Using Census Data to Predict Income Support Dependency

Bibliographic Data

ID6326257
AuthorsMichael Noble (University Lecturer in Applied Social Studies, Department of Applied Social Studies and Social Research, University of Oxford), Sin Yi Cheung (0000-0002-9913-1451, University of Oxford), George Smith (0000-0002-4549-4775, University of Oxford), Tom Smith (0000-0001-5084-8729, University of Oxford), Tom S Smith (0000-0001-7541-8311, University of Oxford)
Year1995
Volume23
Issue4
Pages327-333
Publication date1995-10-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenuePolicy & Politics (JOURNAL)
Journal identifiersISSN: 0305-5736 • E-ISSN: 1470-8442
PublisherBristol University Press (PUBLISHER • GB)
DOI10.1332/030557395782200572
OpenAlexW1968872144
LanguageEN
Citations received3

This article briefly reviews the development of area measures of deprivation. It examines the construction of indices of deprivation and the uses to which such indices are put, particularly in respect of resource allocation. Previous attempts to develop indices have been based on a priori definitions of deprivation (eg the Department of the Environment’s z score and its successor, the 1991 Deprivation Index) and have lacked an empirical base. The inherent difficulties in validation of such indices are briefly rehearsed and the article presents work in progress on an index which predicts dependency on income support. The index is based on weighted Census of Population variables and is constructed using multiple regression techniques. We present the findings and two validation procedures

Actuarial science · Census · Dependency (UML · Econometrics · Economics · Index (typography · Population · Sociology · Statistics · Successor cardinal · Computer Science · Demography · Income, Poverty, and Inequality · Mathematics · Spatial and Panel Data Analysis · Urban, Neighborhood, and Segregation Studies · Artificial Intelligence