25 datasets found
  1. C

    China CN: GDP: % of Manufacturing: Medium and High Tech Industry

    • ceicdata.com
    Updated Oct 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2025). China CN: GDP: % of Manufacturing: Medium and High Tech Industry [Dataset]. https://www.ceicdata.com/en/china/gross-domestic-product-share-of-gdp/cn-gdp--of-manufacturing-medium-and-high-tech-industry
    Explore at:
    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2008 - Dec 1, 2019
    Area covered
    China
    Variables measured
    Gross Domestic Product
    Description

    China GDP: % of Manufacturing: Medium and High Tech Industry data was reported at 41.451 % in 2019. This stayed constant from the previous number of 41.451 % for 2018. China GDP: % of Manufacturing: Medium and High Tech Industry data is updated yearly, averaging 41.451 % from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 43.881 % in 2002 and a record low of 35.226 % in 1993. China GDP: % of Manufacturing: Medium and High Tech Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Gross Domestic Product: Share of GDP. The proportion of medium and high-tech industry value added in total value added of manufacturing; ; United Nations Industrial Development Organization (UNIDO), Competitive Industrial Performance (CIP) database; ;

  2. d

    Manufacturing Company Data | Chemicals & Manufacturing Executives in Asia |...

    • datarade.ai
    Updated Jan 1, 2018
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Success.ai (2018). Manufacturing Company Data | Chemicals & Manufacturing Executives in Asia | Verified Global Profiles from 700M+ Dataset | Best Price Guarantee [Dataset]. https://datarade.ai/data-products/manufacturing-company-data-chemicals-manufacturing-execut-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 1, 2018
    Dataset provided by
    Success.ai
    Area covered
    Asia, Korea (Republic of), State of, Malaysia, Cambodia, Israel, Lebanon, Bhutan, Turkey, Timor-Leste, Azerbaijan
    Description

    Success.ai’s Manufacturing Company Data for Chemicals & Manufacturing Executives in Asia provides a robust dataset tailored to businesses seeking to connect with decision-makers in the chemical and manufacturing industries across Asia. Covering executives, operations managers, and procurement leaders, this dataset offers verified email addresses, phone numbers, and detailed company insights.

    With access to over 700 million verified global profiles and data from 170 million professional datasets, Success.ai ensures your outreach, market research, and partnership development efforts are powered by accurate, continuously updated, and AI-validated information. Backed by our Best Price Guarantee, this solution is designed to help businesses thrive in Asia’s fast-evolving manufacturing sector.

    Why Choose Success.ai’s Manufacturing Company Data?

    1. Verified Contact Data for Precision Outreach

      • Access verified work emails, direct phone numbers, and LinkedIn profiles of manufacturing executives, chemical engineers, and operations leaders.
      • AI-driven validation ensures 99% accuracy, optimizing campaign efficiency and reducing communication errors.
    2. Comprehensive Coverage Across Asia’s Manufacturing Sector

      • Includes profiles of companies from manufacturing hubs such as China, India, Japan, South Korea, and Southeast Asia.
      • Gain insights into regional trends, supply chain dynamics, and market opportunities in Asia’s diverse manufacturing landscape.
    3. Continuously Updated Datasets

      • Real-time updates reflect changes in leadership, company expansions, and market activities.
      • Stay aligned with the fast-paced nature of the manufacturing and chemical industries to seize opportunities effectively.
    4. Ethical and Compliant

      • Adheres to GDPR, CCPA, and other global privacy regulations, ensuring responsible and lawful use of data.

    Data Highlights:

    • 700M+ Verified Global Profiles: Engage with executives, engineers, and operational leaders in Asia’s manufacturing and chemical industries.
    • 170M Professional Datasets: Access verified contact details and actionable insights for strategic outreach and business growth.
    • Company Insights: Gain visibility into company structures, production capacities, and market positioning.
    • Decision-Maker Contacts: Connect directly with CEOs, production managers, and procurement officers driving industry innovation.

