Geodemographics: creating a classification at the level of the individual -PhD thesis-

Publication type

Thesis/Degree/Other Honours


Publication date

June 1, 2014


This research challenges the existing geodemographics ethos by
investigating the benefit to be gained from a move away from
conventional areal unit categorisation to systems capable of classifying
at the individual level. This research will present a unique framework
through which classifications can be developed at this level of
resolution. Inherently methodological, a local classification for Leeds
(UK) will be presented plus further examples of this applied framework.
Issues such as ecological fallacy, Modifiable Areal Unit Problem and
generalisation are aspects to be considered when interpreting spatially
aggregated data. A move away from such problems is one of the central
objectives of this research. Data variables from the UK’s 2001 Small
Area Microdata file underpin this research. These variables undergo
transformation from categorical states into scale variables based on
gross monthly income data present in the British Household Panel Survey
therefore enabling effective clustering. Micro-simulation is then
employed to create an individual-level population. The framework
presented comprises entirely census variables but also demonstrates a
linkage capability to other non-census datasets, such as the British
Household Panel Survey (now Understanding Society), for deeper
profiling, classification validation and enrichment.




Thesis embargoed until 01 Sept. 2019

Not held in Research Library - bibliographic reference only



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