Weather shocks affect rural food security not only through their occurrence, but through the severity of the losses they impose on household income and assets. This paper examines whether household head migration moderates the association between drought and flood related loss severity and household calorie intake in rural eastern India. The study used household panel data from the ICRISAT Village Dynamics in South Asia project for 2010–2014. Food security is measured as daily adult-equivalent calorie intake, while weather-shock severity is measured by household-reported monetary losses from drought and flood events. We estimate household fixed-effects models with year effects and time-varying controls. The results show a conditional pattern. In years with no weather-shock loss reported, migrant-headed households have lower calorie intake than non-migrant headed households. However, as reported weather-shock losses rise, the migration-loss interaction is positive: migrant-headed households exhibit a more favourable calorie-intake gradient than non-migrant headed households. These estimates suggest that household head migration is associated with relative consumption smoothing under severe climatic losses, while also being linked to lower calorie intake in low-loss periods. The findings point to the importance of distinguishing shock incidence from loss severity, and household head migration from migration by other members, when studying climate stress, mobility, and food security.
India has entered the era of below-replacement fertility. In the National Family Health Survey (2019–21), the national total fertility rate (TFR) was 2.0 children per woman and 23 states were below the 2.1 replacement level. As some state governments consider policies to raise fertility, the question is how much demographic scope for recovery remains. Existing studies have focused on fertility intentions, but recovery also depends on who remains exposed to childbearing. This paper develops a framework distinguishing three concepts: the limitation stock, women who have permanently exited childbearing through sterilisation, hysterectomy or infecundity; the prospect stock, women still exposed to childbearing; and the recovery prospect, those who also wish to have another child. Across the 23 below-replacement states, the limitation stock reaches 47.4
This paper examines recent demographic dynamics in Spain, France, and Italy by analysing regional patterns of population turnover and the relative role of natural and migratory components. Building on the fast-slow demography framework, the study employs the Population Turnover Rate (PTR), the Migration Share of Turnover (MST), and the Birth Share of Turnover (BST) to assess how demographic change unfolded across NUTS-2 regions between 2014 and 2023. Although the three countries share geographical proximity and face comparable structural challenges, their demographic trajectories appear to diverge in various ways, partly reflecting differences in fertility levels, ageing patterns, and migration regimes. Special attention is devoted to Mediterranean coastal regions, where migration-driven demographic change has accelerated in recent years. The results suggest the possible formation of a demographic corridor along the Mediterranean rim, especially between the Spanish and French coasts, where relatively high turnover and a growing role of mobility-related processes seem to be taking shape. Yet this transnational coastal dynamism is not uniform. National contexts continue to structure regional outcomes, shaping the balance between mobility-driven (fast) and natural (slow) demographic processes. In Spain and France, coastal regions exhibit clear demographic distinctiveness linked to strong residential attractiveness, especially among older adults. In Italy, by contrast, geographical differences are less pronounced, as most regions benefit from similar coastal or amenity environments. The paper concludes by discussing how ageing, environmental pressures, and evolving residential mobility may shape the future demographic trajectories of these coastal areas.
While a number of studies have been conducted on intimate partner violence (IPV) in interracial marriages in multiracial societies, studies on IPV in cross-cultural but monoracial marriages remain scarce. Also, an integrated framework that explores how religious, language, and cultural differences influence the experience of IPV in cross-cultural marriages is still lacking. This study examines the association between language, religious, and cultural differences and the experience of IPV in a multi-ethnic but monoracial setting: Lagos State, Nigeria. A mixed-methods approach, involving a cross-sectional survey and in-depth interviews, was adopted for the study. A total of 1,357 male and female ever-married adults were selected for the survey, while 15 male and female ever-married adults (9 females and 6 males) from different ethnic backgrounds were recruited for the in-depth interviews. Logistic regression and thematic analysis were used to analyse the quantitative and qualitative data, respectively. The study found a statistically significant association between language, religious, and cultural differences between partners and the probability of experiencing IPV. From the cultural ecological perspective, the conclusion indicates and reinforces the multi-dimensional nature of IPV. Based on the theory, the experience of IPV is influenced by micro-level relational dynamics, meso-level social interactions, and macro-level cultural and institutional barriers. This suggests that the experience of IPV goes beyond a personal or relational matter; it also reflects broader socio-cultural and systemic challenges.
