The University of Southampton
University of Southampton Institutional Repository

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

Beissel-Durrant, Gabriele and Skinner, Chris (2004) Estimation of the Distribution of Hourly Pay from Household Survey Data: The Use of Missing Data Methods to Handle Measurement Error , Southampton, UK Southampton Statistical Sciences Research Institute 27pp. (S3RI Methodology Working Papers, M04/08).

Record type: Monograph (Project Report)

Abstract

This paper considers the application of missing data methods to a measurement error problem arising in the estimation of the distribution of hourly pay in the United Kingdom, using data from the Labour Force Survey. Errors in the measurement of hourly pay lead to bias and the aim is to use auxiliary data, measured accurately for a subsample, to correct for this bias. Alternative point estimators are considered, based upon a variety of imputation and weighting approaches, including fractional imputation, nearest neighbour imputation, predictive mean matching and propensity score weighting. Properties of these point estimators are then 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.

PDF 8181-01.pdf - Other
Download (268kB)

More information

Published date: 2004

Identifiers

Local EPrints ID: 8181
URI: http://eprints.soton.ac.uk/id/eprint/8181
PURE UUID: 94dc0d55-13e3-4e27-8e5e-bbc7962d15b7

Catalogue record

Date deposited: 11 Jul 2004
Last modified: 17 Jul 2017 17:13

Export record

Contributors

Author: Gabriele Beissel-Durrant
Author: Chris Skinner

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×