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The optimal matching (OM) algorithm is widely used for sequence analysis in sociology. It has a natural interpretation for discrete-time sequences but is also widely used for life-history data, which are continuous in time. Life-history data are arguably better dealt with in terms of episodes rather than as strings of time-unit observations, and in this article, the author examines whether the OM algorithm is unsuitable for such sequences. A modified version of the algorithm is proposed, weighting OM’s elementary operations inversely with episode length. In the general case, the modified algorithm produces pairwise distances much lower than the standard algorithm, the more the sequences are composed of long spells in the same state. However, where all the sequences in a data set consist of few long spells, and there is low variability in the number of spells, the modified algorithm generates an overall pattern of distances that is not very different from standard OM.

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We investigate claims originating in the work of Daniel Bell that in post-industrial societies educational qualifications obtained prior to labour market entry increasingly determine individuals' class positions-while opportunities for achieving upward class mobility over the course of working life correspondingly diminish. We apply optimal matching techniques of sequence analysis as a basis for constructing typologies of class histories for men and women in three British birth cohorts whose lives span the period from the mid-twentieth to the early twenty-first century. We find a steady increase across the cohorts in class histories characterised by entry into, and stability within, managerial and professional positions and associated with relatively high levels of qualification. However, there is no decline in class histories characterised by upward mobility; and, while there are clear associations between education and most of the types of class history that we distinguish, the effects of education are systematically and persistently reinforced, or modified, by the independent effects of early life cognitive ability and of class origins. In Britain at least, there is little indication of movement towards an education-based meritocracy, and educational level at labour market entry is today no more class destiny than it was half-a-century ago.

This paper examines the pattern of educational homogamy in Ireland and Britain. Using contemporary data on recent marriages from the early 1970s through to the mid-1990s, we show that these two countries share a broadly similar pattern of educational homogamy, which is quasi-symmetric in character, with no tendency for women to marry up over and above that which can be attributed to the gender difference in educational attainment. In the 1970s, the strength of homogamy was much weaker in Ireland than in Britain. But we discern a clear inter-country difference in how the net strength of homogamy has changed over time. While it has declined in Britain since the 1970s, in Ireland the strength of homogamy has first increased and then levelled off. Our findings are inconsistent with the inverted U-shaped relationship between economic development and homogamy reported by Smits, Ultee and Lammers (1998) - an argument premised on secular change in the criteria of spouse selection. Instead, our results are better understood in terms of Mare's (1991) life course argument that homogamy is inversely related to the time-gap between school departure and first marriage.

The SADI package provides tools for sequence analysis, which focuses on the similarity and dissimilarity between categorical time series such as life-course trajectories. SADI‘s main components are tools to calculate intersequence distances using several different algorithms, including the optimal matching algorithm, but it also includes utilities to graph, summarize, and manage sequence data. It provides similar functionality to the R package TraMineR and the Stata package SQ but is substantially faster than the latter.

The British Household Panel Study collects extensive labour market history information from its respondents, both during the panel period and retrospectively from labour market entry. That this information is of necessity stored in multiple locations, and of varying levels of detail, has made use somewhat inconvenient. This paper describes an exercise to bring the labour market information together in a more convenient format. It also considers some of the problems of retrospective and panel longitudinal data, and discusses issues of recall error and measurement error.The data files described will be made available through the Data Archive. SummaryThe British Household Panel Study collects extensive information on respondents' labour market status, (i) at the time of interview at each wave of the panel, (ii) through the period between 1 September a year before and the interview date, and (iii) retrospectively from first leaving full-time education. Because the retrospective information was collected in two tranches (one focusing on employment status, the other on occupational information) there are four different types of labour-market history information, located (at Wave 5) in twelve different files in the BHPS database. This complexity is a necessary aspect of longitudinal information, but it has inhibited use of the work-life history data. In order to facilitate such use, a set of 'reconciled' files has been created, constituting single continuous records each containing all the information of a particular type in a single location. This paper describes the creation of the files, examines their output and discusses some aspects of measurement error and recall bias relevant to the exercise.The first part of the exercise is to take the 'current status' information and combine it with the inter-wave history, for each wave, and then to combine the five waves thus creating a continuous record from September 1990 to the September 1995 (and later). The second stage is to take the life-time employment status history collected at Wave 2, and the life-time occupational history collected at Wave 3, and to combine each of them with analogous information drawn from the combined panel file, thus creating employment and occupational histories that stretch from labour-market entry to the latest wave. The third stage is to combine these two extended life-time histories into a single record which contains both employment-status information (with good information about non-employed spells) and occupational information (that is, details about the job held during each employed spell).The paper describes the methods used, in terms of an initial specification and its detailed implementation, and goes on to consider the output produced. By including the retrospective data we have information stretching back many decades, though from the point of view of breatdh of detail and quality of recall the panelderived data (covering 1990-95) are much better. When we compare data from different sources, we find systematic difference...