    Key Features of the Dataset:

    1. Leadership Profiles in Chemicals & Manufacturing

      • Identify and connect with professionals responsible for operations, supply chain management, and research and development in the chemical and manufacturing sectors.
      • Target decision-makers overseeing material procurement, technology integration, and compliance.
    2. Advanced Filters for Precision Targeting

      • Filter companies by industry segment (chemical manufacturing, industrial machinery, consumer goods), geographic location, or revenue size.
      • Align campaigns to address specific industry challenges, such as sustainability, cost management, or operational efficiency.
    3. Firmographic Insights and Company Data

      • Access detailed firmographic data, including company hierarchies, operational scopes, and market presence.
      • Use these insights to identify high-value prospects and tailor your approach effectively.
    4. AI-Driven Enrichment

      • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and improve engagement outcomes with manufacturing professionals.

    Strategic Use Cases:

    1. Sales and Vendor Development

      • Present products, services, or equipment tailored to the needs of chemical manufacturers and industrial production companies.
      • Build relationships with procurement teams and operations managers seeking innovative solutions to streamline processes.
    2. Market Research and Competitive Analysis

      • Analyze trends in Asia’s manufacturing and chemical sectors to guide product innovation and strategic planning.
      • Benchmark against competitors to identify growth opportunities, market gaps, and emerging technologies.
    3. Supply Chain Optimization and Partnership Development

      • Engage with manufacturers seeking reliable suppliers, logistics partners, or co-manufacturers to support their operations.
      • Foster alliances that enhance efficiency, scalability, and quality in supply chain networks.
    4. Regulatory Compliance and Risk Mitigation

      • Connect with compliance officers and risk managers ensuring adherence to regional and global manufacturing standards.
      • Offer solutions that streamline compliance reporting, quality assurance, and risk management.

    Why Choose Success.ai?

    1. Best Price Guarantee

      • Access premium-quality manufacturing data at competitive prices, ensuring strong ROI for your marketing, sales, and partnership initiatives.
    2. Seamless I...

  3. Job Posting Data in China

    • kaggle.com
    zip
    Updated Sep 13, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Techsalerator (2024). Job Posting Data in China [Dataset]. https://www.kaggle.com/datasets/techsalerator/job-posting-data-in-china
    Explore at:
    zip(12790179 bytes)Available download formats
    Dataset updated
    Sep 13, 2024
    Authors
    Techsalerator
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Area covered
    China
    Description

    Techsalerator's Job Openings Data for China: A Comprehensive Resource for Employment Insights

    Techsalerator's Job Openings Data for China offers a detailed and essential resource for businesses, job seekers, and labor market analysts. This dataset provides an in-depth view of job openings across various industries in China, collating information from numerous sources such as company websites, job boards, and recruitment agencies.

    Key Data Fields

    • Job Posting Date: Captures the listing date for each job opening, keeping job seekers and HR professionals up-to-date with the latest opportunities and market trends.
    • Job Title: Details the specific role being advertised, helping categorize and filter job openings by industry and career focus.
    • Company Name: Lists the hiring organizations, enabling job seekers to focus their applications and helping businesses monitor competitors and industry trends.
    • Job Location: Specifies the geographic location of the job within China, aiding job seekers in finding regional opportunities and assisting employers in evaluating regional labor markets.
    • Job Description: Provides comprehensive information about the responsibilities, qualifications, and skills required, offering clarity to both candidates and recruiters.

    Top 5 Job Categories in China

    1. Information Technology (IT): A booming sector with high demand for software developers, data scientists, and cybersecurity experts due to the rapid growth of China's digital economy.
    2. Manufacturing: Significant demand for engineers, production managers, and skilled laborers in one of the world’s largest manufacturing hubs.
    3. Finance and Banking: High demand for financial analysts, investment managers, and compliance officers as China’s financial sector continues to expand.
    4. Healthcare: Roles for doctors, nurses, and healthcare administrators driven by the increasing demand for healthcare services due to population growth and aging.
    5. E-Commerce and Retail: Opportunities for logistics managers, supply chain analysts, and digital marketing specialists, reflecting China's leadership in the global e-commerce market.

