In 2023, the birth rate across different regions in China varied from around 13.7 births per 1,000 inhabitants (per mille) in Tibet to 2.9 per mille in Heilongjiang province. The average national birth rate ranged at 6.4 per mille that year. High disparity of birth rates across China Regional birth rates in China reach their highest values in western and southwestern provinces and autonomous regions. In this part of the country, the economy is less developed than in the coastal provinces and traditional values are more prevalent. At the same time, many people from minority communities live in these areas, who were less affected by strict birth control measures in the past and traditionally have more children. In contrast, the lowest birth rates in recent years were registered in the northwestern provinces Jilin, Liaoning, and Heilongjiang, which is the rust belt of China. This region offers few economic opportunities, and many young people leave for a better life in the eastern provinces. They often leave old people behind, which is one reason why these provinces also have some of the highest mortality rates in China. Future developments As most Chinese regions with a higher fertility rate have only few inhabitants, they cannot compensate for the increasing number of provinces with a declining populace. In the future, only economically successful cites will be able to escape this trend, while many provinces and rural areas will slowly lose a significant share of their population.

In 2023, the natural growth rate of the population across China varied between 7.96 people per 1,000 inhabitants (per mille) in Tibet and -6.92 per mille in Heilongjiang province. The national total population growth rate turned negative in 2022 and ranged at -1.48 per mille in 2023. Regional disparities in population growth The natural growth rate is the difference between the birth rate and the death rate of a certain region. In China, natural population growth reached the highest values in the western regions of the country. These areas have a younger population and higher fertility rates. Although the natural growth rate does not include the direct effects of migration, migrants are often young people in their reproductive years, and their movement may therefore indirectly affect the birth rates of their home and host region. This is one of the reasons why Guangdong province, which received a lot of immigrants over the last decades, has a comparatively high population growth rate. At the same time, Jilin, Liaoning, and Heilongjiang province, all located in northeast China, suffer not only from low fertility, but also from emigration of young people searching for better jobs elsewhere. The impact of uneven population growth The current distribution of natural population growth rates across China is most likely to remain in the near future, while overall population decline is expected to accelerate. Regions with less favorable economic opportunities will lose their inhabitants faster. The western regions with their high fertility rates, however, have only small total populations, which limits their effect on China’s overall population size.

CN: Population: Birth Rate: Anhui data was reported at 0.617 % in 2024. This records a decrease from the previous number of 0.645 % for 2023. CN: Population: Birth Rate: Anhui data is updated yearly, averaging 1.288 % from Dec 1990 (Median) to 2024, with 35 observations. The data reached an all-time high of 2.447 % in 1990 and a record low of 0.617 % in 2024. CN: Population: Birth Rate: Anhui data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: Birth Rate: By Region.

CN: Population: Birth Rate: Shanxi data was reported at 0.694 % in 2024. This records an increase from the previous number of 0.613 % for 2023. CN: Population: Birth Rate: Shanxi data is updated yearly, averaging 1.132 % from Dec 1990 (Median) to 2024, with 35 observations. The data reached an all-time high of 2.254 % in 1990 and a record low of 0.613 % in 2023. CN: Population: Birth Rate: Shanxi data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: Birth Rate: By Region.

CN: Population: Birth Rate: Jiangsu data was reported at 0.500 % in 2024. This records an increase from the previous number of 0.481 % for 2023. CN: Population: Birth Rate: Jiangsu data is updated yearly, averaging 0.934 % from Dec 1990 (Median) to 2024, with 35 observations. The data reached an all-time high of 2.054 % in 1990 and a record low of 0.481 % in 2023. CN: Population: Birth Rate: Jiangsu data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: Birth Rate: By Region.

CN: Population: Birth Rate: Guizhou data was reported at 1.074 % in 2024. This records an increase from the previous number of 1.065 % for 2023. CN: Population: Birth Rate: Guizhou data is updated yearly, averaging 1.397 % from Dec 1990 (Median) to 2024, with 35 observations. The data reached an all-time high of 2.309 % in 1990 and a record low of 1.065 % in 2023. CN: Population: Birth Rate: Guizhou data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: Birth Rate: By Region.

