A Comparison of Sample Survey Measures of Earnings of English Graduates with Administrative Data

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.

Are You Being Asked? Impacts of Respondent Selection on Measuring Employment

“…Quality issues with earnings data across survey and administrative sources have also been raised. In the U.K., Britton et al (2019) find systematically lower reporting of earnings in a dataset linking administrative tax records with student loan data, as compared to the concurrent Labor Force Survey -likely due to a combination of low survey response in the LFS from low/irregularly-paid earners, as well as a higher share of self-employed workers with no income in the administrative data (perhaps due to underreporting to avoid tax obligations).…”

Who does and doesn't pay taxes?

“…Much is made of gender pay gap statistics, including those making use of tax data. These rely on tax data being an accurate measure of incomes, and previous research has noted that the gender pay gap is smaller in tax data than in surveys (Britton et al, 2019). Given the prevalence of non-compliance and gender-disparity in compliance behaviour, these results indicate that the administrative data underestimate the pay gap, driven by the differences in extensive margin behaviour, and this could be part of the reason for the patterns previously observed.…”

Is Improving Access to University Enough? Socio‐Economic Gaps in the Earnings of English Graduates

“…Our data by contrast is able to provide insight into graduates’ earnings up to more than a decade after graduation. More extensive detail on the data set is provided in 2019, Shephard and Vignoles (). We have a 10% sub sample of all borrowers from the English part of the SLC, which means they had to be domiciled in England upon application to university and attend a university in the UK.…”

“…Figure shows the earnings distribution for male and female graduates from higher income households (grey triangles), graduates from lower income households (black circles) and for non‐graduates (grey line), for the 1999 cohort in 2012/13. The non‐graduate sample comes from the HMRC databases (more information is given in Britton et al ., ), including a discussion of the relatively high proportion of graduates and non‐graduates who have zero or low earnings. In that paper we argue this is a combination of higher earners who are working abroad and hence do not pay tax, lower earners with intermittent attachment to the labour market and part time and self‐employed workers who will fall below the tax threshold.).…”