To capture the range of possible future population trajectories under varying fertility regimes, three scenarios are established. In the low scenario, fertility would continue to drop to extremely low level at 0.75 by 2035, while fertility would slowly rise to higher levels at 1.3 and 1.6 respectively by 2050 in the context of varying degrees of fertility policy incentives under medium and high scenarios. Results indicate that China's population will continue to shrink throughout the 21st century, declining to 1.18-1.28 billion by 2050, falling below 1 billion between 2063 and 2078, and further decreasing to 0.45-0.80 billion by 2100. The number of annual births in China is expected to follow a downward trajectory throughout the 21st century. Although a recovery in women's fertility rate may drive a fluctuating rebound in birth numbers, the long-term downward trend is unlikely to be altered due to the substantial challenges and limited potential for increasing fertility rate, as well as the ongoing reduction in the number of women of childbearing age. Moreover, fluctuations in the births will affect the size of school-age population through cohort transmission. Projections suggest that China's school-age population will experience a sharp reduction over the next 15 years, with substantial implications for the allocation of educational resources. Additionally, while the size and share of the working-age population aged 15-64 will fluctuate slightly, both are expected to trend downward during this century. Meanwhile, China will witness an acceleration in its population ageing. The proportion of elderly population aged 65 and above is projected to exceed 30% in the mid-to-late 2040s. By then, the size of elderly population will exceed 380 million, making China the country with the largest elderly population in the world.
The findings also highlight an increasing divergence between urban and rural population. The urban population is expected to continue growing over the next decade, remaining above 940 million until 2050, while the rural population will maintain a sustained shrinking trend throughout the century. Both urban and rural areas will experience a notable decline in the child population aged 0-14 within the next five years, with a reduction of approximately one-fifth in urban areas and around two-fifths in rural areas. The ageing process in rural areas is ahead of that in urban areas, although the urban elderly population will have a longer growth period and a higher peak value.
The findings reveal a profound and multifaceted transformation of Chinese households. In terms of quantity and size, although the total number of households continues to rise, average household size steadily declines, reflecting a persistent trend toward smaller household units. One-person households are projected to become the dominant household type. Two-person households show a modest increase in absolute number but a declining share in the overall household structure. By contrast, households comprising three or more persons exhibit sustained declines in both number and proportion.
At the structural level, significant shifts are observed in the age composition and functional characteristics of households. First, elderly households—those containing members aged 65 and above—are becoming increasingly common. Notably, households including the oldest-old (aged 80 and above) are growing at a particularly rapid pace. Solo-living among the elderly and two-person elderly-only households will become increasingly common. Second, the proportion of households with children (aged 18 and below) is systematically declining. Third, the number of young adult households—those comprising individuals aged 20 to 49—is expected to increase initially but eventually decline, accompanied by a sustained rise in young adults living alone. A related and critical development is the pronounced decrease in both the number and share of childbearing households—defined here as households containing a married woman of reproductive age. Fourth, while nuclear families are decreasing in number and stem families are increasing slightly, both categories are losing ground in terms of their relative share among all household types.
These trends point to three major structural risks facing Chinese households. The first is the simultaneous growth in the number of households and the contraction in household size, which together weaken traditional family functions such as caregiving and intra-household economic support. The second is the impending inversion of the household age structure, wherein elderly households are projected to substantially outnumber households with children. The third is the contraction of the young adult demographic and the associated decline in childbearing households, undermining both social vitality and the foundations of demographic reproduction. Collectively, these changes pose considerable challenges to the planning and delivery of public services, the robustness of the social security system, and the formulation of medium- and long-term socioeconomic strategies. The findings underscore the urgent need for policy frameworks to move beyond individual-level demographic projections and proactively adapt to the shifting structure and needs of households.
This research addresses three core questions: (1) How can a comprehensive measurement system for healthy ageing be constructed for China, considering China's unique socioeconomic conditions? (2) What are the temporal trends, structural characteristics, and regional disparities in China's healthy ageing levels? (3) Based on empirical findings, what targeted pathways can be proposed for optimization? To answer these questions, we developed a six-dimensional index encompassing physical health, mental health, social participation, living environment, economic security, and health behaviors and knowledge. The analysis integrates nationally representative microdata from the China Longitudinal Aging Social Survey (CLASS) with macro-level statistics from the China Statistical Yearbook. Entropy method is employed for objective weighting to synthesize a composite Healthy Ageing Index (HAI), and kernel density estimation is utilized to analyze distribution dynamics and regional evolution.
The key findings reveal a steady improvement in China's national HAI, rising from 0.1653 in 2018 to 0.2339 in 2023. However, progress is highly uneven across dimensions and regions. Significant gains were observed in the dimensions of physical health, living environment, and health behaviors and knowledge, which emerged as the primary drivers of overall improvement. In contrast, mental health, social participation, and economic security showed minimal improvement, constituting critical and persistent bottlenecks. Furthermore, healthy ageing among China's older population exhibits significant regional disparities and dimensional imbalances.