Can relaxing fertility restrictions reshape fertility ideals? We examine this question in the context of China’s Three-Child Policy, announced in May 2021. Using repeated cross-sectional data from the 2017, 2018, 2021, and 2023 waves of the Chinese General Social Survey, we estimate intensity-based difference-in-differences and event-study models. Treatment intensity is measured by the pre-policy regional share of respondents aged 20–49 who already had exactly two children. We find little evidence of a broad increase in average ideal family size after the policy. However, regions with higher pre-policy two-child intensity showed larger post-policy increases in the probability that respondents reported an ideal family size of three or more children. Across specifications, a 10-percentage-point increase in pre-policy intensity is associated with an additional 0.82–1.37
This study investigates whether and how the division of domestic labor and gender role attitudes predict the fertility gap, the discrepancy between ideal and actual number of children, among married and cohabiting adults in Taiwan. Drawing on the 2022 wave of the Panel Study of Family Dynamics (n = 1,893), we estimate binary logistic regression models for the full sample and separately by sex. In the full-sample models, wife’s housework share is a significant negative predictor of fertility gap, a counterintuitive pattern interpreted as reflecting normative congruence in traditionally organized households. Gender-stratified analyses show different patterns by sex: among male respondents, the wife’s housework share is a significant negative predictor while gender role attitudes are not; among female respondents, the wife’s housework share is non-significant, while more traditional gender role attitudes are associated with a higher likelihood of a fertility gap. Because the groups are modeled separately, these are described as subgroup patterns rather than a formally tested sex difference. Financial difficulty is also a significant negative predictor for women but not men. These findings suggest that the fertility gap in Taiwan is associated with gendered patterns rooted in the incomplete transition toward more equal household gender arrangements.
Climate change is increasingly recognized as a driver of unequal health risks, yet empirical evidence examining how these risks are shaped by structural vulnerabilities and institutional responses among migrant populations remains limited. Addressing this gap, this study examines climate change and migrant health in Thailand, focusing on how institutional stakeholders understand the structural conditions and response capacities that shape health risks and access to care. Thailand represents a critical case due to its high climate exposure and large, diverse migrant workforce, including workers concentrated in climate-sensitive sectors such as construction, agriculture, fisheries, and domestic work. The study adopts a qualitative, systems-oriented design, combining an organisational readiness assessment adapted from the Capacity Assessment Tool for Climate Action Transparency with a semi-structured focus group discussion involving stakeholders from policy, implementation, civil society, and academic settings working with migrant populations. Anchored in the Intergovernmental Panel on Climate Change risk framework and the social determinants of health, the analysis conceptualizes climate-related migrant health risk as the interaction of hazard, exposure, vulnerability, and institutional response, and examines both direct health impacts and indirect pathways mediated through social, economic, legal, and institutional conditions. The findings suggest that climate-related health risks among migrants are intensified by precarious employment, hazardous housing, insecure documentation, language barriers, and weakly coordinated service systems. The organisational readiness assessment further indicates moderate-to-low institutional preparedness, particularly in surveillance, monitoring, and cross-sector coordination. A central finding is that institutional capacity remains limited and insufficiently aligned with the chronic, cumulative, and socially mediated nature of climate-related migrant health risks. The study contributes empirical and conceptual insight to climate–migration–health scholarship by demonstrating how structural inequalities and institutional responses jointly shape migrant health outcomes in climate-vulnerable settings.
