The statistic shows the population of Hangzhou in China from 1980 to 2010, with forecasts up until 2035. In 2010, the population of Hangzhou had amounted to about 5.76 million inhabitants and was forecasted to grow up to almost 9.7 million by 2035.

Population: Census: Zhejiang: Hangzhou data was reported at 11,936.010 Person th in 12-01-2020. This records an increase from the previous number of 8,700.400 Person th for 12-01-2010. Population: Census: Zhejiang: Hangzhou data is updated decadal, averaging 8,700.400 Person th from Dec 2000 (Median) to 12-01-2020, with 3 observations. The data reached an all-time high of 11,936.010 Person th in 12-01-2020 and a record low of 6,878.722 Person th in 12-01-2000. Population: Census: Zhejiang: Hangzhou data remains active status in CEIC and is reported by Hangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City: By Census.

Population: Usual Residence: Birth Rate: Zhejiang: Hangzhou data was reported at 7.500 ‰ in 2024. This records an increase from the previous number of 6.700 ‰ for 2023. Population: Usual Residence: Birth Rate: Zhejiang: Hangzhou data is updated yearly, averaging 9.090 ‰ from Dec 2010 (Median) to 2024, with 15 observations. The data reached an all-time high of 12.500 ‰ in 2017 and a record low of 6.700 ‰ in 2023. Population: Usual Residence: Birth Rate: Zhejiang: Hangzhou data remains active status in CEIC and is reported by Hangzhou 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.

Population: Zhejiang: Hangzhou: Household Registration data was reported at 8,757.000 Person th in 2024. This records an increase from the previous number of 8,606.036 Person th for 2023. Population: Zhejiang: Hangzhou: Household Registration data is updated yearly, averaging 6,891.200 Person th from Dec 1996 (Median) to 2024, with 29 observations. The data reached an all-time high of 8,757.000 Person th in 2024 and a record low of 6,032.200 Person th in 1996. Population: Zhejiang: Hangzhou: Household Registration data remains active status in CEIC and is reported by Hangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City.

Population: Usual Residence: Natural Growth Rate: Zhejiang: Hangzhou data was reported at 2.300 ‰ in 2024. This records an increase from the previous number of 1.300 ‰ for 2023. Population: Usual Residence: Natural Growth Rate: Zhejiang: Hangzhou data is updated yearly, averaging 4.120 ‰ from Dec 2010 (Median) to 2024, with 15 observations. The data reached an all-time high of 7.400 ‰ in 2017 and a record low of 1.300 ‰ in 2023. Population: Usual Residence: Natural Growth Rate: Zhejiang: Hangzhou data remains active status in CEIC and is reported by Hangzhou 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.

Population: Zhejiang: Hangzhou: Usual Residence data was reported at 12,624.000 Person th in 2024. This records an increase from the previous number of 12,522.000 Person th for 2023. Population: Zhejiang: Hangzhou: Usual Residence data is updated yearly, averaging 9,969.500 Person th from Dec 1999 (Median) to 2024, with 22 observations. The data reached an all-time high of 12,624.000 Person th in 2024 and a record low of 6,157.500 Person th in 1999. Population: Zhejiang: Hangzhou: Usual Residence data remains active status in CEIC and is reported by Hangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City.

As of January 2024, Hangzhou in China had the highest annual metropolitan population growth rate among megacities in the Asia-Pacific region, at about **** percent. In contrast, all three Japanese megacities Tokyo, Nagoya, and Osaka had the lowest annual population growth rates across APAC, with Osaka's population shrinking by **** percent as of January 2024.

Population: Usual Residence: Urbanization Rate: Zhejiang: Hangzhou data was reported at 84.800 % in 2024. This records an increase from the previous number of 84.200 % for 2023. Population: Usual Residence: Urbanization Rate: Zhejiang: Hangzhou data is updated yearly, averaging 79.300 % from Dec 2010 (Median) to 2024, with 15 observations. The data reached an all-time high of 84.800 % in 2024 and a record low of 73.300 % in 2010. Population: Usual Residence: Urbanization Rate: Zhejiang: Hangzhou data remains active status in CEIC and is reported by Hangzhou 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: Zhejiang: Hangzhou: Linan data was reported at 542.990 Person th in 2022. This records an increase from the previous number of 542.175 Person th for 2021. Population: Zhejiang: Hangzhou: Linan data is updated yearly, averaging 527.000 Person th from Dec 2004 (Median) to 2022, with 19 observations. The data reached an all-time high of 542.990 Person th in 2022 and a record low of 519.000 Person th in 2004. Population: Zhejiang: Hangzhou: Linan 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.

Hangzhou. name, office head of government, Mayor, image, Area, date founded, Elevation, Country, administrative division, continent, latitude, waterbody, longitude, Website, population, Demonym

Population: Non-natural Change: Zhejiang: Hangzhou data was reported at 129.867 Person th in 2023. This records an increase from the previous number of 101.340 Person th for 2022. Population: Non-natural Change: Zhejiang: Hangzhou data is updated yearly, averaging 57.511 Person th from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 183.686 Person th in 2021 and a record low of 29.036 Person th in 2013. Population: Non-natural Change: Zhejiang: Hangzhou data remains active status in CEIC and is reported by Hangzhou 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: Zhejiang: Hangzhou: Fuyang data was reported at 701.432 Person th in 2023. This records an increase from the previous number of 697.888 Person th for 2022. Population: Zhejiang: Hangzhou: Fuyang data is updated yearly, averaging 662.300 Person th from Dec 2004 (Median) to 2023, with 20 observations. The data reached an all-time high of 701.432 Person th in 2023 and a record low of 628.000 Person th in 2004. Population: Zhejiang: Hangzhou: Fuyang 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.

