The statistic shows the population of Nanjing in China from 1980 to 2010, with forecasts up until 2035. In 2010, the population of Nanjing had amounted to about 6.16 million inhabitants and was forecasted to reach 8.55 million in 2019.

Chart and table of population level and growth rate for the Nanjing, Jiangsu, China metro area from 1950 to 2025. United Nations population projections are also included through the year 2035.

Population: Inflow: Jiangsu: Nanjing data was reported at 91.655 Person th in 2022. This records a decrease from the previous number of 147.497 Person th for 2021. Population: Inflow: Jiangsu: Nanjing data is updated yearly, averaging 160.085 Person th from Dec 2000 (Median) to 2022, with 23 observations. The data reached an all-time high of 231.863 Person th in 2006 and a record low of 91.655 Person th in 2022. Population: Inflow: Jiangsu: Nanjing data remains active status in CEIC and is reported by Nanjing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Non-natural Change.

Population: Usual Residence: Urban: Jiangsu: Nanjing data was reported at 8,325.000 Person th in 2023. This records an increase from the previous number of 8,258.000 Person th for 2022. Population: Usual Residence: Urban: Jiangsu: Nanjing data is updated yearly, averaging 7,283.300 Person th from Dec 2005 (Median) to 2023, with 19 observations. The data reached an all-time high of 8,325.000 Person th in 2023 and a record low of 5,259.035 Person th in 2005. Population: Usual Residence: Urban: Jiangsu: Nanjing data remains active status in CEIC and is reported by Nanjing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Usual Residence: By Residence.

. China Population: Household Registration: Urbanization Rate: Jiangsu: Nanjing data remains active status in CEIC and is reported by Nanjing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Urbanization Rate.

Population: Fujian: Zhangzhou: Nanjing data was reported at 345.395 Person th in 2023. This records a decrease from the previous number of 350.882 Person th for 2022. Population: Fujian: Zhangzhou: Nanjing data is updated yearly, averaging 353.691 Person th from Dec 2004 (Median) to 2023, with 20 observations. The data reached an all-time high of 362.400 Person th in 2018 and a record low of 341.169 Person th in 2005. Population: Fujian: Zhangzhou: Nanjing 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.GJ: Population: County Level Region.

As of 2023, around 7.42 million people were living in the city Nanjing. Nanjing is the largest city of Jiangsu province and was designated as capital in several dynasties in Chinese history.

In 2019, around 67,600 babies were born in the city Nanjing, while 38,500 people passed away there. Nanjing is the largest city of Jiangsu province and was designated as capital in several dynasties in Chinese cities.

Univariate logistic regression for CHD risk factors.

Population: Jiangsu: Nanjing: Household Registration data was reported at 7,393.604 Person th in 2022. This records an increase from the previous number of 7,337.258 Person th for 2021. Population: Jiangsu: Nanjing: Household Registration data is updated yearly, averaging 6,297.700 Person th from Dec 1996 (Median) to 2022, with 27 observations. The data reached an all-time high of 7,393.604 Person th in 2022 and a record low of 5,254.300 Person th in 1996. Population: Jiangsu: Nanjing: Household Registration data remains active status in CEIC and is reported by Nanjing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City.

In 2024, around 9.54 million babies were born in China. The number of births has increased slightly from 9.02 million in the previous year, but is much lower than the 17.86 million births recorded in 2016. Demographic development in China In 2022, the Chinese population decreased for the first time in decades, and population decline is expected to accelerate in the upcoming years. To curb the negative effects of an aging population, the Chinese government decided in 2013 to gradually relax the so called one-child-policy, which had been in effect since 1979. From 2016 onwards, parents in China were allowed to have two children in general. However, as the recent figures of births per year reveal, this policy change had only short-term effects on the general birth rate: the number of births slightly increased from 2014 onwards, but then started to fell again in 2018. In 2024, China was the second most populous country in the world, overtaken by India that year. China’s aging population The Chinese society is aging rapidly and facing a serious demographic shift towards older age groups. The median age of China’s population has increased massively from about 18 years in 1970 to 37.5 years in 2020 and is projected to rise continuously until 2080. In 2020, approximately 17.9 percent of the Chinese were 60 years and older, a figure that is forecast to rise as high as 44 percent by 2060. This shift in demographic development will increase social and elderly support expenditure of the society as a whole. One measure for this social imbalance is the old-age dependency ratio, measuring the relationship between economic dependent older age groups and the working-age population. The old-age dependency ratio in China is expected to soar to 69 percent in 2060, implying that by then three working-age persons will have to support two elderly persons.

Multivariate logistic regression for CHD risk factors.

The UEBMI cohort in Nanjing during the ten-year period (2005–2014).

Population: Usual Residence: Birth Rate: Jiangsu: Nanjing data was reported at 5.680 ‰ in 2023. This records a decrease from the previous number of 6.010 ‰ for 2022. Population: Usual Residence: Birth Rate: Jiangsu: Nanjing data is updated yearly, averaging 6.250 ‰ from Dec 2018 (Median) to 2023, with 5 observations. The data reached an all-time high of 9.740 ‰ in 2018 and a record low of 5.680 ‰ in 2023. Population: Usual Residence: Birth Rate: Jiangsu: Nanjing data remains active status in CEIC and is reported by Nanjing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: Usual Residence: Natural Growth Rate.

The 2015 China Comprehensive Social Survey data (CGSS) was used to compare the differences between floating population and unfloating population, rural-urban floating population and urban floating population, and the propensity score matching method (PSM) was used to estimate the impact of mobility and different types of mobility on their social security participation. The study found that mobility has a negative impact on social security participation is significant. Compared with the unmobile people, the probability of migrant people participating in social security is lower, with a decrease of about 9%; the probability of participation in social security is lower than that of urban-urban floating population, with a decrease of about 12%.

