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Estimation of the Distribution of Hourly Pay from Household Survey Data: The Use of Missing Data Methods to Handle Measurement Error

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  • Gabriele Beissel-Durrant
  • Chris Skinner

Abstract

Measurement errors in survey data on hourly pay may lead to serious upward bias in low payestimates. We consider how to correct for this bias when auxiliary accurately measured dataare available for a subsample. An application to the UK Labour Force Survey is described.The use of fractional imputation, nearest neighbour imputation, predictive mean matchingand propensity score weighting are considered. Properties of point estimators are comparedboth theoretically and by simulation. A fractional predictive mean matching imputationapproach is advocated. It performs similarly to propensity score weighting, but displaysslight advantages of robustness and efficiency.

Suggested Citation

  • Gabriele Beissel-Durrant & Chris Skinner, 2003. "Estimation of the Distribution of Hourly Pay from Household Survey Data: The Use of Missing Data Methods to Handle Measurement Error," CeMMAP working papers 12/03, Institute for Fiscal Studies.
    • Handle: RePEc:azt:cemmap:12/03
    DOI: 10.1920/wp.cem.2003.1203
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    References listed on IDEAS

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    1. Richard Dickens & Alan Manning, 2004. "Has the national minimum wage reduced UK wage inequality?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(4), pages 613-626, November.
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