    Top 5 Employers in China

    1. Alibaba Group: A leading e-commerce company with frequent openings in logistics, IT, marketing, and management roles.
    2. Tencent: A technology giant offering positions in software development, gaming, and cloud computing.
    3. China National Petroleum Corporation (CNPC): Major employer in the energy sector with roles in engineering, management, and technical services.
    4. China Construction Bank: One of the largest banks in China, regularly hiring in areas like banking operations, financial analysis, and customer service.
    5. Huawei Technologies: A global telecommunications company offering roles in R&D, engineering, sales, and project management.

    Accessing Techsalerator’s Data

    To access Techsalerator’s Job Openings Data for China, please contact info@techsalerator.com with your specific data requirements. We will provide a customized quote based on the data fields and records you need, with delivery available within 24 hours. Ongoing access options can also be discussed.

    Included Data Fields

    • Job Posting Date
    • Job Title
    • Company Name
    • Job Location
    • Job Description
    • Application Deadline
    • Job Type (Full-time, Part-time, Contract)
    • Salary Range
    • Required Qualifications
    • Contact Information

    Techsalerator’s dataset serves as a valuable tool for tracking employment trends and job opportunities in China, empowering businesses, job seekers, and analysts to make informed decisions.

  4. f

    Digital development of China’s manufacturing industry.

    • plos.figshare.com
    xls
    Updated May 30, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Qingwei Fu (2023). Digital development of China’s manufacturing industry. [Dataset]. http://doi.org/10.1371/journal.pone.0267299.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Qingwei Fu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China
    Description

    Digital development of China’s manufacturing industry.

  5. Enterprise Survey 2012 - China

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Mar 29, 2019
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    World Bank (2019). Enterprise Survey 2012 - China [Dataset]. http://catalog.ihsn.org/catalog/3280
    Explore at:
    Dataset updated
    Mar 29, 2019
    Dataset provided by
    World Bank Grouphttp://www.worldbank.org/
    Authors
    World Bank
    Time period covered
    2011 - 2013
    Area covered
    China
    Description

    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.

  6. New Zealand’s daily export trade with China

    • kaggle.com
    zip
    Updated Mar 15, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Marília Prata (2020). New Zealand’s daily export trade with China [Dataset]. https://www.kaggle.com/mpwolke/cusersmarildownloadsimportschinacsv
    Explore at:
    zip(2934 bytes)Available download formats
    Dataset updated
    Mar 15, 2020
    Authors
    Marília Prata
    Area covered
    New Zealand, China
    Description

    Context

    This Dataset presents New Zealand’s daily export trade with China from 27 January 2020. It compares 2020 values with those from previous years, to show the potential impacts of COVID-19 since its outbreak in late 2019.

    We advise caution in making decisions based on this experimental data. Please send any comments to overseastrade@stats.govt.nz.

    https://www.stats.govt.nz/experimental/provisional-indications-effects-of-coronavirus-outbreak-on-new-zealand-trade-with-china

    Content

    Imports from China The cumulative total value of imports from China alone in the past four weeks and one day to 29 February 2020 was about $775 million . This is about $169 million less than for the same period in 2019 .

    Daily trade for 1 February–29 February 2020 (published 10 March 2020) Imports from China (experimental, published 10 March 2020) CSV files include imports from China, including key exports of meat, seafood, dairy, and forestry products. The data is provisional and should be regarded as an early, indicative estimate of intentions to export only, subject to revision. These are not official statistics, but an effort to provide the latest available trade data at a time of heightened interest in trade with China. The data compares the four weeks and a day up to 29 February 2020 against previous years. This allows for an estimate to be made of what may have happened to exports, if they had followed typical patterns in the past four weeks.

