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Book Chapter Employment Location in Cities and Regions: Models and Applications

Occupation, education and social inequalities: a case study linking survey data sources to an urban microsimulation analysis

Authors

Editors

Francesca Pagliara, Michiel de Bok, David Simmonds, and Alan Wilson

Publication date

2012

Summary

This chapter
describes how a dynamic microsimulation model of the urban population,
initiated from census data, can be productively linked with rich
socio-economic survey data resources in order to give a more effective
understanding of the development of occupations and educational
qualifications through time and hence socio-economic inequalities. Small
area modelling of these elements is a key feature of understanding
labour markets and hence the distribution of employment. A selection of
strategies for linking data resources are discussed, some analytical
results presented, and discussion given on how these approaches can be
facilitated by the ‘NeISS’ infrastructural provision.
In the urban
simulation model, the city is represented as a complete but synthetic
array of households and their constituent individuals. The model is
capable of projections forward in time through the incorporation of
demographic processes relating not only to the major events of
fertility, mortality and migration, but also the formation and
dissolution of households and changes in individual health status. The
model is operational for every city or region in Great Britain. The
chapter looks at how this model can be linked with survey data from the
British Household Panel Survey, and the combined results used to explore
the evolution of two major socio-economic variables – occupation and
education – within the microsimulation model in a manner designed to
engage with extended research traditions in the sociological study of
social stratification.

DOI

http://dx.doi.org/10.1007/978-3-642-31779-8_10

Subjects

Urban Economy, Demography, and Microsimulation

Notes

Not held in Res Lib - bibliographic reference only

#521163


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