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Modelling socioeconomic trajectories: an optimal matching approach

Modelling socioeconomic trajectories: an optimal matching approach
Modelling socioeconomic trajectories: an optimal matching approach
Purpose: the aim of this paper is to describe the use of sequence analysis to model trajectories of life-course economic activity status, within a broader research agenda aimed at improving understanding of the relationship between socioeconomic position and health.
Design/methodology/approach: the analysis used data on 288 participants of the Boyd Orr Stratified Sub-Sample, comprising a combination of prospective and retrospective information on economic activity status, as well as health in early old age. Economic activity was coded as a time-based sequence of states for each participant based on six-month periods throughout their lives. Economic activity was classified as: pre-labour market; full-time employment; part-time employment; housewife; made redundant; stopped work due to illness; retired; other unemployed; or not applicable. Optimal matching analysis was carried out to produce a matrix of distances between each sequence, which was then used as the basis for cluster analysis.
Findings: the optimal matching analysis resulted in the classification of individuals into five economic activity status trajectories: full-time workers (transitional exit), part-time housewives, career breakers, full-time workers (late entry, early exit), and full-time housewives.
Originality/value: the paper presents the case for using sequence analysis as a methodological tool to facilitate a more interdisciplinary approach to the measurement of the life-course socioeconomic position, in particular attempting to integrate the empirical emphasis of epidemiological research with the more theoretical contributions of sociology. This may in turn help generate a framework within which to examine the relationships between life-course socioeconomic position and outcomes such as health in later life
economic models, health and safety, lifeplanning, socioeconomic regions
0144-333X
217-230
Stone, Juliet
e90cfda9-64e9-4619-8a16-911312a0a965
Netuveli, Gopalakrishnan
a108fa80-aff3-42cd-aab2-48c89755a43a
Blane, David
56c854f0-809d-4cd7-9ca9-63d932f06ece
Stone, Juliet
e90cfda9-64e9-4619-8a16-911312a0a965
Netuveli, Gopalakrishnan
a108fa80-aff3-42cd-aab2-48c89755a43a
Blane, David
56c854f0-809d-4cd7-9ca9-63d932f06ece

Stone, Juliet, Netuveli, Gopalakrishnan and Blane, David (2008) Modelling socioeconomic trajectories: an optimal matching approach. International Journal of Sociology and Social Policy, 28 (5/6), 217-230. (doi:10.1108/01443330810881268).

Record type: Article

Abstract

Purpose: the aim of this paper is to describe the use of sequence analysis to model trajectories of life-course economic activity status, within a broader research agenda aimed at improving understanding of the relationship between socioeconomic position and health.
Design/methodology/approach: the analysis used data on 288 participants of the Boyd Orr Stratified Sub-Sample, comprising a combination of prospective and retrospective information on economic activity status, as well as health in early old age. Economic activity was coded as a time-based sequence of states for each participant based on six-month periods throughout their lives. Economic activity was classified as: pre-labour market; full-time employment; part-time employment; housewife; made redundant; stopped work due to illness; retired; other unemployed; or not applicable. Optimal matching analysis was carried out to produce a matrix of distances between each sequence, which was then used as the basis for cluster analysis.
Findings: the optimal matching analysis resulted in the classification of individuals into five economic activity status trajectories: full-time workers (transitional exit), part-time housewives, career breakers, full-time workers (late entry, early exit), and full-time housewives.
Originality/value: the paper presents the case for using sequence analysis as a methodological tool to facilitate a more interdisciplinary approach to the measurement of the life-course socioeconomic position, in particular attempting to integrate the empirical emphasis of epidemiological research with the more theoretical contributions of sociology. This may in turn help generate a framework within which to examine the relationships between life-course socioeconomic position and outcomes such as health in later life

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More information

Published date: 2008
Keywords: economic models, health and safety, lifeplanning, socioeconomic regions

Identifiers

Local EPrints ID: 71181
URI: http://eprints.soton.ac.uk/id/eprint/71181
ISSN: 0144-333X
PURE UUID: 4d884a57-2666-4f1c-9fed-7b7a0686a321

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Date deposited: 27 Jan 2010
Last modified: 13 Mar 2024 20:22

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Contributors

Author: Juliet Stone
Author: Gopalakrishnan Netuveli
Author: David Blane

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