The paper “China’s Population Development Trends and Policy Implications”, co-authored by Assistant Prof. Lei Chen and Prof. Jing He from our team, together with Prof. Songxi Chen of Tsinghua University, has been officially published in Statistical Research, a leading Chinese journal in the field of statistics.
Abstract
Population decline, low fertility, and population aging have posed growing challenges and risks to China’s population security, economic development, and social security system. Building on the conventional cohort-component method with deterministic parameter settings under high-, medium-, and low-fertility scenarios, this paper develops a robust estimation method for uncertainty in the total fertility rate based on the idea of “sufficient coverage.” Combined with the cohort-component method, the study projects China’s population trends from 2026 to 2100 under three fertility scenarios and provides corresponding confidence intervals.
The results show that China’s total population is expected to continue declining, while low fertility and population aging will become increasingly pronounced. In the short term (2026–2050), the projections under the three scenarios differ only slightly, indicating that changes in the total fertility rate have a limited impact on short-term population trends. In the long term (2051–2100), however, the projections diverge substantially. The low-fertility scenario produces a more severe demographic outlook, whereas the high-fertility scenario shows a marked improvement relative to the medium scenario, highlighting the important role of fertility changes in shaping medium- and long-term population trends.
Sensitivity analyses further show that a modest increase in the total fertility rate can significantly improve China’s long-term demographic outlook. Fertility-support policies exhibit a clear “window effect,” with delayed implementation leading to greater losses in policy effectiveness. Owing to changes in the cohort structure of women of childbearing age, postponing the age of childbearing may, in the medium to long term, slightly alleviate population decline and aging. Increases in life expectancy can raise the medium- and long-term population size, but the additional population is mainly concentrated among older age groups.
Based on these findings, the paper recommends improving fertility-support policies, making full use of the 2026–2035 policy window, and strengthening dynamic population monitoring and forecasting. The study provides an empirical basis and policy reference for addressing population decline, low fertility, and aging, and for promoting long-term balanced population development and sustainable socioeconomic development.
Author Introduction
Lei Chen is an Assistant Professor at the Joint Laboratory of Data Science and Business Intelligence, Southwestern University of Finance and Economics. His main research interests lie at the intersection of demography, big data, and macroeconomics.
Songxi Chen is a Chair Professor at Tsinghua University, and Chief Scientist of the Institute for Interdisciplinary Innovation in Statistics at Southwestern University of Finance and Economics. His main research interests include demography, statistical inference for ultra-high-dimensional data, mathematical geophysics, statistical methods for climate change, and econometrics.
Jing He is a Professor at the Joint Laboratory of Data Science and Business Intelligence, Southwestern University of Finance and Economics. Her main research interests include high-dimensional data analysis and statistical inference for complex data.
