The growth of the manufacturing industry is the engine of rapid economic growth in developing regions. Characterizing the geographical distribution of manufacturing firms is critically important for scientists and policymakers. However, data on the manufacturing industry used in previous studies either have a low spatial resolution (or fuzzy classification) or high-resolution information is lacking. Here, we propose a map point-of-interest classification method based on machine learning technology and build a dataset of the distribution of Chinese manufacturing firms called the Gridded Manufacturing Dataset. This dataset includes the number and type of manufacturing firms at a 0.01° latitude by 0.01° longitude scale. It includes all manufacturing firms (classified into seven categories) in China in 2015 (4.40 million) and 2019 (6.01 million). This dataset can be used to characterize temporal and spatial patterns in the distribution of manufacturing firms as well as reveal the mechanisms underlying the development of the manufacturing industry and changes in regional economic policies.

Industrial Production in China increased 4.90 percent in October of 2025 over the same month in the previous year. This dataset provides - China Industrial Production - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Description

This dataset contains contact details of battery manufacturers in China, including company names, websites, emails, LinkedIn profiles, and phone numbers. It has been compiled to support research, networking, and outreach activities in the energy storage and battery industry.

The dataset provides a starting point for anyone looking to:

• Explore the Chinese battery manufacturing landscape
• Identify potential partners, suppliers, or clients
• Conduct market research on renewable energy and storage solutions
• Build outreach pipelines for sales or collaborations

Data Fields

• id → Unique identifier for each entry
• contact_number → Company phone numbers (varied formats)
• linkedin → LinkedIn company or personal profile
• company_name → Name of the company
• website → Official company website
• emails → One or multiple email addresses (in some cases missing or unstructured)

Data Preprocessing & Cleaning

The dataset is raw and may require preprocessing before use:

• Standardize phone numbers into a consistent format
• Extract multiple emails into separate rows or structured lists
• Clean missing values (some companies may not have all fields filled)
• Normalize company names (some in English, some in Chinese)
• Verify websites/LinkedIn links for accessibility and accuracy

Potential Uses

• Business development & lead generation
• Market mapping of Chinese battery manufacturers
• Supplier discovery for EV, solar, and renewable energy projects
• Academic research on China’s role in the global battery supply chain

This dataset is a useful resource but will benefit from data cleaning and enrichment for maximum accuracy and usability.

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.

Wages in Manufacturing in China increased to 103932 CNY/Year in 2023 from 97528 CNY/Year in 2022. This dataset provides - China Average Yearly Wages in Manufacturing - actual values, historical data, forecast, chart, statistics, economic calendar and news.

How the Chinese Economy Works

The Chinese economy is the second largest in the world, after the United States. It is a mixed economy, with elements of both capitalism and socialism. The government plays a significant role in the economy, but there is also a growing private sector.

Agriculture

Agriculture is a major sector of the Chinese economy, employing about 25% of the workforce. China is a major producer of rice, wheat, corn, soybeans, and cotton. The country is also a leading producer of fruits, vegetables, and livestock.

Manufacturing

Manufacturing is the largest sector of the Chinese economy, accounting for about 40% of GDP. China is a major producer of a wide range of goods, including electronics, textiles, apparel, and machinery. The country is also a major exporter of manufactured goods.

Services

Services are the third largest sector of the Chinese economy, accounting for about 45% of GDP. This sector includes a wide range of activities, such as finance, transportation, real estate, and tourism.

Government

The government plays a significant role in the Chinese economy. The government owns and operates many state-owned enterprises, which are important players in the economy. The government also regulates the economy through a variety of policies, such as tariffs, subsidies, and taxes.

Private Sector

The private sector is growing in importance in the Chinese economy. Private companies are playing an increasing role in manufacturing, services, and other sectors. The government is encouraging the growth of the private sector by reducing regulations and providing support for small businesses.

Challenges

The Chinese economy faces a number of challenges, including:

Inequality: The gap between the rich and the poor is growing in China. Environmental degradation: China is facing serious environmental problems, such as air pollution and water pollution. Political stability: The Chinese government is facing increasing challenges to its authority. Outlook

The Chinese economy is expected to continue to grow in the coming years. However, the growth is likely to slow down as the country faces the challenges mentioned above.

