CLASS CAREERS AS SEQUENCES - AN OPTIMAL MATCHING ANALYSIS OF WORK-LIFE HISTORIES

We apply optimal matching techniques to class careers from age 15 to a ge 35 for two moderately large samples, as a means of exploring the ut ility of this sequence-oriented approach for the analysis of work-life social mobility. We first apply multi-dimensional scaling techniques to the inter-sequence distances generated by the optimal matching algo rithm in order to test whether the technique locates sequences in a co herent and interpretable space. We find the space to be highly pattern ed and reasonably interpretable. Next we run the two moderately large samples (each approximately 1500 sequences) through the analysis and e xamine the nature of the set of clusters that emerges. We find the clu sters to be distinct and an intuitively attractive grouping of the seq uences. Finally, we consider how the clusters are distributed across c ohorts: the distributions change markedly, though this is largely due to changes in the distribution of classes over time. We briefly discus s means of separating 'pure sequence' change from change in the gross 'class time-budget' of cohorts, and consider means of applying statist ical models to the problem. We conclude by endorsing Optimal Matching Analysis, especially as a means of exploratory analysis of longitudina l data.