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School of Economics

Using Census, Institutional and Geospatial Data to Estimate the Socio-Economic Profile of Post-School Students by Institutional Type

Abstract

dc:description.abstract

The socio-economic profile of students who are participating in post-school education; and the distribution of their socio-economic characteristics between universities and colleges, between institutions of a similar type, and within particular institutions is not well understood. Part of the reason for this is because potential data sets that could be used to answer this fall short on dimensions needed to fully explore the extent of socio-economic differences amongst student bodies by institutional type. I, therefore, generate a data set that draws on institutional, census, and geospatial information to estimate the socio-economic background of students' home postal code. Using this data set, I compare the mean statistic and generalised entropy index of a range of individual and household socio-economic postal code indicators for student bodies by institutional type to descriptively analyse their socio-economic profile. I show student bodies at traditional universities and Unisa appear socio-economically similar and display higher socio-economic circumstances than that of student bodies at comprehensive universities, universities of technology and TVET colleges who appear socio-economically similar. Between 2008 and 2019, the mean socio-economic profile declined for all student bodies, whereas there was no uniform trend for whether socio-economic heterogeneity was increasing or decreasing over time by university type. Lastly, my findings suggest there is more evidence for horizontal stratification between particular universities (regardless of their institutional type) rather than between university types, or between universities and TVET colleges.

Degree

thesis:*
Grantor
School of Economics
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Culligan, Samantha
Advisors dc:contributor.advisor
  • Branson, Nicola
  • Leibbrandt, Murray

Subjects

dc:subject × 1

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11427/37101
OAI identifier oai:identifier
oai:open.uct.ac.za:11427/37101

Chain of custody

source
Harvested from
University of Cape Town
Base URL
open.uct.ac.za/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
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citation

Culligan, Samantha. Using Census, Institutional and Geospatial Data to Estimate the Socio-Economic Profile of Post-School Students by Institutional Type. School of Economics, 2022. http://hdl.handle.net/11427/37101