Conclusion

The Chinese economy is a complex and dynamic system. It is a mix of capitalism and socialism, with a significant role for the government. The economy is growing rapidly, but it also faces a number of challenges.

As the world's second-largest economy, information about China is in high demand. In addition, its prospect has increased due to the opening of A-share markets to foreign investors. China is different from western economies when it comes to the generation of data, as Chinese consumers do not generate data through traditional providers such as Google. Instead, this data is generated by Chinese proxies.

The power of SpaceKnow Nowcasting data lies in its standardization. You can safely compare all our Chinese data with each other or to other datasets for other countries. SpaceKnow obtains data from radar satellites which consistently deliver data down to earth. SpaceKnow monitors over 10,000 locations in China.

About data: SpaceKnow data has a history since January 2017 SpaceKnow data is updated on a weekly and daily basis SpaceKnow data provides the latest data point to customers instantly SpaceKnow data is transparent about locations from which it collects data SpaceKnow data is not affected by weather conditions

Available datasets: China Country Nowcasting Weekly updated change data Indices focused on the macroeconomic sector: manufacturing, mining with traditional benchmark predictions Indices focused on sectors: mining, automotive, chemical, transport, etc. Indices focused on regional and country pollution Industry indices provide information in z-score and percentages for low, normal and high activity Pollution indices provide information in mol/m2 and parts per billion for methane

China Nowcasting Summary:

China Logistic Centres Daily updated data aggregated by country and segregated by the 17 Chinese provinces Dataset provides three types of indices with different information: A level index that captures the long-term trends in the level of domestic trade A change index that captures the total flow of activity entering and exiting the monitored locations An activity index that captures different types of activity across time Indices are level in squared meters, change in z-score and activity in percentage

China Retail Indices Daily updated level data in squared meters Indices capture retail-related activity across China over parking areas that belong to shopping centres and metro stations Indices estimate the current state of the retail market in China Retail Parking Retail Metro Parking

China Automotive Companies [Released] Daily updated level data in squared meters Indices cover the production of assembled cars, movement at employee parking areas Covered companies: SAIC, BBAC, Changan, Dongfeng, Geely, GAC Group, Tesla Shanghai and more

China Coal [Coming Soon] Daily updated level data in squared meters Focus on mines, storage, processing and distribution centres Indices cover country and also region levels for Xinjiang, Shaanxi, Shanxi, Inner Mongolia China Truck Stops [Coming Soon]

Key information about China Industrial Production Index Growth

• China Industrial production rose 4.9 % YoY in Oct 2025, following an increase of 6.5 % YoY in the previous month.
• China Industrial production index growth rate YoY data is updated monthly, available from Jan 1995 to Oct 2025, with an average rate of 7.3 %.
• The data reached an all-time high of 23.2 % in Feb 2004 and a record low of -2.9 % in Apr 2022.

The National Bureau of Statistics provides monthly Industrial Production Index Growth. Industrial Production Index Growth reflects the annual increase of total value added by all industrial sectors in current prices, indicating value changes.

Business Confidence in China increased to 49.20 points in November from 49 points in October of 2025. This dataset provides - China Business Confidence - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Digital development of China’s manufacturing industry.

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; ;

Data was collected through an online self-administered survey targeting senior and middle management personnel from manufacturing enterprises in Mainland China. The unit of analysis is the organization. A non-probability convenience sampling technique was employed to gather data from 224 respondents across various sectors of the Chinese manufacturing industry. The dataset focuses on the impact of internal incentive mechanisms on supply chain reconfiguration, with employee incentive acceptance as a mediating factor.

Note: Updates to this data product are discontinued. The China agricultural and economic database is a collection of agricultural-related data from official statistical publications of the People's Republic of China. Analysts and policy professionals around the world need information about the rapidly changing Chinese economy, but statistics are often published only in China and sometimes only in Chinese-language publications. This product assembles a wide variety of data items covering agricultural production, inputs, prices, food consumption, output of industrial products relevant to the agricultural sector, and macroeconomic data.

