Educational differences in macro-level determinants of early exit from paid work: a multilevel analysis of 14 European countries

教育程度差异对过早退出有偿工作的宏观层面决定因素的影响:对14个欧洲国家的多层次分析

阅读:1

Abstract

The aim of this study was to identify macro-level determinants of early work exit and investigate whether the effects of these determinants differ across educational groups. We used data from the Survey on Health, Ageing and Retirement in Europe (SHARE) (2011-2013) and the English Longitudinal Study of Ageing (ELSA) (2010/2011-2012/2013) as well as macro-level data and included 10,584 participants in 14 European countries. We used logistic multilevel analyses to examine educational differences in macro-level determinants of early work exit. Macro-level determinants were: minimum unemployment replacement rates, expenditure on active labour market policies (aimed to help the unemployed find work) and passive labour market policies (unemployment and early retirement benefits), employment protection legislation (costs involved in dismissing individuals), unemployment rates, statutory pension age and implicit tax on continued work. We found low-educated workers to be more at risk of early work exit than higher educated workers. In low-educated men, higher unemployment replacement rates, higher expenditure on passive labour market policies, stricter employment protection legislation and a higher implicit tax on continued work were associated with a higher risk of early work exit, whereas no macro-level factors were associated with early work exit in highly educated men. In women, a higher expenditure on passive labour market policies and a higher implicit tax on continued work were determinants of early work exit, regardless of educational level. To conclude, low-educated men seem to be especially responsive to the effects of pull factors that make early retirement financially more attractive.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。