Work orders: Analysing employment histories using sequence data

Abstract

The analysis of employment histories has been facilitated recently by advances in survey methodology, statistical processes and computing power. While much work has focused on transitions between states and time spent in one state, the potential of analysing a series of states (i.e. careers) has largely been ignored. A concentration on movement between two states, whilst allowing relevant contextual covariates to be controlled for, often ignores valuable data both prior to and after the episode in question. Analysis of extended sequences of employment states is better able to describe employment trajectories. Furthermore, comparison of sequences permits either allocation to theoretical categories, or the identification of latent groupings using cluster analysis. The resulting typology of careers can then be used in inferentially based analyses. This paper explores sequence analysis using Optimal Matching Analysis (OMA). OMA is explained in relation to one broad substantive issue: the relationship between employment trajectories and gender.