A comparison of sample survey measures of earnings of English graduates with administrative data. (21st February 2019)

• Record Type: Journal Article
• Authors: Britton, Jack; Shephard, Neil; Vignoles, Anna
• Is Part Of: Journal of the Royal Statistical Society. Volume 182:Number 3(2019)
• Page Start: 719
• Page End: 754
• Publication Date: 2019-02-21
• Subjects: Administrative data -- Graduate earnings -- Labour force survey -- Student loans; Social sciences -- Statistical methods -- Periodicals; Statistics -- Periodicals; 300.15195
• DOI: 10.1111/rssa.12382
• Languages: English
• ISSNs: 0964-1998

Abstract

Summary: Administrative data sets are increasingly used in research because of their excellent coverage and large scale. However, in the UK the use of administrative data on individuals' earnings, and particularly graduates' earnings, is novel. Understanding the strengths and weaknesses of such data is important as they are set to be used extensively for research and to inform policy. Here we compare survey‐based labour earnings data from the UK's Labour Force Survey (LFS) with UK Government administrative sources of individual level earnings data, focusing separately on young (up to age 32 years) graduates and non‐graduates. This type of administrative data set has few sample selection issues and is longitudinal and its large samples mean that the earnings of subpopulations can potentially be studied with low error. Overall we find a similar share of individuals with zero earnings in the LFS and administrative data, but a considerably higher share (conditionally on working) earning below £8000 in the administrative data. The LFS has generally higher earnings right through the distribution, though above the median a large share of the differences can potentially be explained by employee pension contributions. We also find considerably larger gender difference in the survey data. The findings hold for both graduates and non‐graduates. These differences are substantively important and suggest different conclusions about the gender wage gap, the graduate earnings premium and the extent of earnings inequality.