    Acknowledgements

    https://www.stats.govt.nz/experimental/provisional-indications-effects-of-coronavirus-outbreak-on-new-zealand-trade-with-china Photo by Andy Li on Unsplash

    Inspiration

    The Global trade impact of the Coronavirus (COVID-19) Epidemic . “The spread of the new coronavirus is a public health crisis that could pose a serious risk to the macro economy through the halt in production activities, interruptions of people's movement and cut-off of supply chains” - Japanese Finance Minister Taro Aso. G20 gathering in Riyadh, Saudi Arabia, February 24, 2020. " Besides its worrying effects on human life, the novel strain of coronavirus (COVID-19) has the potential to significantly slowdown not only the Chinese economy but also the global economy. China has become the central manufacturing hub of many global business operations. Any disruption of China’s output is expected to have repercussions elsewhere through regional and global value chains. https://unctad.org/en/PublicationsLibrary/ditcinf2020d1.pdf

  7. C

    China CN: Manufacturing: Cost of Sales: ytd

    • ceicdata.com
    Updated Dec 15, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2024). China CN: Manufacturing: Cost of Sales: ytd [Dataset]. https://www.ceicdata.com/en/china/manufacturing/cn-manufacturing-cost-of-sales-ytd
    Explore at:
    Dataset updated
    Dec 15, 2024
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Apr 1, 2017 - Mar 1, 2018
    Area covered
    China
    Description

    China Manufacturing: Cost of Sales: Year to Date data was reported at 58,002.580 RMB bn in Sep 2018. This records an increase from the previous number of 51,784.900 RMB bn for Aug 2018. China Manufacturing: Cost of Sales: Year to Date data is updated monthly, averaging 42,510.490 RMB bn from Dec 2016 (Median) to Sep 2018, with 22 observations. The data reached an all-time high of 89,068.330 RMB bn in Dec 2017 and a record low of 11,831.650 RMB bn in Feb 2018. China Manufacturing: Cost of Sales: Year to Date data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Industrial Sector – Table CN.MFG: Manufacturing.

  8. S

    Annual winter wheat mapping datasets and dynamics in China from 2001 to 2020...

    • scidb.cn
    Updated Dec 5, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Jie Dong; Zhouye Pang; Yangyang Fu; Qiongyan Peng; Xiangqian Li; Wenping Yuan (2023). Annual winter wheat mapping datasets and dynamics in China from 2001 to 2020 [Dataset]. http://doi.org/10.57760/sciencedb.13901
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 5, 2023
    Dataset provided by
    Science Data Bank
    Authors
    Jie Dong; Zhouye Pang; Yangyang Fu; Qiongyan Peng; Xiangqian Li; Wenping Yuan
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    China
    Description

    As one of the largest producers of winter wheat worldwide, China contributes more than 19 % of the global production of winter wheat and playing a vital role in maintaining sustainable wheat production. Therefore, mapping the spatial distribution of winter wheat in China over long time scale precisely is of great importance for ensuring food security and investigating the spatiotemporal pattern of winter wheat at a national scale. Nevertheless, existing high resolution remote sensing datasets which can provide continuous observation for 20 years suffer from data gaps caused by cloud cover, making it difficult to map winter wheat area over long time scale. In this study, we used a phenology-based method to identify winter wheat area by integrated three key growing features of winter wheat into one variable for calculating the planting probability of winter wheat, which enlarged phenological differences between winter wheat and non-winter wheat fields. On this basis, we produced a long-term winter wheat mapping dataset at 30 m spatial resolution in China from 2001 to 2020 using the fusion dataset. Validations based on a total of 32,957 field survey samples displayed high accuracy, with the user’s, producer’s, and overall accuracies of 91.17%, 90.92%, and 91.6% in China, respectively. Furthermore, the identified winter wheat area aggregated to the municipal- and county-level exhibited good correlations with the agricultural statistical data. Based on this dataset, we found that the winter wheat planting condition in China exhibited a high frequency of continuous planting, with 54.45% of pixels having continuously planted winter wheat for over 10 years. During the period of 2001–2020, approximately 40% of the winter wheat pixels showed significantly increasing trends, which mainly concentrated in the major production area for winter wheat, such as Shandong, Henan, and Anhui province. Conversely, less than a quarter of winter wheat pixels showed significantly decreasing trends, which distributed in central and western provinces in China.