Based on these empirical findings, this study proposes five interconnected optimization pathways: (1) strengthening the economic security system to solidify the foundation for healthy ageing; (2) constructing community-based psychosocial support networks to address gaps in mental well-being and social inclusion; (3) promoting life-cycle health management to sustain gains in physical health and behavioral improvements; (4) leveraging smart technologies for inclusive, age-friendly environmental upgrades while bridging the digital divide; and (5) cultivating an interdisciplinary talent pool to support the sustainable operation of service systems.
The contributions of our study are threefold. Firstly, it advances the theoretical framework by integrating the World Health Organization's “functional ability” concept with China's specific contextual factors into a coherent, multi-dimensional measurement system. Secondly, it provides a robust longitudinal and spatial analysis of healthy ageing trends in China using recent nationwide data and objective weighting techniques, offering novel empirical evidence on evolving regional patterns and dimensional bottlenecks. Thirdly, in terms of policy relevance, the findings and proposed pathways offer a data-driven, localized roadmap for policymakers to design targeted interventions, contributing to the strategic goals of “Healthy China 2030” and an effective response to population ageing.
Drawing on data from the 2023 Survey of Social Condition of Foreign Talents in Guangzhou and Shenzhen, this study employs a logit model to systematically identify the acculturation patterns of high-skilled foreign professionals in China and delineate the mechanisms by which these patterns influence residence intentions through life satisfaction, place dependence, and place identity.
The analysis revealed four primary acculturation strategies: assimilation-inclined integration, integration, moderate integration, and separation. These findings extend and empirically test the applicability of bidirectional acculturation theory to non-traditional immigration contexts. Most professionals adopt proactive strategies (assimilation-inclined integration, integration, moderate integration), all of which show positive associations with residence intentions in both the short and long term. By contrast, only a minority (16.07%) resort to separation—a finding that contrasts with earlier observations of short-term high-skilled migrants frequently remaining within an “expat bubble”. Second, these strategies influence residence intentions through distinct mediating mechanisms. Integration operates via life satisfaction, place dependence, and place identity; assimilation-inclined integration and moderate integration operate via life satisfaction and place dependence. Third, self-efficacy plays a significant protective role, both by indirectly influencing settlement intentions through moderating the effects of assimilation-oriented acculturation strategies on life satisfaction and place identity, and by showing a significant positive correlation with long-term settlement intentions. Fourth, proactive acculturation has a stronger positive effect on residence intentions of family-reunion migrants than on those of corporate expatriates, whereas moderate integration is more effective in boosting residence intentions of career-oriented migrants. The frequency of voluntary participation is a direct positive predictor of settlement intentions among separated individuals. However, high-frequency participation undermines the positive effect of integration-oriented and moderate integration strategies on short-term settlement intentions. Autonomous participation attenuates only the effect of integration-oriented strategies on short-term settlement intentions. In contrast, the influence pathways of acculturation strategies remain largely unaffected by variations in the frequency of community-based participation.
We propose an integrated three-pronged strategy to promote proactive cultural adaptation and strengthen long-term retention among foreign high-skilled professionals in China. This involves: (1) establishing a targeted identification and dynamic evaluation mechanism to deliver motivation-strategy aligned interventions; (2) defining a clear collaborative governance framework between the government and market actors across functional and psychological dimensions to clarify roles and enhance synergy; and (3) constructing a tiered social participation platform, guided by public-service initiatives and supported by community networks, to provide structured pathways for meaningful engagement. Collectively, these measures are designed to cultivate an enabling ecosystem that facilitates adaptive acculturation and systematically enhances foreign professionals' willingness to pursue sustained career development in China.
In this context, this study aims to clarify the impact of AI development on workers' overall employment quality and its sub-dimensions, explore the underlying mechanisms, and examine heterogeneity across different groups. To address these issues, this study combines city-level AI patent data with individual-level data from the China Family Panel Studies (CFPS), constructing a comprehensive employment quality index at the worker level and an AI patent density indicator at the city level. A fixed-effects model is employed for baseline regression analysis. To address potential endogeneity concerns, this study further applies an instrumental variable approach, the Heckman two-step method, and an exogenous shock identification strategy. In addition, a series of robustness checks are conducted.
