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. [ABSTRACT FROM AUTHOR]