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Causal Effects of the Timing of Life-course Events: Age at Retirement and Subsequent Health
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. (Stat4Reg)
Umeå University, Faculty of Social Sciences, Department of Geography and Economic History. Umeå University, Faculty of Social Sciences, Centre for Demographic and Ageing Research (CEDAR).
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
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2017 (English)In: Sociological Methods & Research, ISSN 0049-1241, E-ISSN 1552-8294Article in journal (Refereed) Epub ahead of print
Abstract [en]

n this article, we combine the extensive literature on the analysis of life-course trajectories as sequences with the literature on causal inference and propose a new matching approach to investigate the causal effect of the timing of life-course events on subsequent outcomes. Our matching approach takes into account pre-event confounders that are both time-independent and time-dependent as well as life-course trajectories. After matching, treated and control individuals can be compared using standard statistical tests or regression models. We apply our approach to the study of the consequences of the age at retirement on subsequent health outcomes, using a unique data set from Swedish administrative registers. Once selectivity in the timing of retirement is taken into account, effects on hospitalization are small, while early retirement has negative effects on survival. Our approach also allows for heterogeneous treatment effects. We show that the effects of early retirement differ according to preretirement income, with higher income individuals tending to benefit from early retirement, while the opposite is true for individuals with lower income.

Place, publisher, year, edition, pages
Sage Publications, 2017.
Keywords [en]
life-course analysis, matching, propensity score, retirement, register data, sequence analysis
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:umu:diva-142215DOI: 10.1177/0049124117729697Local ID: 881251OAI: oai:DiVA.org:umu-142215DiVA, id: diva2:1160313
Available from: 2017-11-26 Created: 2017-11-26 Last updated: 2019-04-04

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de Luna, XavierLundholm, EmmaSvensson, Ingrid

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de Luna, XavierLundholm, EmmaSvensson, Ingrid
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StatisticsDepartment of Geography and Economic HistoryCentre for Demographic and Ageing Research (CEDAR)
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