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Abstract
The UK is one of the countries with high share of population claiming health-related out of work benefits. Its share of claimants is reaching 6% of the working age population (Beatty and Fothergill, 2015). Share of working population on incapacity benefits exhibits a distinct spatial pattern with significantly lower share in the South East and pockets of higher claims in former mining areas. The persistence and the spatial disparity of incapacity benefit claims has been linked to the pattern of structural changes in the UK economy, deindustrialization, decline in manufacturing. Regional and local job opportunities influence the decision to apply for incapacity benefits. While the unemployment rates and incapacity claimant rates are potentially endogenously determined, household income represents the employment opportunities and can therefore account for the variation in the disability claims rates across localities. The aim of the study is to explain the incapacity benefit claims at the level of UK local authorities using the following variables: average household income for the locality, industry sector employment shares, educational qualifications, age profile, share of self-employed. Spatial econometrics model is used because local authority claiming rates exhibit spatial dependence. The analysis uses income data produced by Horizon 2020 IMAJINE project. The findings of this study are important for understanding the impact of welfare reform on incapacity benefit uptake.
Original language | English |
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Pages (from-to) | 35-48 |
Number of pages | 13 |
Journal | Romanian Journal of Regional Science |
Volume | 14 |
Issue number | 2 |
Publication status | Published - 30 Dec 2020 |
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Dive into the research topics of 'Explaining spatial patterns of incapacity benefit claimant rolls in the UK'. Together they form a unique fingerprint.Projects
- 1 Finished
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Integrative Mechanisms for Addressing Spatial Justice and Territorial Inequalities in Europe (IMAJINE) - SMB
Plotnikova, M. (PI)
01 Jan 2017 → 30 Jun 2022
Project: Externally funded research