Time use during the life course in the USA, Norway, and the Netherlands: a HAPC-analysis
This paper analyses life course variations by means of Hierarchical Age-Period-Cohort-modelling (HAPC) of time use data for thee welfare states: the USA, Norway, and the Netherlands. By means of analyzing time use data insight is gained in the (relative) importance of various life spheres as paid work, household work, volunteer aid, care, anc education in and over people's life. The relevance of an integrated insight in the relation between paid work and these other life spheres seems to have grown with the introduction and (policy) application of the idea of "transitional labour markets". This paper aims to find out the relevance of age, period and cohort as underlying factors in population ageing and change. The author compares the fixed versus the random-effects model specifications for APC-analysis. The random-effects HAPC-model appears the most appropriate specification. The HAPC analyses find evidence in support of quadratic age effects on time use. Furthermore, the HAPC analyses find proof in support of the contentions in the literature that both cohort and period effects should be distinguished in life course analyses. Finally, the analyses show clear differences in time use patterns during the life course between the welfare states. These may indicate a non-negligible sensitivity for welfare policies with respect to reconciling life domains during the life course.
|Date of creation:||2008|
|Date of revision:|
|Publication status:||Published in Department of Economics Research Memorandum 02 (2008): pp. 1-30|
|Contact details of provider:|| Postal: Ludwigstraße 33, D-80539 Munich, Germany|
Web page: https://mpra.ub.uni-muenchen.de
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- S. Illeris & G. Akehurst, 2001. "Introduction," The Service Industries Journal, Taylor & Francis Journals, vol. 21(1), pages 1-4, January.
- Yang Yang & Kenneth C. Land, 2008. "Ageâ€“Periodâ€“Cohort Analysis of Repeated Cross-Section Surveys: Fixed or Random Effects?," Sociological Methods & Research, SAGE Publishing, vol. 36(3), pages 297-326, February.
- Omar Paccagnella, 2006. "Centering or Not Centering in Multilevel Models? The Role of the Group Mean and the Assessment of Group Effects," Evaluation Review, SAGE Publishing, vol. 30(1), pages 66-85, February.
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