Climate variability has emerged as a critical structural driver of livelihood disruption and labour mobility in vulnerable agrarian regions of India. This study examines how different forms of climate variability shape household migration decisions in two ecologically distinct districts of Odisha—Kendrapara (cyclone-prone coastal) and Nuapada (drought-prone western)—and investigates whether livelihood insecurity mediates this relationship while social protection moderate’s climate-induced mobility.Using primary household survey data from 600 households (300 per district) across 32 villages, combined with secondary climate data (2018–2023), the analysis employs binary and multinomial logistic regression, structural equation modeling for pathway analysis, and propensity score matching as a robustness check.Climate variability is associated with significantly higher migration likelihood. The findings are consistent with livelihood insecurity acting as a pathway between climate variability and migration, with income instability, crop loss, and indebtedness emerging as key links. Migration patterns differ by shock typology: drought is associated with seasonal/circular migration while cyclones are associated with temporary/post-disaster migration. Social protection is associated with reduced migration odds. Subgroup analyses indicate that marginal farmers, SC/ST households, and low-education groups show larger associations. Non-linear relationships suggest threshold effects where migration accelerates sharply under high climate stress.The findings imply that climate-induced migration is not inevitable under supportive policy conditions. Model-based simulations suggest that integrated interventions combining social protection expansion with livelihood diversification could potentially reduce migration below baseline levels. Well-targeted, spatially coordinated policies may help households adapt in place rather than migrate in distress.
In demographic literature, forecast uncertainty is often quantified with a statistical model. This model-based approach may potentially suffer from drawbacks, namely model misspecification, selection effect, and lack of finite-sample validity. We introduce a model-agnostic and distribution-free procedure, conformal prediction, for constructing prediction intervals for a functional time series. In the family of conformal prediction, split conformal prediction divides the data into training, validation, and test sets. Within the validation set, we can select optimal tuning parameters by calibrating the empirical coverage probabilities to match their nominal values. With the selected optimal tuning parameters, we then construct the prediction intervals using the same forecasting model for the holdout data in the testing set. Without sample splitting, sequential conformal prediction sequentially updates the predicted quantiles via an autoregressive process. Using Australian age- and sex-specific log mortality rates, we evaluate and compare the interval forecast accuracy, as measured by empirical coverage probability, coverage probability difference and mean interval score, between the two variants of conformal prediction.
This study examines the determinants of students’ decisions to overstay non-immigrant visas upon completing the Summer Work and Travel program in the United States. This study uses a logistic regression model to analyze survey data collected from Uzbek alumni of the Summer Work and Travel program, assessing six categories of factors influencing overstay decisions: demographic background, prior travel experience, social networks, previous Summer Work and Travel program experience, education, and financial background of students. The primary findings highlight the significance of demographic factors, past travel experience, and family financial situation as main predictors of visa overstay decisions.
Fertility transitions have transformed both the number of births women have and the timing of those births across the reproductive lifespan. While indicators such as the total fertility rate and mean age at childbearing summarize fertility levels and central timing, they provide limited insight into how widely fertility is distributed across ages. This paper introduces the childbearing span, a simple percentile-based indicator measuring the number of years between the ages at which 10
This study investigates how fertility, family structures, and institutional environments shape women’s labor force participation in Southern Europe (Greece, Italy, Spain, Portugal) and Türkiye. Using balanced panel data from 2015 to 2022 and fixed effects models with Driscoll–Kraay standard errors, the analysis identifies a negative relationship between fertility and female employment, though only at marginal levels of statistical significance. Robustness checks using Ridge regression and principal component analysis confirm this finding across alternative specifications. Significant country-level fixed effects reveal considerable heterogeneity, with Portugal and Spain exhibiting higher baseline participation rates and Türkiye recording notably lower values. While the empirical model does not directly measure institutional support, childcare availability, or cultural norms, the comparative literature suggests that cross-country differences in these dimensions likely contribute to the observed patterns. The findings point to the potential importance of integrated policy approaches, including affordable childcare and flexible work arrangements, in supporting women’s employment alongside fertility.
