Using linked longitudinal administrative data to identify social disadvantage

Pattaro, S. , Bailey, N. and Dibben, C. (2019) Using linked longitudinal administrative data to identify social disadvantage. Social Indicators Research, (doi:10.1007/s11205-019-02173-1) (Early Online Publication)

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Abstract

Administrative data are widely used to construct indicators of social disadvantage, such as Free School Meals eligibility and Indices of Multiple Deprivation, for policy purposes. For research these indicators are often a compromise between accuracy and simplicity, because they rely on cross-sectional data. The growing availability of longitudinal administrative data may aid construction of more accurate indicators for research. To illustrate this potential, we use administrative data on welfare benefits from DWP’s National Benefits Database and annual earnings from employment from HMRC’s P14/P60 data to reconstruct individual labour market histories over a 5-year period. These administrative datasets were linked to survey data from the Poverty and Social Exclusion UK 2012. Results from descriptive and logistic regression analyses show that longitudinal measures correlate highly with survey responses on the same topic and are stronger predictors of poverty risks than measures based on cross-sectional data. These results suggest that longitudinal administrative measures would have potentially wide-ranging applications in policy as well as poverty research.

Item Type:Articles
Status:Early Online Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Bailey, Professor Nick and Pattaro, Dr Serena
Authors: Pattaro, S., Bailey, N., and Dibben, C.
College/School:College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:Social Indicators Research
Publisher:Springer
ISSN:0303-8300
ISSN (Online):1573-0921
Published Online:20 September 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Social Indicators Research 2019
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
163737Poverty and Social Exclusion in the United Kingdom: the 2010 SurveyES/G035784/1 (PI Prof David Gordon)Nick BaileyEconomic and Social Research Council (ESRC)ES/G035784/1S&PS - Urban Studies
300676Wider impact of benefit sanctions on healthNick BaileyEconomic and Social Research Council (ESRC)ES/R005729/1S&PS - Urban Studies

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