The simulation of small-area migrant populations through integration of aggregate and disaggregate data sources
The simulation of small-area migrant populations through integration of aggregate and disaggregate data sources
In Western Europe, the impact of migration on national, regional and local population change has outgrown that of natural change through births and deaths. A geographical approach to the study of migration is however seriously hampered by the lack of spatially detailed migrant datasets. Researchers are commonly faced with a choice between survey data, which offer detailed demographic and socio-economic information about migrant individuals and households, and census data, which provide information on the whole population of a country at a fine spatial scale, but are only released in the form of aggregate tables. As a result, very little is known about migrant populations in small areas.
This thesis describes an innovative methodology to create small-area migrant microdata through the use of microsimulation. The model is applied to the integration of aggregate and disaggregate migrant data from the 1991 British Census of Population. We demonstrate that it is possible to characterise the migrant population resident in a small area by combining detailed area-level information about the small area with detailed attribute information about migrant individuals. The Samples of Anonymised Records (SARs) tell us who is moving, whilst the Small Area and Local Base Statistics (SAS/LBS) tell us where migrants move to. We simulate small-area migrant populations by fitting a selection of migrant individual records extracted from the SARs into known small-area migrant counts provided by the SAS/LBS. The search for the best fit is performed in an iterative fashion, using a combinatorial algorithm adapted from the hill-climbing technique. Three computer programs are designed and tested in an empirical study based in the West Midlands, more particularly in the districts of Birmingham and Solihull.
The migrant microdatabase thus created represents a considerable gain over standard census outputs, as it successfully integrates the highest levels of spatial and attribute disaggregation currently available in different census datasets. The potential of analysis of this new database resource is shown to be considerable. The methodology developed in this thesis could be applied to the integration of other aggregate and disaggregate datasets and to topics other than migration.
University of Southampton
1999
Wanders, Anne-Christine
(1999)
The simulation of small-area migrant populations through integration of aggregate and disaggregate data sources.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
In Western Europe, the impact of migration on national, regional and local population change has outgrown that of natural change through births and deaths. A geographical approach to the study of migration is however seriously hampered by the lack of spatially detailed migrant datasets. Researchers are commonly faced with a choice between survey data, which offer detailed demographic and socio-economic information about migrant individuals and households, and census data, which provide information on the whole population of a country at a fine spatial scale, but are only released in the form of aggregate tables. As a result, very little is known about migrant populations in small areas.
This thesis describes an innovative methodology to create small-area migrant microdata through the use of microsimulation. The model is applied to the integration of aggregate and disaggregate migrant data from the 1991 British Census of Population. We demonstrate that it is possible to characterise the migrant population resident in a small area by combining detailed area-level information about the small area with detailed attribute information about migrant individuals. The Samples of Anonymised Records (SARs) tell us who is moving, whilst the Small Area and Local Base Statistics (SAS/LBS) tell us where migrants move to. We simulate small-area migrant populations by fitting a selection of migrant individual records extracted from the SARs into known small-area migrant counts provided by the SAS/LBS. The search for the best fit is performed in an iterative fashion, using a combinatorial algorithm adapted from the hill-climbing technique. Three computer programs are designed and tested in an empirical study based in the West Midlands, more particularly in the districts of Birmingham and Solihull.
The migrant microdatabase thus created represents a considerable gain over standard census outputs, as it successfully integrates the highest levels of spatial and attribute disaggregation currently available in different census datasets. The potential of analysis of this new database resource is shown to be considerable. The methodology developed in this thesis could be applied to the integration of other aggregate and disaggregate datasets and to topics other than migration.
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Published date: 1999
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Local EPrints ID: 463996
URI: http://eprints.soton.ac.uk/id/eprint/463996
PURE UUID: 568acefc-5573-4059-9a6a-13ee85e88595
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Date deposited: 04 Jul 2022 21:00
Last modified: 04 Jul 2022 21:00
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Author:
Anne-Christine Wanders
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