:

    1. Christian Bontemps & Thierry Magnac & Eric Maurin, 2012. "Set Identified Linear Models," Econometrica, Econometric Society, vol. 80(3), pages 1129-1155, May.
    2. Nicoletti, Cheti, 2006. "Nonresponse in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 132(2), pages 461-489, June.
    3. Tiefensee, Anita & Grabka, Markus M., 2016. "Comparing Wealth - Data Quality of the HFCS," EconStor Open Access Articles, ZBW - Leibniz Information Centre for Economics, pages 119-142.
    4. Rosalia Vazquez-Alvarez, 2003. "Anchoring Bias and Covariate Nonresponse," University of St. Gallen Department of Economics working paper series 2003 2003-19, Department of Economics, University of St. Gallen.

    More about this item

    Keywords

    microeconomics; nonresponse;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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