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Displaying results 1 to 10 out of 47
This Data Insight uses a simulation model built from the Annual Survey of Hours and Earnings (ASHE) linked to 2011 Census – England and Wales dataset. The model compares two simulated labour markets: one where applicants from ethnic minority groups are less likely to be invited to interview (“callbacks”), and one where all applicants have the same chance of getting a callback.
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ASHE and official labour market statistics substantially underreport multiple jobholding. In HMRC PAYE data, not only is the level of multiple jobholding substantially higher but its prevalence among young women also becomes visible. Read this Data Insight from ADR UK fellow Darja Reuschke to find out more.
This Data Insight explores the factors that are associated with the receipt of careers advice and guidance among young adults in Wales.
This Data Insight explores how young workers are matched to firms across local labour markets in England, using the Longitudinal Education Outcomes (LEO) dataset. We focus on differences in ‘positive assortative matching’ – the extent to which high-skilled workers are matched to high-quality firms – which is assumed to increase productivity in many standard economic models.
This Data Insight uses the Longitudinal Education Outcomes (LEO) dataset – England to compare the labour market trajectories of students who followed academic and vocational pathways after their GCSEs. The insights point to a substantial gap in earnings growth, with students who followed academic education routes experiencing higher earnings growth in their careers. The research highlights the role of firms in explaining and amplifying this difference.
This Data Insight, from ADR UK fellow Daniel Derbyshire, combines data from the ASHE-Census 2011 dataset with data from the Annual Population Survey to examine the disability pay gap and disability employment gap across England and Wales. The insights presented here highlight how the nature and extent of labour market inequalities experienced by disabled people varies greatly across England and Wales.
This Data Insight uses the Migrant Workers Scan dataset (MWS) - an administrative register from HM Revenue and Customs that records every non-UK national applying for a National Insurance Number - to explore how the wages of migrants change over time, compared to the native population.
This Data Insight by Dr Michelle Jamieson analyses data relating to nurses and midwives and others of similar social grade.
This Data Insight by Dr Michelle Jamieson analyses data relating to nurses and midwives and others of similar social grade. Around 60% of people analysed lived within 10 km from of their place of work, a distance within which active travel is feasible. Yet over 70% of both groups travelled to work by car.
This study was summarised by Rianna during her internship at ADR England, with input and feedback from Ezgi Kaya who produced the original research. It looks at differences in job quality between UK-born and immigrant workers, using detailed data on pay, working hours, and job types.