Population: Jiangsu: Nanjing: Gaochun data was reported at 450.000 Person th in 2017. This records an increase from the previous number of 440.000 Person th for 2016. Population: Jiangsu: Nanjing: Gaochun data is updated yearly, averaging 427.000 Person th from Dec 2004 (Median) to 2017, with 13 observations. The data reached an all-time high of 450.000 Person th in 2017 and a record low of 420.000 Person th in 2006. Population: Jiangsu: Nanjing: Gaochun 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.GJ: Population: County Level Region.

In 2022, the gross domestic product (GDP) at current prices of the city of Nanjing in China reached around 1.69 trillion yuan. Nanjing is the provincial capital of Jiangsu province in Eastern China.

Abstract

This research was carried out in China between December 2011 and February 2013. Data was collected from 2,700 privately-owned and 148 state-owned firms.

The objective of Enterprise Surveys is to obtain feedback from businesses on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

Usually Enterprise Surveys focus only on private companies, but in China, a special sample of fully state-owned establishments was included as this is an important part of the economy. Data on 148 state-owned enterprises is provided separately from the data of 2,700 private sector firms. To maintain comparability of the China Enterprise Surveys to surveys conducted in other countries, only the dataset of privately sector firms should be used.

Geographic coverage

Twenty-five metro areas: Beijing (municipalities), Chengdu City, Dalian City, Dongguan City, Foshan City, Guangzhou City, Hangzhou City, Hefei City, Jinan City, Luoyang City, Nanjing City, Nantong City, Ningbo City, Qingdao City, Shanghai (municipalities), Shenyang City, Shenzhen City, Shijiazhuang City, Suzhou City, Tangshan City, Wenzhou City, Wuhan City, Wuxi City, Yantai City, Zhengzhou City.

Analysis unit

The primary sampling unit of the study is an establishment.The establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or universe of the study, is the non-agricultural economy of firms with at least 5 employees and positive amounts of private ownership. The non-agricultural economy comprises: all manufacturing sectors according to the group classification of ISIC Revision 3.1: (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for China ES was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the following way: the universe was stratified into 11 manufacturing industries and 7 services industries as defined in the sampling manual. Each manufacturing industry had a target of 150 interviews. Sample sizes were inflated by about 20% to account for potential non-response cases when requesting sensitive financial data and also because of likely attrition in future surveys that would affect the construction of a panel. Note that 100% government owned firms are categorized independently of their industrial classification. The 148 surveyed state-owned enterprises were categorized as a separate sector group to preserve the representativeness of other sector groupings for the private economy.

Size stratification was defined following the standardized definition for the rollout: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers. This seems to be an appropriate definition of the labor force since seasonal/casual/part-time employment is not a common practice, except in the sectors of construction and agriculture.

Regional stratification was defined in twenty-five metro areas: Beijing (municipalities), Chengdu City, Dalian City, Dongguan City, Foshan City, Guangzhou City, Hangzhou City, Hefei City, Jinan City, Luoyang City, Nanjing City, Nantong City, Ningbo City, Qingdao City, Shanghai (municipalities), Shenyang City, Shenzhen City, Shijiazhuang City, Suzhou City, Tangshan City, Wenzhou City, Wuhan City, Wuxi City, Yantai City, Zhengzhou City.

The sample frame was obtained by SunFaith from SinoTrust.

The enumerated establishments were then used as the frame for the selection of a sample with the aim of obtaining interviews at 3,000 establishments with five or more employees. The quality of the frame was assessed at the onset of the project through calls to a random subset of firms and local contractor knowledge. The sample frame was not immune from the typical problems found in establishment surveys: positive rates of non-eligibility, repetition, non-existent units, etc.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments are needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 31% (6,485 out of 20,616 establishments).

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available: - Services Questionnaire, - Manufacturing Questionnaire, - Screener Questionnaire.

The Services Questionnaire is administered to the establishments in the services sector. The Manufacturing Questionnaire is built upon the Services Questionnaire and adds specific questions relevant to manufacturing.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

The number of contacted establishments per realized interview was 7.24. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The number of rejections per contact was 0.55.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect the refusal to respond as a different option from don’t know. b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

The fertility rate of a country is the average number of children that women from that country will have throughout their reproductive years. In 1930, China's fertility rate was 5.5 children per woman, and this number then dropped to just under five over the next fifteen years, as China experienced a civil war and the Second World War. The fertility rate rose rather quickly after this to over 6.1 in 1955, before dropping again in the late 1950s, as Chairman Mao's 'Great Leap Forward' failed to industrialize the nation, and resulted in widespread famine that killed an estimated 45 million people. In the decade following this, China's fertility rate reached it's highest level in 1970, before the implementation of the two-child policy in the 1970s, and the one-child policy** in the 1980s, which radically changed the population structure. The fertility rate fell to an all time low in the early 2000s, where it was just 1.6 children per woman. However this number has increased to 1.7 today, and the two-child policy was reintroduced in 2016, replacing the one-child policy that had been effective for over 36 years.

Population: Jiangsu: Nanjing: Lishui data was reported at 440.000 Person th in 2017. This records an increase from the previous number of 430.000 Person th for 2016. Population: Jiangsu: Nanjing: Lishui data is updated yearly, averaging 413.700 Person th from Dec 2004 (Median) to 2017, with 13 observations. The data reached an all-time high of 440.000 Person th in 2017 and a record low of 400.000 Person th in 2005. Population: Jiangsu: Nanjing: Lishui 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.GJ: Population: County Level Region.