The main findings are as follows. First, AI development significantly improves workers' overall employment quality： a one-standard-deviation increase in city-level AI patent density raises employment quality by 2.21%. This result holds after accounting for endogeneity and conducting multiple robustness tests. Second, analysis of the sub-dimensions of employment quality shows that AI development significantly increases labor income, improves welfare security, enhances job stability, and reduces the risk of overwork, while its effect on job satisfaction is statistically insignificant. Third, mechanism analysis indicates that AI development improves employment quality mainly by promoting occupational upgrading, strengthening human capital accumulation, and improving job-skill matching. Fourth, heterogeneity analysis indicates that the employment quality enhancement effect of AI development varies across groups. The positive effects are more prominent among workers with lower employment quality, female workers, and those with stronger non-cognitive skills.
Based on these findings, this study proposes several policy implications： actively expanding new forms of human-machine collaboration to create more high-quality jobs; building a lifelong learning system to facilitate workers' skill upgrading; and integrating non-cognitive skill development into the education system to enhance workers' comparative advantages in human-machine collaboration. Together, these measures can help achieve broad-based improvement in employment quality in the AI era. In summary, through rigorous empirical analysis, this study provides new micro-level evidence and theoretical explanations for understanding the evolution of employment quality in the AI era. It deepens theoretical insights into the role of technology in empowering workers, and offers more targeted policy implications for guiding AI development toward the promotion of high-quality employment and the creation of a more equitable labor market.
Moreover, this paper examines the evolution of China's institutional system for proactively addressing population ageing from three dimensions： types of institutional tools, composition of governance actors, and paradigms of institutional objectives. The study finds that the content of these institutions has expanded from basic livelihood security to comprehensive multi-domain governance, while Institutional arrangements have progressed from initial basic living safeguards to lifecycle-spanning strategic responses. This evolution reflects a shift from “reactive coping” to “proactive governance,” from “unilateral governance” to “collaborative governance,” and from “ensuring survival” to “promoting comprehensive development”—a process characterised by “adapting institutions to demographic changes.” Such an evolutionary pathway offers instructive insights for enriching and improving the institutional system of the national strategy during the 15th Five-Year Plan period and beyond.
Looking ahead, implementing the national strategy for proactively addressing population ageing should build on the established institutional framework. It will be essential to strengthen institutional guarantees through legislation, gradually advancing specialised laws for the elderly population. Institutional systematicity should be reinforced to enhance the system's capacity for dynamic response, systemic coordination, and long-term provision. Innovation in institutional implementation mechanisms is needed to improve resilience to demographic transition, economic development, and social transformations. Digital and intelligent reforms in institutions should be promoted to elevate the scientific accuracy of institutional supply. Through these measures, the adaptability of institutional design, the efficiency of institutional operation, and the feasibility of institutional safeguards can be steadily improved.
To address this gap, this study draws on six most extensively used national large-scale social surveys among Chinese scholars. It compares their sampling designs and empirically investigates the similarities and differences in their sample structures. Using a consistent model specification, this study investigates the impact of deviations in sample structure on statistical analysis results, and reveals the underlying logic by which sample structure influences statistical inference.
The main findings are as follows. First, although almost all surveys employ a multi-stage, stratified Probability Proportional to Size (PPS) random sampling method, they exhibit significant differences in sampling frame coverage, stratification principles, the sampling methods and quantities of sampling units at each stage, and within-household sampling procedures. Second, notable disparities exist in the distributions of key demographic variables across the surveys. Moreover, each survey's sample structure deviates to some extent from that of the 2015 National 1% Population Sample Survey. Third, differences in sample structure lead to variations in statistical results. Under identical models, analyses based on different survey data yield both a consensus component reflecting shared social realities and significant discrepancies in the significance and direction of effects for certain variables. Fourth, adjustments in population definitions, weighting schemes, variable selection, and operationalization alter the joint distribution of variables within a sample, thereby significantly affecting statistical outcomes. When sample structures differ initially, such adjustments may further amplify discrepancies in results across different survey datasets. Fifth, the foundational role of sample structure in the methodology of statistical inference must be fully acknowledged.
Based on these findings, the study recommends that researchers should meticulously review survey technical documentation,prudently select appropriate survey data based on research objectives, appropriately address data missingness and weighting, prioritize robustness checks of analytical results, and thoroughly evaluate or explain the sample representativeness of the survey data used. Survey institutions, on the other hand, should provide more detailed weighting information and comprehensive technical documentation to enable researchers to use the data more appropriately.
The primary contributions of this study are as follows. (1) It employs empirical methods to systematically examine the sample structures of six large-scale social surveys and the impact of sample structure deviations on statistical results, revealing methodological pitfalls that offer a new perspective for understanding the contradictory conclusions drawn from different datasets in existing literature. (2) Theoretically, it extends methodological reflection in quantitative research from model specification back to the data-collection stage, broadening scholarly discourse. (3) Practically, it provides empirical guidance for standardizing data usage in quantitative research, thereby enhancing the comparability and robustness of research conclusions.
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