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Misreported schooling and returns to education: evidence from the UK

Author

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  • Erich Battistin

    (Institute for Fiscal Studies)

  • Barbara Sianesi

    (Institute for Fiscal Studies and Institute for Fiscal Studies)

Abstract

In this paper we study the impact of misreported treatment status on the estimation of causal treatment effects. We characterise the bias introduced by misclassification on the average treatment effect on the treated under the assumption of selection on observables. Although the bias of matching-type estimators computed from misclassified data cannot in general be signed, we show that the bias is most likely to be downward if misclassification does not depend on variables entering the selection-on-observables assumption, or only depends on such variables via the propensity score index. We extend the framework to multiple treatments. We provide results to bound the returns to a number of educational qualifications in the UK semi-parametrically, and by using the unique nature of our data we assess the plausibility for the two biases from measurement error and from omitted variables to cancel out.

Suggested Citation

  • Erich Battistin & Barbara Sianesi, 2006. "Misreported schooling and returns to education: evidence from the UK," CeMMAP working papers CWP07/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:07/06
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    File URL: http://cemmap.ifs.org.uk/wps/cwp0607.pdf
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    References listed on IDEAS

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    Cited by:

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    2. Joop Hartog & Aslan Zorlu, 2009. "How important is homeland education for refugees’ economic position in The Netherlands?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 22(1), pages 219-246, January.
    3. Anna Vignoles & Augustin de Coulon, 2008. "An Analysis of the Benefit of NVQ2 Qualifications Acquired at Age 26-34," CEE Discussion Papers 0106, Centre for the Economics of Education, LSE.
    4. Yingying Dong, 2012. "Regression Discontinuity Applications with Rounding Errors in the Running Variable," Working Papers 111206, University of California-Irvine, Department of Economics.
    5. Kristensen, Nicolai & Westergård-Nielsen, Niels C., 2006. "A Large-Scale Validation Study of Measurement Errors in Longitudinal Survey Data," IZA Discussion Papers 2329, Institute of Labor Economics (IZA).

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    More about this item

    Keywords

    Measurement Error; Misclassification; Programme Evaluation; Returns to Educational Qualifications; Treatment Effect; Bounds;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • I20 - Health, Education, and Welfare - - Education - - - General
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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