In 2024, approximately **** children were born per 1,000 permanent residents in Guangdong province, China. The relaxation of the one-child policy and its final abolition in 2016 had a positive effect on the number of births in Guangdong. However, figures since 2020 indicate that the birth rate has fallen below previous levels.

The outbreak of the COVID-19 in early 2020 and the recurring epidemic in later years have disturbed China’s economy. Moreover, China’s demographic dividend has been disappearing due to its fastest aging population and declining birth rate. The birth rates in eastern provinces of China are much lower than those of the western provinces. Considering the impacts of the COVID-19 and aging population, this paper focused on the relationship between birth rate and the disposable income and tried to find effective measures to raise China’s birth rate. We discovered through regression analysis that the link between per capita disposable income and birth rate is initially "reverse J" and later "inverted J", indicating that per capita disposable income will influence the birth rate. Women’s employment rate and educational level are negatively correlated with the birth rate. To raise the fertility rate in China, it is necessary to increase the marriage rate and the willingness to have children by raising the per capita disposable income and introducing effective tax relief policies.

In 2024, approximately **** children per 1,000 regular resident population were born in Zhejiang province in China. The gradual relaxation of the one-child policy and its final abolition in 2016 did only have a moderate effect on the birth rate in Zhejiang. The negative effects of the coronavirus pandemic and the following economic downturn on the birth rate, however, are very obvious in the case of Zhejiang.

The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of live births to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age and age-specific fertility rates to map the estimated distributions of births for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al. and James et al.. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Taiwan 1km Births. Version 1.0 2015 estimates of numbers of live births per grid square, with national totals adjusted to match UN national estimates on numbers of live births (http://esa.un.org/wpp/). DOI: 10.5258/SOTON/WP00581

This study is part of a program of in-depth surveys on the population fertility and related factors in various provinces and municipalities of China.. The study aimed to improve understanding of the levels and trends in fertility of the Chinese population and to provide the government with reliable data useful in the formation of population policy. Data were collected in the provinces of Beijing, Liaoning, Gansu, Guangdong, Guizhou, and Shandong. For each province, data were collected on complete pregnancy and marriage history, fertility preferences and contraception, and socio-economic background.

V1 dataset:Under the global framework of Shared Socioeconomic Pathways (SSPs), based on localized population and economic parameters, a Population Development Environment (PDE) model is adopted to construct population grid data for SSPs from 2020 to 2100; Using the Cobb Douglas model, construct economic data for SSPs from 2020 to 2100.The v1 dataset includes:Population grid data of the world, The Belt and Road region, and China, with a spatial resolution of 0.5°GDP grid data of the world, The Belt and Road region, and China, with a spatial resolution of 0.5 °Grid data on the output value of three industries in the Chinese region, with a spatial resolution of 0.1 °V2 dataset:Based on the data from the 7th National Population Census of China, starting from 2020, the parameters such as fertility rate, mortality rate, migration rate, and education level in the Population Development Environment (PDE) model were updated. Under the Shared Socioeconomic Pathways (SSP1-5), a new version (v2) of the total population and age and gender specific population projection dataset for China and its provinces from 2020 to 2100 was created. Based on the data from the 7th National Population Census and the 4th Economic Census of China, with 2020 as the starting year, the parameters of total factor productivity, capital stock, labor input, and capital elasticity coefficient in the Cobb Douglas model were updated. Under the shared SSP1-5, a new version (v2) of China and its provincial GDP projectiondataset from 2020 to 2100 was created.The v2 (2024 version) dataset includes:Total Population Data of China and Provinces (2020-2100)Population data by age and gender in China (2020-2100)China and Provincial GDP Data (2020-2100)

Population: Birth Rate: Liaoning data was reported at 0.406 % in 2023. This records a decrease from the previous number of 0.408 % for 2022. Population: Birth Rate: Liaoning data is updated yearly, averaging 0.664 % from Dec 1990 (Median) to 2023, with 34 observations. The data reached an all-time high of 1.630 % in 1990 and a record low of 0.406 % in 2023. Population: Birth Rate: Liaoning data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: Birth Rate: By Region.

