Despite extensive research on educational inequalities in healthy life expectancy (HLE), most studies focus on average differences, leaving open how healthy longevity is distributed within educational groups. This study examines sex-specific educational differences in healthy longevity distributions at age 60 in Europe, using multiple health measures. We combined data from the Survey of Health, Ageing and Retirement in Europe (SHARE) with Eurostat life expectancy data (2016-2017). A Markov chain model combined with the maximum entropy method was used to estimate distributions of age at the end of healthy lifespan. Educational differences were formally compared using the healthy lifespan outsurvival statistic and the Hellinger distance. High education was often associated with more negatively skewed healthy longevity distributions. Men with low education had higher healthy lifespan variation than men with high education. Across all health measures for women, and most health measures for men, the probability that a person with low education had a longer healthy lifespan than a person of the same sex with high education was below 50
Despite economic changes and the expansion of family policies, fertility rates in East Asian countries, including Japan, remain persistently low. One possible explanation is that widespread pessimism about future economic and demographic conditions dampens individuals’ intentions to marry and have children. Against this backdrop, this study applies a narrative framework to examine the effects of future-oriented narratives—specifically those concerning the economy, population, and policy—on the marriage and fertility intentions of unmarried individuals in Japan. In this study, a factorial survey experiment is conducted among unmarried individuals aged 23–32 years in Japan (N = 2,270), a context in which low levels of cohabitation and nonmarital childbearing, along with declining marriage rates, substantially contribute to declining fertility rates. The experiment constructs positive, status quo, and negative scenarios across three dimensions—the economy, population, and policy—which are randomly combined into vignettes. The respondents’ marriage and fertility intentions are measured in response to these scenarios. The results show that economic scenarios clearly affect both marriage and fertility intentions, whereas negative population scenarios reduce both outcomes. Policy scenarios also influence both intentions. These findings suggest that the spread of pessimistic narratives about the future of the economy and population, coupled with a lack of significant policy expansion, may contribute to discouraging people from forming families. This study demonstrates that the narrative framework applies to both fertility and marriage intentions and extends the relevance of this framework to East Asian contexts.
Concerns about the negative impact of population decline, and especially the systemic depopulation of remote and marginalised areas, have become a central issue in contemporary policy debates. The National Strategy for Inner Areas (SNAI), established in 2014, represents the main Italian policy framework explicitly aimed at supporting territories affected by long-term demographic fragility. This study applies the Systemic Depopulation Areas Index (SyDAs) to municipalities in three Italian regions—Abruzzo, Basilicata, and Emilia-Romagna—over the period 1994–2023 to identify and characterise systemic depopulation processes. Municipal trajectories are examined both in terms of exit from systemic depopulation (SyDAs Exit) and reduction in its intensity (SyDAs Reduction), measured through differences in population trend slopes before and after the introduction of SNAI. These outcomes are then examined in relation to the degree of economic implementation of SNAI projects at the municipal level. The results indicate a general expansion or stabilization of systemic depopulation across the analysed regions, while only a small minority of municipalities display either an exit from the SyDAs condition or a measurable reduction in its intensity. Moreover, no statistically significant association emerges between higher levels of SNAI economic implementation and either SyDAs Exit or SyDAs Reduction. Taken together, these findings suggest that observed demographic trajectories do not display systematic differentiation across levels of policy exposure. This evidence highlights the analytical importance of moving beyond financial implementation alone and points to the need for refined territorial targeting, outcome-oriented monitoring, and sustained, context-sensitive support for local governance in place-based development strategies.
In the last decade, the substantial expansion of online education in Italy has been accompanied by a growing public and institutional debate over its academic quality and effectiveness. This study contributes to this debate by investigating the differences in academic outcomes between students enrolled in online institutions and those in traditional universities, with a particular focus on first-year dropout. Using administrative data from the MOBYSU.IT database on the population of students enrolled in an Italian university between 2010 and 2019, we apply Propensity Score Matching to estimate the causal impact of attending an online institution. Our analysis shows that students in online universities are, on average, less likely to drop out after the first year. This retention effect is especially evident among students who enrol later in life, those from technical and vocational schools, and those from Southern Italy. Conversely, students entering university directly after high school are more likely to transfer to traditional institutions. These findings suggest that online universities can play a complementary role in reducing dropout and promoting access to higher education, particularly for non-traditional and underserved student populations.
Abstract The conventional approach to modeling age at death through parametric models often employs a three-component mixture as a standard. However, recognizing the need to more accurately reflect the diverse trends in old age mortality, this study introduces a five-component Bayesian mortality model. This model is designed to address data exhibiting cohort effects and transitions in the old age mortality component, which moves from a skew-normal distribution to a mix of Gaussian and skew-normal distributions as the period progresses. The proposed model comprises a point probability for infant mortality, a uniform distribution for background mortality, a Gaussian distribution for premature mortality, and two components for old age mortality (Gaussian and skew-normal). Applied to data from 10 Italian regions spanning 1974–2022, including cohort effects for cohorts born between 1913 and 1947, the model demonstrates a stable interpretation of mortality components over time. In contrast to simpler models, it reveals a significant shift in old age mortality from a skew-normal to a combined Gaussian and skew-normal distribution around the millennium’s turn. This study not only sheds light on the evolution of old age mortality in Italy, highlighting a non-uniform shift and compression of mortality across the population, but also lays the groundwork for future forecasting models by maintaining a consistent parameter interpretation throughout the period.