  9. Technology level heterogeneity analysis.

    • plos.figshare.com
    xls
    Updated Jun 9, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Qingwei Fu (2023). Technology level heterogeneity analysis. [Dataset]. http://doi.org/10.1371/journal.pone.0267299.t007
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Qingwei Fu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Technology level heterogeneity analysis.

  10. T

    MANUFACTURING PMI by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jan 2, 2014
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2014). MANUFACTURING PMI by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/manufacturing-pmi
    Explore at:
    xml, json, csv, excelAvailable download formats
    Dataset updated
    Jan 2, 2014
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    World
    Description

    This dataset provides values for MANUFACTURING PMI reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  11. f

    The dataset provides data for the simulation process outlined in this study,...

    • figshare.com
    • plos.figshare.com
    xlsx
    Updated Sep 3, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Tao Jin; Zhihao Li (2025). The dataset provides data for the simulation process outlined in this study, as well as for the cross-country comparative analysis. All data herein are computed based on the World Input-Output Database (WIOD). [Dataset]. http://doi.org/10.1371/journal.pone.0330908.s002
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Sep 3, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Tao Jin; Zhihao Li
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The dataset provides data for the simulation process outlined in this study, as well as for the cross-country comparative analysis. All data herein are computed based on the World Input-Output Database (WIOD).

  12. T

    China Exports By Category

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Apr 22, 2017
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    TRADING ECONOMICS (2017). China Exports By Category [Dataset]. https://tradingeconomics.com/china/exports-by-category
    Explore at:
    json, csv, excel, xmlAvailable download formats
    Dataset updated
    Apr 22, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1990 - Dec 31, 2025
    Area covered
    China
    Description

    China's total Exports in 2024 were valued at US$3.58 Trillion, according to the United Nations COMTRADE database on international trade. China's main export partners were: the United States, Hong Kong and Vietnam. The top three export commodities were: Electrical, electronic equipment; Machinery, nuclear reactors, boilers and Vehicles other than railway, tramway. Total Imports were valued at US$2.59 Trillion. In 2024, China had a trade surplus of US$991.41 Billion.

  13. C

    China CN: Steel: Production: Quality Section

    • ceicdata.com
    Updated Jan 30, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2025). China CN: Steel: Production: Quality Section [Dataset]. https://www.ceicdata.com/en/china/steel-production-annual/cn-steel-production-quality-section
    Explore at:
    Dataset updated
    Jan 30, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1995 - Dec 1, 2003
    Area covered
    China
    Variables measured
    Industrial Production
    Description

    China Steel: Production: Quality Section data was reported at 14,074.900 Ton th in 2003. This records an increase from the previous number of 11,466.400 Ton th for 2002. China Steel: Production: Quality Section data is updated yearly, averaging 6,730.200 Ton th from Dec 1995 (Median) to 2003, with 9 observations. The data reached an all-time high of 14,074.900 Ton th in 2003 and a record low of 5,856.900 Ton th in 1997. China Steel: Production: Quality Section data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Metal and Steel Sector – Table CN.WAD: Steel Production: Annual.