The resilience of migrant youth is under-theorised and poorly understood, yet it is crucial for successful adaptation and integration. This systematic review examines the literature on resilience and coping strategies among migrant youth. A systematic search of four academic databases (Emerald Insight, Google Scholar, ProQuest, and Scopus) identified 1,273 studies, of which 20 met the eligibility criteria for inclusion. The studies were thematically analysed, and their methodological quality was assessed using the Effective Public Health Practice Project (EPHPP) and the Critical Appraisal Skills Programme (CASP) tools. Findings indicate the importance of family, peers, community support, and personal agency in fostering resilience. Despite growing empirical evidence on the impacts of social networks on migrant youth’s resilience and well-being, there is a research gap regarding the role of family processes and parental mental health literacy in promoting resilience among migrant youth experiencing psychosocial externalising challenges. Our findings indicate a need to adopt an intersectional and ecological lens to fully understand migrant youth experiences, resilience and coping strategies. There is a need for more evidence on the effects of specific types of resilience on the adversity experienced by migrant youth. However, the scope and methodology of the included studies are limited, necessitating further research to elucidate how resilience and coping support the well-being of this population.
Migration is shaped by a complex interplay of social, economic, political, demographic, and environmental factors that vary across population groups. This study explores the motivations driving return migration among retired older adults to their place of origin in the Yogyakarta Special Region, Indonesia. Drawing on in-depth interviews with 27 retirees who had lived outside the province for 22 to 43 years, the findings show that return migration reflects multiple interrelated considerations. The foremost motivation is the desire to reside in closer proximity to family members, particularly parents and children, as well as friends, accompanied by a pursuit of more affordable living conditions and a preference for cleaner environments with accessible recreational amenities. Rather than signalling failure or dissatisfaction, return migration emerges as a planned, purposeful choice aimed at optimizing well-being in later life within the familiar social and ecological settings of one’s place of origin.
The study analyzes gender disparities in time spent on various daily activities for Indian adolescents across family backgrounds. The analysis shows that gender disparity in adolescent time use in India follows the traditional gender norms related to the segregation of work where the girls are overburdened with unpaid work. Although higher education of the family head and better economic status reduce this gap, the gap is not eliminated even in the most affluent families. Moreover, girls from the socially deprived castes are doubly disadvantaged as the disparity is greater for them than for others. We consider the presence of working women in the family to study the effect of socialization. Among low economic classes, the gender gap in paid work is lower for families with working women, indicating the demonstration effect. However, the gender gap in unpaid work is not lowered, and affluent families with working women show a greater gender gap in unpaid work than those without them.
This study aims to identify the most accurate pair model for predicting the life expectancy at birth (e0) at national and subnational levels, including men and women, by rural and urban areas, and which model provides the closest estimates of observed e0 in the Sample Registration System (SRS) and the National Family Health Survey (NFHS). Furthermore, the decomposition method is applied to e0 differences to identify mortality pattern differentials between SRS and NFHS in same reference period. The life table were constructed from the Chiang method using SRS statistical report 2015, 2020; NFHS-4 (2015-16); and NFHS-5 (2019-21), then after pair model such as, Brass logit, Splicing, and Modified logit were used to calculate age pattern of mortality and e0 using under-five mortality rate and adult mortality rate for 2015 and 2020 at national and subnational levels. The results reveal that the Splicing model’s age pattern of mortality and e0 is the closest to the Chiang method compared to the Brass logit and Modified logit models at both national and subnational levels, among men and women in the SRS and NFHS. The differences in e_0 values between the Splicing and the Chiang models were one or fewer than a year among men and women in both SRS and NFHS. Decomposition analysis reveals that the infant, child, and 5-14-year age groups made a significant contribution to Δe0 between SRS and NFHS in 2015 and 2020. The Splicing model yields the closest e₀ estimates, particularly with SRS data, compared to NFHS, underscoring its importance for subnational mortality assessment in contexts where mortality data are incomplete and unavailable.