The health and survival of women and their new-born babies in low income countries is a key public health priority, but basic and consistent subnational data on the number of pregnancies to support decision making has been lacking. WorldPop integrates small area data on the distribution of women of childbearing age, age-specific fertility rates, still births and abortions to map the estimated distributions of pregnancies for each 1x1km grid square across all low and middle income countries. Further details on the methods can be found in Tatem et al and James et al.. WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton). 2018. Taiwan 1km Pregnancies. Version 1.0 2015 estimates of numbers of pregnancies per grid square, with national totals adjusted to match national estimates on numbers of pregnancies made by the Guttmacher Institute (http://www.guttmacher.org) DOI: 10.5258/SOTON/WP00632

The data set records the statistical data of birth rate, death rate and natural growth rate (2001-2008) in different regions of China, and the data are divided by year. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains eight data tables, each of which has the same structure. For example, the data table in 2008 has five fields: Field 1: Province (city, district) Field 2: total population at the end of the year Field 3: birth rate Field 4: population mortality Field 5: natural population growth rate

Abstract (en): The China Multi-Generational Panel Dataset - Liaoning (CMGPD-LN) is drawn from the population registers compiled by the Imperial Household Agency (neiwufu) in Shengjing, currently the northeast Chinese province of Liaoning, between 1749 and 1909. It provides 1.5 million triennial observations of more than 260,000 residents from 698 communities. The population mainly consists of immigrants from North China who settled in rural Liaoning during the early eighteenth century, and their descendants. The data provide socioeconomic, demographic, and other characteristics for individuals, households, and communities, and record demographic outcomes such as marriage, fertility, and mortality. The data also record specific disabilities for a subset of adult males. Additionally, the collection includes monthly and annual grain price data, custom records for the city of Yingkou, as well as information regarding natural disasters, such as floods, droughts, and earthquakes. This dataset is unique among publicly available population databases because of its time span, volume, detail, and completeness of recording, and because it provides longitudinal data not just on individuals, but on their households, descent groups, and communities. Possible applications of the dataset include the study of relationships between demographic behavior, family organization, and socioeconomic status across the life course and across generations, the influence of region and community on demographic outcomes, and development and assessment of quantitative methods for the analysis of complex longitudinal datasets. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Standardized missing values.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. Smallest Geographic Unit: Chinese banners (8) The data are from 725 surviving triennial registers from 29 distinct populations. Each of the 29 register series corresponded to a specific rural population concentrated in a small number of neighboring villages. These populations were affiliated with the Eight Banner civil and military administration that the Qing state used to govern northeast China as well as some other parts of the country. 16 of the 29 populations are regular bannermen. In these populations adult males had generous allocations of land from the state, and in return paid an annual fixed tax to the Imperial Household Agency, and provided to the Imperial Household Agency such home products as homespun fabric and preserved meat, and/or such forest products as mushrooms. In addition, as regular bannermen they were liable for military service as artisans and soldiers which, while in theory an obligation, was actually an important source of personal revenue and therefore a political privilege. 8 of the 29 populations are special duty banner populations. As in the regular banner population, the adult males in the special duty banner populations also enjoyed state allocated land free of rent. These adult males were also assigned to provide special services, including collecting honey, raising bees, fishing, picking cotton, and tanning and dyeing. The remaining populations were a diverse mixture of estate banner and servile populations. The populations covered by the registers, like much of the population of rural Liaoning in the eighteenth and nineteenth centuries, were mostly descendants of Han Chinese settlers who came from Shandong and other nearby provinces in the late seventeenth and early eighteenth centuries in response to an effort by the Chinese state to repopulate the region. 2016-09-06 2016-09-06 The Training Guide has been updated to version 3.60. Additionally, the Principal Investigator affiliation has been corrected, and cover sheets for all PDF documents have been revised.2014-07-10 Releasing new study level documentation that contains the tables found in the appendix of the Analytic dataset codebook.2014-06-10 The data and documentation have been updated following re-evaluation.2014-01-29 Fixing variable format issues. Some variables that were supposed to be s...

