Measuring Life Course Complexity with Dynamic Sequence Analysis

David Pelletier (), Simona Bignami- Van Assche and Anaïs Simard-Gendron
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David Pelletier: Institut national de la recherche scientifique (INRS)
Simona Bignami- Van Assche: Université de Montréal
Anaïs Simard-Gendron: Université de Montréal

Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 2020, vol. 152, issue 3, No 12, 1127-1151

Abstract: Abstract The transformation of life courses in industrialized countries since the mid-twentieth century can be analyzed through the lens of life course complexity, a function of the number of transitions or states experienced by individuals over a given time span. Life course complexity is often measured with composite indices in a static sequence analysis framework (i.e. over a single age interval), but this method has seldom been evaluated. This paper fills this gap. We review nine indicators of life course complexity and explore the advantages of a dynamic approach to sequence analysis (i.e. examining many nested or consecutive age intervals). An application to data on the partnership histories of American and French women is used to show the properties of each measure. We conclude that simple indicators, used alone or in combination, provide a more easily interpretable description of changes and differentials in life course complexity than commonly used composite indices. In addition, we show that, for all indicators, a dynamic approach allows a more nuanced illustration of age-related transformations of life course complexity than the static approach does.

Keywords: Life course; Sequence analysis; Complexity indicators; Turbulence; Cross-cohort change (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11205-020-02464-y

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