The stability of geodemographic cluster assignments over an intercensal period
Alexander Singleton; Michail Pavlis; Paul A. Longley (2016). Journal of Geographical Systems, 18(2), 97-123. DOI: 10.1007/s10109-016-0226-x
Abstract
A geodemographic classification provides a set of categorical summaries of the built and socio-economic characteristics of small geographic areas. Many classifications, including that developed in this paper, are created entirely from data extracted from a single decennial census of population. Such classifications are often criticised as becoming less useful over time because of the changing composition of small geographic areas. This paper presents a methodology for exploring the veracity of this assertion, by examining changes in UK census-based geodemographic indicators over time, as well as a substantive interpretation of the overall results. We present an innovative methodology that classifies both 2001 and 2011 census data inputs utilising a unified geography and set of attributes to create a classification that spans both census periods. Through this classification, we examine the temporal stability of the clusters and whether other secondary data sources and internal measures might usefully indicate local uncertainties in such a classification during an intercensal period.
Extended Summary
This research investigates whether geodemographic classifications—systems that categorise small geographic areas by their social and economic characteristics—remain accurate throughout the decade between national censuses. The study addresses growing concerns that these neighbourhood classification systems, widely used for public service planning and commercial targeting, become obsolete as local populations change over time. Using data from England’s 2001 and 2011 censuses, the research develops an innovative methodology that creates a unified classification spanning both time periods. Rather than analysing each census separately, this approach pools data from both decades using 55 consistent variables across 171,372 output areas (small geographic zones containing approximately 300 residents each). The analysis employs k-means clustering to identify eight distinct neighbourhood types: suburban diversity, ethnicity central, intermediate areas, students and aspiring professionals, county living and retirement, blue-collar suburbanites, professional prosperity, and hard-up households. The findings reveal that 39% of output areas (46,078 zones) changed their geodemographic classification between 2001 and 2011, with 85.6% of these changes occurring in urban areas. The most significant transition involved areas moving from ‘hard-up households’ to ‘suburban diversity’, reflecting increased ethnic diversity in traditionally white suburban areas. Regional variations emerged, with London experiencing the greatest instability—only 16.7% of ‘hard-up households’ areas remained in that category by 2011. The research demonstrates that certain variables have disproportionate influence on classification stability, particularly population density, housing type (especially terraced houses and flats), and ethnicity measures. The study explores whether ancillary data sources—such as annual population estimates, council tax valuations, and property transactions—could help identify areas likely to change classification during intercensal periods. These secondary indicators showed statistically significant differences between stable and changing areas, suggesting potential for developing early warning systems. The work challenges assumptions about geodemographic stability whilst highlighting opportunities for ‘open geodemographics’ using publicly available data. The findings have important implications for organisations relying on census-based classifications for resource allocation, service planning, and market research, particularly in rapidly changing urban environments where traditional classifications may quickly become outdated.
Key Findings
- 39% of English output areas changed geodemographic classification between 2001-2011, with 85.6% of changes occurring in urban areas
- London showed greatest classification instability, with only 16.7% of ‘hard-up households’ areas maintaining their category over the decade
- The largest single transition involved areas moving from ‘hard-up households’ to ‘suburban diversity’, reflecting increasing ethnic diversity in suburbs
- Population density, housing type, and ethnicity measures have disproportionate influence on neighbourhood classification stability over time
- Secondary data sources like property transactions and population estimates can help identify areas likely to change classification between censuses
Citation
@article{singleton2016stability,
author = {Alexander Singleton; Michail Pavlis; Paul A. Longley},
title = {The stability of geodemographic cluster assignments over an intercensal period},
journal = {Journal of Geographical Systems},
year = {2016},
volume = {18(2)},
pages = {97-123},
doi = {10.1007/s10109-016-0226-x}
}