Per capita disposable income of urban residents in different regions Unit: Yuan.

Notes from product: II. Notes on China 2000 and 2010 Population Census Data In order to guide you to use the data correctly, provide you some explanations as follows: (l) Census time: 0:00AM of November 1, 2000 and 2010 as the reference time for the census. (2) The 2000 and 2010 population census covered all persons who hold the nationality of, and have permanent residing place in the People's Republic of China. During the census, each person was enumerated in his/her permanent residing place. The following persons should be enumerated in their permanent residing place: a) Those who reside in the townships, towns and street communities and have their permanent household registration there. b) Those who have resided in the townships, towns and street communities for more than 6 months but the places of their permanent household registration are elsewhere. c) Those who have resided in the townships, towns and street communities for less than 6 months but have been away from the place of their permanent household registration for more than 6 months. d) Those who live in the townships, towns and street communities during the population census while the places of their household registration have not yet settled. e) Those who used to live in the townships, towns and street communities but are working or studying abroad during the census and have no Permanent household registration for the time being. (3) Two types of questionnaires (long form and short form) were used for the 2000 and 2010 population census. The short form contains items that reflect the basic situation of the population, while the long form include all short form items plus other items such as migration, education, economic activities, marriage and family, fertility , housing , etc. . According to the National Bureau of Statistics of China, the households for the Long Form survey were selected by a random sampling program. The data included in this product are from 100% Short Form survey.(4) Results in this publication are based on the processing of data directly from enumeration without any adjustment. It is therefore worthwhile to notice the following: a. Data in the publication do not include population not enumerated in the Census. b. Data in the publication do not include the servicemen of the People's Liberation Army. c. The post-enumeration sample survey indicates an undercount of 1.81% in 2000 Census and 0.12% in 2010 Census. III. Notes on the China Province GIS Maps for the 2000 and 2010 Population Census Data (1) The China Province GIS map were developed for the 2000 and 2010 population Census data, which covered all 31 municipalities, provinces and autonomous regions of China, except for Taiwan, Hong Kong and Macao. (2) The population data came from the 5th and 6th China Population Census surveyed in 2000 and 2010. The GIS data is based on the national digital map (1:1 million) developed by the National Geographic Information Center of China (NGCC), including rives, roads, residential area and administrative boundaries.(3) The China province GIS maps are developed for matching 2000 and 2010 China population Census data, which should only be used as references for research or education instead of used as official maps. The distributor is not responsible for the accuracy of the those maps if the maps are used for business or other purposes.

Regression results after excluding the variable EL.

As China continues to implement its progressive fertility promotion policy, there has been a drastic decline in the fertility rate. Given that the migrant population constitutes more than a quarter of China’s total population, enhancing the willingness of this demographic to have additional children through policy-guided urban public services is pivotal for optimizing China’s population development strategy. This study analyzes the influence of urban public services on the reproductive intentions of the migrant population, utilizing data from 110,667 migrant families with one child, drawn from China’s Migrant Population Dynamic Monitoring data in 2016 and 2018. The data analysis reveals several key findings: (1) Urban public services, overall, exhibit a notable positive effect on the willingness of the migrant population to have more children, albeit with limitations and a declining trend. (2) Among urban public services, primary basic education significantly impacts the willingness of the migrant population to expand their families. (3) Large cities have created a ’reverse screening’ effect on the migrant population, leading to differential access to public services. This scenario caters effectively to the high human capital migrant individuals while reducing accessibility to livelihood public services for the low human capital migrant population. This paper critically evaluates China’s progressively adjusted fertility policy from the perspective of the migrant population. It underscores the necessity of establishing a comprehensive fertility support policy system across China.