  14. C

    China CN: Other Manufacturing: YoY: Inventory: Finished Product

    • ceicdata.com
    Updated Oct 15, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2025). China CN: Other Manufacturing: YoY: Inventory: Finished Product [Dataset]. https://www.ceicdata.com/en/china/other-manufacturing/cn-other-manufacturing-yoy-inventory-finished-product
    Explore at:
    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Apr 1, 2017 - Mar 1, 2018
    Area covered
    China
    Variables measured
    Economic Activity
    Description

    China Other Manufacturing: YoY: Inventory: Finished Product data was reported at 6.000 % in May 2018. This records an increase from the previous number of 5.800 % for Apr 2018. China Other Manufacturing: YoY: Inventory: Finished Product data is updated monthly, averaging 5.800 % from Jan 2012 (Median) to May 2018, with 77 observations. The data reached an all-time high of 24.187 % in Jul 2014 and a record low of -8.473 % in Nov 2012. China Other Manufacturing: YoY: Inventory: Finished Product data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s China – Table CN.BIM: Other Manufacturing.

  15. C

    China CN: Furniture: Gross Industrial Output

    • ceicdata.com
    Updated Mar 24, 2018
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2018). China CN: Furniture: Gross Industrial Output [Dataset]. https://www.ceicdata.com/en/china/furniture-manufacturing/cn-furniture-gross-industrial-output
    Explore at:
    Dataset updated
    Mar 24, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2000 - Dec 1, 2011
    Area covered
    China
    Variables measured
    Economic Activity
    Description

    China Furniture: Gross Industrial Output data was reported at 508,984.342 RMB mn in 2011. This records an increase from the previous number of 441,481.000 RMB mn for 2010. China Furniture: Gross Industrial Output data is updated yearly, averaging 31,929.000 RMB mn from Dec 1986 (Median) to 2011, with 26 observations. The data reached an all-time high of 508,984.342 RMB mn in 2011 and a record low of 5,100.000 RMB mn in 1986. China Furniture: Gross Industrial Output data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s China – Table CN.BHI: Furniture Manufacturing.

  16. C

    China Producer Price Index: Machine Manufacturing

    • ceicdata.com
    Updated Oct 15, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2025). China Producer Price Index: Machine Manufacturing [Dataset]. https://www.ceicdata.com/en/china/producer-price-index/producer-price-index-machine-manufacturing
    Explore at:
    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2013 - Dec 1, 2024
    Area covered
    China
    Variables measured
    Producer Prices
    Description

    China Producer Price Index: Machine Manufacturing data was reported at 97.900 Prev Year=100 in 2024. This records an increase from the previous number of 97.500 Prev Year=100 for 2023. China Producer Price Index: Machine Manufacturing data is updated yearly, averaging 99.500 Prev Year=100 from Dec 1980 (Median) to 2024, with 45 observations. The data reached an all-time high of 121.200 Prev Year=100 in 1989 and a record low of 96.170 Prev Year=100 in 2002. China Producer Price Index: Machine Manufacturing data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Inflation – Table CN.IE: Producer Price Index.

  17. C

    China Average Wage: Manufacturing

    • ceicdata.com
    Updated Oct 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2025). China Average Wage: Manufacturing [Dataset]. https://www.ceicdata.com/en/china/average-wage-by-industry/average-wage-manufacturing
    Explore at:
    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2013 - Dec 1, 2017
    Area covered
    China
    Description

    China Average Wage: Manufacturing data was reported at 58,049.000 RMB in 2017. This records an increase from the previous number of 54,338.000 RMB for 2016. China Average Wage: Manufacturing data is updated yearly, averaging 50,684.000 RMB from Dec 2013 (Median) to 2017, with 5 observations. The data reached an all-time high of 58,049.000 RMB in 2017 and a record low of 42,911.000 RMB in 2013. China Average Wage: Manufacturing data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Labour Market – Table CN.GC: Average Wage: by Industry.

