Class Careers as Sequences: An Optimal Matching Analysis of Work-Life Histories

Halpin, Brendan; Chan, Tak Wing

doi:10.1093/oxfordjournals.esr.a018230

Cited by 125 publications

(90 citation statements)

References 13 publications

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“…In contrast, sequence analysis considers whole career sequences (as careers can be represented as a serial succession of different statuses over time) and therefore makes it possible to treat this data holistically. The handling of whole sequences is exactly what existing analyses of career mobility leave out (see Chan 1995;Brückner/Rohwer, 1996;Erzberger/Prein, 1997;Halpin, 1996;Halpin/Chan, 1998;Rohwer/Trappe, 1997 for counter-examples). This approach is able to provide viable answers concerning typical patterns in unique sequences; it allows one to empirically identify typologies of sequences.…”

Section: Methodology and Datamentioning

confidence: 99%

Early Career Patterns: A Comparison of Great Britain and West Germany

Scherer¹

2001

European Sociological Review

178

126

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The transition from initial education to work has received a great amount of attention, but hardly any research treats this process holistically. This paper focuses on the serial succession of statuses instead of on single events in the early years after leaving full-time education. As methodological tool Sequence Analysis will be applied. Optimal matching procedures allow for the direct comparison of entire career sequences taking into account the ordering of the events. The objective of applying this rather new tool is to empirically identify distinct patterns of transition into the labour market. The analysis covers the whole range of employment statuses including periods of unemployment and inactivity that individuals experience within the first five years following completion of education. A cross-national comparison between Great Britain and Germany aims at investigating to what extent the observed patterns of transition processes are shaped by their institutional embeddedness.

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Section: Methodology and Datamentioning

confidence: 99%

Early Career Patterns: A Comparison of Great Britain and West Germany

Scherer¹

2001

European Sociological Review

178

126

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“…They have since been applied in the social sciences, where they have been used to analyse life trajectories, career paths, and school to work transitions (cf. Abbott and Forrest 1986;Halpin and Chan 1998;Abbott and Tsay 2000;McVicar and Anyadike-Danes 2002), and, in a small number of studies, to analyse time diaries (Lesnard 2004;2008;2010;Vrotsou, Ynnerman, and Cooper 2014).…”

Section: Optimal Matchingmentioning

confidence: 99%

Sequencing the real time of the elderly: Evidence from South Africa

Grapsa¹,

Posel²

2016

DemRes

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BACKGROUNDUnderstanding how the elderly in developing countries spend their time has received little attention. Moreover, the potential of time use data to discern variation in activity patterns has not been fully realized by methods which use a mean added time approach. OBJECTIVESTo uncover patterns of time use among the elderly (60 years and older) in South Africa by applying an innovative methodology that incorporates the timing, duration, and frequency of activities in the analysis. METHODSWe use sequence analysis, which treats the daily series of activities of each individual as a sequence, and cluster analysis, to group these sequences into common clusters of time use behaviour. We then estimate multinomial logit regressions to identify the characteristics of the elderly which predict cluster membership. RESULTSWe find that the time use behaviour of the elderly in South Africa can be divided into five distinct clusters, according to the relative importance in their day of personal care, household maintenance, work, mass media, and social or cultural activities. In comparison to men, women are overrepresented in the cluster where household work dominates, while they are underrepresented in the cluster of the elderly who engage in production work. A range of other individual and household characteristics are also important in predicting cluster membership.

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“…Investigating trajectories has become increasingly common in the social sciences and in particular in life-course analysis looking at careers and social status Tsay 2000, Halpin andCban 1998;. A second generation of sequence analysis is being developed to answer the first criticisms and go beyond some initial limits (Aisenberg and Fasang 2010;Scherer 2001).…”

Section: Describing Trajectories: Some Indicatorsmentioning

confidence: 99%