Content of Exploring Population Theory with Chinese Characteristics in our journal

Published in last 1 year |  In last 2 years |  In last 3 years |  All Please wait a minute... For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails Select Reproductive Cycle Transition: A Historical Review, Future Prospects, and Theoretical Construction from an International Comparative Perspective Geng Wenjun, Ding Jinhong, Shen Ke, Gu Gaoxiang Population Research    2025, 49 (4): 3-19.   Abstract （1911）      PDF （1384KB）（994）       Knowledge map    Save The reproductive cycle refers to the process from a woman's first to last birth. Through a systematic categorization and analysis of the evolution of reproductive cycles across global regions, combined with theoretical discussions on long-term demographic development, this study reveals that reproductive cycle evolution exhibits significant ergodicity, termed the Reproductive Cycle Transition (RCT). The RCT progresses through four stages: a Steady-State Stage, a Compression Stage, a Leveling-Off Stage, and an Equilibrium Stage. It shifts from a traditional pattern characterized by a low age at first birth, a high age at last birth, and a long reproductive span (“low-high-high”) to a modern pattern characterized by a high age at first birth, a low age at last birth, and a short reproductive span (“high-low-low”). The RCT parallels the fertility transition. Europe, North America, Australia, New Zealand and East Asia have entered the Leveling-Off Stage. In contrast, most of Asia, Africa, and Latin America are in the late stage of the Compression Stage, while East, Central, and West Africa remain in their early stage. China's reproductive cycle exhibits an accelerated pattern, beginning in the 1960s and entering the Leveling-Off Stage by the early 1990s. The shortening of the reproductive span carries the risk of lowest-low fertility. Fertility support policies should target the distinct fertility needs of women across different age groups. Reference | Related Articles | Metrics Select From “Baby Boom” to “Ageing Boom”: Facts and Trends Du Peng, Ma Qifeng Population Research    2025, 49 (3): 3-19.   Abstract （2367）      PDF （1268KB）（949）       Knowledge map    Save As the “ageing echo” of the “Baby Boom”, the “Ageing Boom” has not yet received sufficient scholarly attention. Since the founding of the People's Republic of China, the nation has experienced four distinct “Baby Boom” cohorts, which are projected to transform into “Ageing Boom” during the periods 2010-2018, 2022-2036, 2041-2054, and 2071-2079 respectively. Each “Ageing Boom” represents a peak in the growth of the new elderly population, and its cumulative and superimposed effects will drive China's ageing population through phased transformations characterized by sequential stages: ascent, peak, buffer, and decline. China's demographic ageing under the “Ageing Boom” paradigm exhibits both distinctive and general characteristics: a historically unprecedented population scale, asynchronous growth in size and proportion, ageing of the age structure, balancing of the gender structure, and steadily rising survival rates. Focusing on the ongoing second “Ageing Boom”, projections indicate that approximately 330 million individuals will enter old age, with urban residents and population with at least secondary education constituting the majority of this elderly cohort. These demographic shifts present dual implications—harboring developmental opportunities while simultaneously posing practical challenges that require prudent consideration and proactive responses. Reference | Related Articles | Metrics Select Changing Scale and Structure of China's Floating Population in the Context of Negative Population Growth Zhou Hao Population Research    2025, 49 (3): 20-35.   Abstract （1511）      PDF （1247KB）（277）       Knowledge map    Save Under the background of negative population growth, whether the scale of China's floating population will continue to grow and how its structure will change in the future are related to the construction goals of relevant social systems. Based on the data of the fifth, sixth, and seventh national population censuses, age structure standardization and decomposition methods are used to analyze the relative role of structure effect, scale effect, and intensity effect in the change of China's floating population in the past 20 years, and population projections are used to examine the future trend of the floating population. Research has found that the increase in the size of China's floating population in the past 20 years is mainly due to scale and intensity effects. Among them, the increase in the size of the urban floating population is mainly due to scale effects, while the increase in the rural floating population is mainly due to intensity effects; The structure effect has always had a negative impact, with the negative effect in the last 10 years being greater than that in the first 10 years. This negative structure effect shows similar behavior among different types of floating populations. Assuming the age-specific migration rate remains unchanged, the size of China's floating population will continue to decline in the future, and its age and urban-rural structure will undergo significant changes. The structure effect can be regarded as an intrinsic factor of natural growth, and the study of China's floating population must be situated within the context of negative population growth and population ageing. Reference | Related Articles | Metrics Select The Existence of Population Cushion in International Industrial Division and Its Implications for China Wang Jinying, Zhang Jin Population Research    2025, 49 (2): 32-49.   Abstract （1452）      PDF （1315KB）（360）       Knowledge map    Save Based on previous literature, this study elucidates the influence of population size on international industrial division and its mechanisms. Drawing on data from the World Bank and the World Trade Organization, this study further examines the impact of population size on countries' or regions' participation in the international industrial division. The results show that population size significantly promotes participation, dependence, and competitiveness in international industrial division, indicating a “room for maneuver” of population size. Countries or regions with larger populations are less dependent on the international industrial division and exhibit stronger competitiveness, while smaller countries or regions are more reliant on the international industrial division. In face of the long-term population decline, China should leverage its vast population and territory to capitalize on the room for maneuver in population size. Deepening domestic industrial division, enhancing productivity, and maintaining a complete industrial system could help improve participation and competitiveness in international industrial division, thereby promoting high-quality economic development. Reference | Related Articles | Metrics Select The Potential Impact of Population Size on the Development of Artificial Intelligence Technology Huang Qing, Xie Yu Population Research    2025, 49 (2): 50-63.   Abstract （1889）      PDF （1280KB）（259）       Knowledge map    Save As a new wave of technological revolution and industrial transformation emerges globally, artificial intelligence (AI) is evolving at an accelerated pace, profoundly impacting global economic and social development as well as the advancement of human civilization. The study reveals that, unlike technological innovations of the Industrial Revolution, which primarily relied on experiments and physical models, AI development is inherently data-driven. A large population plays a crucial role in advancing AI technology, particularly by supplying abundant data resources, optimizing the cost of technology development, and accelerating the dissemination and application of innovations. As one of the world's most populous countries, China possesses unique competitive advantages in the AI sector, especially in terms of its vast data foundation, strong market demand, and diverse application scenarios. To further leverage population size as a driver of AI technology development, it is essential to enhance data infrastructure, optimize talent cultivation systems, promote the adoption and application of AI, and strengthen AI ethics and security regulations. Reference | Related Articles | Metrics