Ageing women at work in Europe and the search for work-life balance: combining econometric models and artificial neural networks

The equilibrium between personal and professional life (i.e., work-life balance) has become increasingly relevant in Europe, particularly due to the ageing population. The European Commission and European countries are increasingly investing in the well-being of both workers and retired citizens. Consequently, scientific literature concentrates on analysing factors influencing this equilibrium with the goal of proposing ad-hoc policies. This study delves into the nuanced realm of work-life balance (WLB) for ageing working women across European countries, leveraging data from the extensive European Working Conditions Survey (EWCS). The research employs a two-step approach, integrating econometric models and artificial neural networks (ANNs) to dissect the multifaceted determinants of WLB. These determinants encompass individual factors, job-related elements, non-standard work scheduling, workplace social environment, firm characteristics, and control factors. The study puts emphasis on the gender dimension, facilitating a comparative analysis of results among European nations. Preceding the primary analysis, the “percentualization approach” is used to compute an average synthetic index of WLB satisfaction intensity. The investigation then delves into exploring the intricate relationship between gender roles and WLB satisfaction, employing a range of econometric models tailored to factors such as sample size and the distribution of the dependent variable. In the second phase, the study aspires to craft a tailored policy portfolio aimed at enhancing WLB satisfaction for female workers. Anticipated results are poised to not only enrich our understanding of the intricate factors influencing WLB, but also to furnish policymakers with targeted recommendations for effective, personalized policies while minimizing public expenditure.