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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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Author Info
Gabriele Beissel-Durrant
Chris Skinner () (Institute for Fiscal Studies and University of Southampton)
Abstract

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

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File URL: http://cemmap.ifs.org.uk/wps/cwp0312.pdf
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP12/03.

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Length: 28 pp.
Date of creation: May 2003
Date of revision:
Handle: RePEc:ifs:cemmap:12/03

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  1. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 287-96, July.
  2. Richard Dickens & Alan Manning, 2002. "Has The National Minimum Wage Reduced UK Wage Inequality?," CEP Discussion Papers dp0533, Centre for Economic Performance, LSE. [Downloadable!]
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