Work–life balance in Europe: institutional contexts and individual factors

In: The international journal of sociology and social policy, Band 40, Heft 3/4, S. 366-381

Abstract

PurposeThe purpose of this paper is to explore how individual and macro-level factors shape the work–life balance of young men and women across European countries.Design/methodology/approachThe paper combines macro-level data from the official statistics with individual-level data from the Work, Family and Wellbeing (2010/2011) module of the European Social Survey. The study uses multilevel modelling to explore the factors which shape the work–life balance of men and women aged 15–34 across 24 European countries.FindingsThe findings show both differences and similarities between young men and women in how education shapes work–life balance. Higher education increases the likelihood of considering work–life balance as important in work selection for men, while lower education decreases the odds of considering this balance for women. More education is associated with lower acceptance of the traditional norm, for both men and women, and less time spent on housework. Higher share of family benefits decreases the importance of work–life balance, more so for men than for women. Work–life balance is more important for men living in conservative, Mediterranean and post-socialist welfare regimes compared to those from social-democratic regimes.Social implicationsThe policy implications are to more closely consider education in the transformation of gender-sensitive norms during earlier stages of child socialization and to design more holistic policy measures which address the multitude of barriers individuals from poor families and ethnic/migrant background face.Originality/valueThe study contributes to existing literature by applying the capability approach to the empirical investigation of work–life balance. The analytical model contains three dimensions – norms about paid/unpaid work, considering work–life balance in the choice of employment and time spent on unpaid work. Through this approach, we are able to uncover the agency inequality of young people taking into account individual level characteristics, including gender, education, ethnicity and macro-level factors.