Following the introduction of a religion question in the 2001 Census of England and Wales, and its inclusion in the two subsequent censuses of 2011 and 2021, multiple analyses have concluded that the strictly Orthodox Jewish population, known as haredim, has most likely been consistently and substantially undercounted on each occasion. Beyond technical concerns about enumeration accuracy, this is a pressing social problem since a high proportion of this community is young, lives in overcrowded conditions and is economically vulnerable. Previous attempts to investigate the nature of this suspected undercount have been focused on assessing missing individuals while assuming that haredi households have been enumerated accurately. Here, geographical information is used which takes advantage of the fact that, like many ethnic minority groups, the haredi population forms voluntary enclaves, presenting the possibility to directly compare detailed household counts at the postcode sector level held by the community, with equivalent data from the 2021 Census. In doing so, it is demonstrated that the assumption of accurate household enumeration is probably incorrect and that there is credible evidence to indicate that compared with community records, haredi households were undercounted by between 21
Small-area population estimates have long been a critical part of the work program of National Statistical Offices. The 2021 Australian census and following ‘rebasing’ process of population estimates from 1 July 2016 to 30 June 2021 marked five years of small area data produced using the cohort-component method. This period oversaw wider challenges however, with the COVID-19 pandemic interrupting established patterns of internal and overseas migrant flows between March 2020 and June 2021 of this period. This paper sets out to assess the components method after its first five years in small area population estimates. Analysis of percentage error between un-rebased and rebased population estimates was undertaken for Statistical Area Level 2 geographies at 30 June 2021. A selection of measures capturing bias, accuracy, and the effects of larger errors were analysed between higher-order geographies and across a range of demographic profiles. The findings of this analysis show that the cohort-component method performs better with medium-sized, slower growing or more stable populations, while larger errors tend to result among faster growing populations and those at each size extreme. This analysis provides important insights for users of Australian small area population estimates to understand data dynamics at finer geographical scales.
We evaluate the short- and long-term impacts of a supply-side conditional cash transfer (SS-CCT) program that incentivized healthcare providers to increase the delivery of essential maternal and child health services in Afghanistan. Leveraging data from a randomized controlled trial conducted between 2010 and 2013 and nationally representative household surveys from 2013 to 2018, we estimate causal effects during the implementation period and after program termination. Short-term impacts are identified using two-stage least squares (2SLS), instrumenting actual service receipt with randomized facility assignment. Long-term effects are estimated using a multilevel random effects model that exploits variation in historical exposure to the SS-CCT program. Results show that the intervention significantly increased antenatal care visits, institutional deliveries, and child immunizations in the short run, with larger gains among women with formal education and households in higher wealth quintiles. After the program ended, these gains diminished for most preventive services but persisted for institutional deliveries. Supplementary analyses suggest that sustained provider motivation and facility quality are critical to maintaining long-term impacts. These findings highlight both the potential and fragility of SS-CCT programs in resource-constrained environments like Afghanistan.
This study investigates the impact of demographic aging on income inequality in Central and Eastern European (CEE) states in 2005 and 2022. Using EU-SILC data, the analysis examines income disparities through the lenses of age and household type, exploring differences between CEE post-socialist liberal and corporatist welfare state typologies. The results highlight growing income disparities across age groups and household types, with elderly-headed households consistently recording lower incomes, particularly in the case of single-person elderly households, which may reflect the effects of demographic aging. Conversely, multi-generational households mitigate inequality, offering more economic stability in both CEE liberal and corporatist states. The findings reveal significant variations between post-socialist welfare state typologies. Liberal post-socialist states, such as Estonia, Latvia, and Lithuania, exhibit higher overall inequality, whereas corporatist states, including Poland, Czechia, and Slovakia, demonstrate lower disparities. However, inequality among elderly households has risen in both typologies, with pronounced challenges in addressing the vulnerabilities of single-person elderly households. This study contributes to the neo-familial perspective, emphasizing the role of families and households in mitigating economic vulnerabilities, particularly in aging societies. The results underline the need for targeted policies, including strengthening redistributive pensions, incentivizing family caregiving, and supporting multi-generational living arrangements to reduce inequalities exacerbated by demographic shifts. These insights inform policymakers seeking to balance demographic challenges with economic equity in rapidly aging societies.