  18. C

    China CN: Energy Production: Electricity: Hydro

    • ceicdata.com
    Updated Mar 26, 2018
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2018). China CN: Energy Production: Electricity: Hydro [Dataset]. https://www.ceicdata.com/en/china/energy-production
    Explore at:
    Dataset updated
    Mar 26, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Nov 1, 2023 - Dec 1, 2024
    Area covered
    China
    Variables measured
    Industrial Production
    Description

    CN: Energy Production: Electricity: Hydro data was reported at 78.130 kWh bn in Mar 2025. This records a decrease from the previous number of 82.720 kWh bn for Dec 2024. CN: Energy Production: Electricity: Hydro data is updated monthly, averaging 25.343 kWh bn from Jan 1986 (Median) to Mar 2025, with 451 observations. The data reached an all-time high of 166.450 kWh bn in Jul 2024 and a record low of 4.410 kWh bn in Feb 1987. CN: Energy Production: Electricity: Hydro data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s China – Table CN.RBA: Energy Production. [COVID-19-IMPACT]

  19. C

    China PMI: New Orders

    • ceicdata.com
    Updated Oct 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2025). China PMI: New Orders [Dataset]. https://www.ceicdata.com/en/china/purchasing-managers-index-manufacturing/pmi-new-orders
    Explore at:
    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2024 - Feb 1, 2025
    Area covered
    China
    Variables measured
    Purchasing Manager Index
    Description

    China PMI: New Orders data was reported at 49.200 % in Nov 2025. This records an increase from the previous number of 48.800 % for Oct 2025. China PMI: New Orders data is updated monthly, averaging 50.100 % from Jan 2005 (Median) to Nov 2025, with 251 observations. The data reached an all-time high of 65.100 % in Apr 2007 and a record low of 29.300 % in Feb 2020. China PMI: New Orders data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OP: Purchasing Managers' Index: Manufacturing.

  20. C

    China Industrial Production: Copper Processing Product

    • ceicdata.com
    Updated Oct 15, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2025). China Industrial Production: Copper Processing Product [Dataset]. https://www.ceicdata.com/en/china/industrial-production/industrial-production-copper-processing-product
    Explore at:
    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Nov 1, 2023 - Dec 1, 2024
    Area covered
    China
    Variables measured
    Industrial Production
    Description

    China Industrial Production: Copper Processing Product data was reported at 2,125.000 Ton th in Mar 2025. This records a decrease from the previous number of 2,273.000 Ton th for Dec 2024. China Industrial Production: Copper Processing Product data is updated monthly, averaging 549.000 Ton th from Jan 1989 (Median) to Mar 2025, with 387 observations. The data reached an all-time high of 2,293.000 Ton th in Dec 2019 and a record low of 22.000 Ton th in Dec 1989. China Industrial Production: Copper Processing Product data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s China – Table CN.BA: Industrial Production.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
CEICdata.com (2025). China CN: GDP: % of Manufacturing: Medium and High Tech Industry [Dataset]. https://www.ceicdata.com/en/china/gross-domestic-product-share-of-gdp/cn-gdp--of-manufacturing-medium-and-high-tech-industry

China CN: GDP: % of Manufacturing: Medium and High Tech Industry

Explore at:
Dataset updated
Oct 15, 2025
Dataset provided by
CEICdata.com
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Dec 1, 2008 - Dec 1, 2019
Area covered
China
Variables measured
Gross Domestic Product
Description

China GDP: % of Manufacturing: Medium and High Tech Industry data was reported at 41.451 % in 2019. This stayed constant from the previous number of 41.451 % for 2018. China GDP: % of Manufacturing: Medium and High Tech Industry data is updated yearly, averaging 41.451 % from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 43.881 % in 2002 and a record low of 35.226 % in 1993. China GDP: % of Manufacturing: Medium and High Tech Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Gross Domestic Product: Share of GDP. The proportion of medium and high-tech industry value added in total value added of manufacturing; ; United Nations Industrial Development Organization (UNIDO), Competitive Industrial Performance (CIP) database; ;

Search
Clear search
Close search
Google apps
Main menu