Based on the land economic density of 892 town units, the spatial pattern of the land economic density in Zhejiang Province is analyzed using the coefficient of variation, spatial classification, and spatial correlation methods, and the influencing factors are analyzed using a spatial regression model. The results are as follows: (1) The coefficients of variation were 2.6 and 3.1 in 2014 and 2019, respectively, indicating that the degree of imbalance of the town’s industrial economy at the county level increased. (2) The distribution of the high-level agglomeration areas was characterized by one core area and two sub-core areas. The main core area was located at the junction of Hangzhou City, Shaoxing City, and Jiaxing City, and the two sub-core areas were located in Yuyao City and the main urban area of Ningbo City. In addition, several small-scale agglomeration areas composed of medium and high-level units were distributed in Wenzhou City. (3) The high-value agglomeration and low-value agglomeration distribution in the spatial correlation patterns was identified using the spatial auto-correlation method. The hot spots and sub-hot spots were distributed in Northern Zhejiang, and the cold spots formed a large-scale agglomeration in Quzhou City, Lishui City, Taizhou City, and several other cities in Southern Zhejiang. (4) Compared with the county scale, the spatial scope of the high-level areas in Northern Zhejiang shrunk significantly at the township scale, and the high-level agglomeration areas along the southeast coast changed into a cluster of several townships. (5) According to the geographically weighted regression (GWR) model, the importance of influencing factors is as follows: population density > regional area > industrial output value per capita > total population > proportion of secondary and tertiary personnel > total employees.

Population: Zhejiang: Hangzhou: Jiande data was reported at 502.521 Person th in 2023. This records a decrease from the previous number of 505.478 Person th for 2022. Population: Zhejiang: Hangzhou: Jiande data is updated yearly, averaging 510.000 Person th from Dec 2004 (Median) to 2023, with 20 observations. The data reached an all-time high of 513.400 Person th in 2009 and a record low of 502.521 Person th in 2023. Population: Zhejiang: Hangzhou: Jiande 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.

Background13-valent pneumococcal polysaccharide conjugate vaccine (PCV13) has been introduced in Hangzhou since 2017, whereas its current immunization state in children is not clear. Therefore, this study aims to describe the PCV13 vaccination distribution among children born in Hangzhou from 2017 to 2021 to provide data for reducing vaccination differences among different populations.MethodsDescriptive epidemiology was used for data analysis and PCV13 vaccination related information of children was collected from children vaccination management system of Zhejiang Province (ZJCVMS).ResultsAmong the 649,949 children born in Hangzhou from 2017 to 2021, 169,230 were vaccinated with an average full course vaccination rate of 26.0%. The full course vaccination rates in 5 years were different (P = 0.000) with an increasing trend (Pfortrend < 0.01). The first dose vaccination rates were different in 5 years (P = 0.000) with an increasing trend (Pfortrend < 0.01). The distribution of age when first dose PCV13 was administered varied, most people at 2 months and least people at 5 months. The full course vaccination rate varied by areas, highest in central urban areas and lowest in remote areas respectively (all P-value < 0.05). Overall, the full course vaccination rate of PCV13 was higher in the registered residence population than the non-registered residence population, which was 136,693 (31.4%) and 32,537 (15.1%) respectively (P = 0.000). The full course vaccination rates were the same between men and women (P = 0.502), which was 87,844 for men (26.0%) and 81,386 for women (26.1%).ConclusionAlthough the number of people who received PCV13 full course vaccination and received the first dose vaccination showed yearly increasing trends in Hangzhou, the full course vaccination rate for the whole population was relatively low. In addition, the PCV13 vaccination rates also differed by geography and household registration status. Measures such as expanding vaccination publicity or including national immunization should be taken to increase vaccination rates and reduce the differences in vaccination among groups with different characteristics.

This set of qualitative and quantitative (household survey) data was collected in Tianjin, China, between January 2018 and December 2019. The project aims to examine current urbanisation processes in China from the perspective of the neighbourhood, and therefore to better understand the processes of migration, social and spatial differentiation, and their implications for emerging intra- and inter-neighbourhood inequalities and access to public services. Group interviews, focus group discussions, and household survey were conducted in three cities located in different regions of China to understand the recent urban development and transformation. The household survey aims to establish the socio-economic and demographic profiles and changes of neighbourhood population, housing tenure and choice, housing costs, living conditions, and asset and property ownership. It seeks to understand the basis of residential decision making and everyday lives of residents in different types of city neighbourhoods, especially access to and use of key public services - schools, healthcare, and employment support and training. It also covers social networks and social integration. The interviews and focus groups help to understand the organisation, management and administration of urban neighbourhoods and the provision of local public services.

List of factors influencing the land economic density.

Population: Zhejiang: Hangzhou: Tonglu data was reported at 418.326 Person th in 2023. This records a decrease from the previous number of 419.276 Person th for 2022. Population: Zhejiang: Hangzhou: Tonglu data is updated yearly, averaging 406.950 Person th from Dec 2004 (Median) to 2023, with 20 observations. The data reached an all-time high of 419.276 Person th in 2022 and a record low of 394.000 Person th in 2004. Population: Zhejiang: Hangzhou: Tonglu 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.

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.

Population: Zhejiang: Hangzhou: Chunan data was reported at 446.881 Person th in 2023. This records a decrease from the previous number of 450.242 Person th for 2022. Population: Zhejiang: Hangzhou: Chunan data is updated yearly, averaging 455.000 Person th from Dec 2004 (Median) to 2023, with 20 observations. The data reached an all-time high of 460.769 Person th in 2017 and a record low of 446.881 Person th in 2023. Population: Zhejiang: Hangzhou: Chunan 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.