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How to Measure Retirement Age? A Comparison of Survey and Register Data
Stockholm University, Faculty of Social Sciences, Aging Research Center (ARC), (together with KI).ORCID iD: 0000-0003-1478-5550
Stockholm University, Faculty of Social Sciences, Aging Research Center (ARC), (together with KI).
Stockholm University, Faculty of Social Sciences, Aging Research Center (ARC), (together with KI).
Number of Authors: 42019 (English)In: Journal of Population Ageing, ISSN 1874-7884, E-ISSN 1874-7876Article in journal (Refereed) Epub ahead of print
Abstract [en]

Due to an increasing heterogeneity in retirement transitions, the measurement of retirement age constitutes a major challenge for researchers and policymakers. In order to better understand the concept of retirement age, we compare a series of measures for retirement age assessed on the basis of survey and register data. We use data from Sweden, where flexible retirement schemes are implemented and register data are available. We link survey data from the Swedish Level of Living Survey with register data from the Swedish Longitudinal Integration Database for Health Insurance and Labour Market Studies. We create four measures of retirement age based on these datasets, applying approaches that have been used in previous literature. We analyse the means and distributions of these measures and evaluate the correlations between them. Finally, we regress common predictors of retirement age such as gender or education on the four measures of retirement age to examine potential differences in size, direction and statistical significance of the associations. We find that the survey measure of retirement age resembles the following two ways of defining retirement age in the register data: first, the age at which people receive more than half their income from old-age or disability pension and, second, the age at which they were not gainfully employed for at least 2 years. This insight gives us a better understanding of when in the retirement transition process, individuals identify with retirement. Moreover, it provides decision support for researchers working with register data to determine which measure to use.

Place, publisher, year, edition, pages
2019.
Keywords [en]
Retirement transition, Retirement age, Old-age pensions, Measurement, Survey data, Register data
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
URN: urn:nbn:se:su:diva-175760DOI: 10.1007/s12062-019-09254-6ISI: 000492323700001OAI: oai:DiVA.org:su-175760DiVA, id: diva2:1372704
Available from: 2019-11-25 Created: 2019-11-25 Last updated: 2020-01-16

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Eyjolfsdóttir, Harpa S.
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Public Health, Global Health, Social Medicine and Epidemiology

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Citation style
  • apa
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  • vancouver
  • Other style
More styles
Language
  • de-DE
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  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
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  • asciidoc
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