Description

This dataset provides monthly economic indicators examining the relationship between US protectionist trade policies and Chinese economic growth from May 2022 to May 2025. The dataset can be used for academic research, statistical analysis, and educational purposes in international economics and trade policy studies.

Context

The dataset captures the economic dynamics during a period of heightened trade tensions between the United States and China. It includes comprehensive indicators of US protectionist measures and their potential impact on various dimensions of Chinese economic performance.

Dataset Structure

Time Period: May 2022 - May 2025 Frequency: Monthly Total Observations: 1127 Total Variables: 14

Column Descriptions

Date

• Type: Categorical (YYYY-MM format)
• Description: Month and year of observation

US Protectionism Indicators

US_Tariff_Index

• Type: Continuous
• Range: 100-120
• Description: Tariff rate index where 100 represents the baseline. Higher values indicate increased protectionist measures.

US_Trade_Restrictions

• Type: Discrete
• Range: 5-15
• Description: Number of new trade restrictions implemented per month, including tariffs, quotas, and non-tariff barriers.

US_AntiDumping_Cases

• Type: Discrete
• Range: 0-12
• Description: Number of anti-dumping cases filed against Chinese products per month.

US_Trade_Policy_Uncertainty

-Type: Continuous - Range: 90-160 - Description: Index measuring uncertainty in trade policy (0-200 scale). Higher values indicate greater uncertainty.

Chinese Growth Indicators

China_GDP_Growth_YoY

• Type: Continuous
• Unit: Percentage (%)
• Range: 3.5-5.5%
• Description: Year-over-year GDP growth rate for China.

China_Industrial_Production_YoY

• Type: Continuous
• Unit: Percentage (%)
• Range: 2.5-5.0%
• Description: Year-over-year change in industrial production output.

China_Exports_Growth_YoY

• Type: Continuous
• Unit: Percentage (%)
• Range: 0-15%
• Description: Year-over-year growth rate of Chinese exports.

China_Manufacturing_PMI

• Type: Continuous
• Range: 47-52
• Description: Purchasing Managers' Index for manufacturing sector. Values >50 indicate expansion, <50 indicate contraction.

China_FDI_Inflow_USD_Billion

• Type: Continuous
• Unit: Billion USD
• Range: 7-15
• Description: Monthly foreign direct investment inflows into China.

Bilateral Trade Indicators

US_China_Trade_Volume_USD_Billion

• Type: Continuous
• Unit: Billion USD
• Range: 40-60
• Description: Total monthly bilateral trade volume between US and China.

US_Trade_Deficit_China_USD_Billion

• Type: Continuous
• Unit: Billion USD
• Range: -32 to -24
• Description: US trade deficit with China. Negative values indicate deficit.

Additional Economic Indicators

USD_CNY_Exchange_Rate

• Type: Continuous
• Range: 6.7-7.3
• Description: Exchange rate expressing yuan per US dollar.

China_Stock_Index

• Type: Continuous
• Range: 2,800-3,500
• Description: Shanghai Composite Stock Index (normalized).

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 2037 companies listed on the Shanghai Stock Exchange (XSHG) in China. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

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Top 5 used data fields in the End-of-Day Pricing Dataset for China:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in China:

Shanghai Stock Exchange (SSE) Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Shanghai Stock Exchange. This index provides an overview of the overall market performance in China.

Shenzhen Stock Exchange (SZSE) Domestic Company Index: The index that tracks the performance of domestic companies listed on the Shenzhen Stock Exchange. This index reflects the performance of companies listed on the technology-focused exchange.

Company A: A prominent Chinese company with diversified operations across various sectors, such as technology, finance, or manufacturing. This company's stock is widely traded on either the Shanghai Stock Exchange or the Shenzhen Stock Exchange.

Company B: A leading financial institution in China, offering banking, insurance, or investment services. This company's stock is actively traded on one of the major stock exchanges in China.

Company C: A major player in the Chinese agriculture sector or other industries, involved in the production and distribution of goods or services. This company's stock is listed and actively traded on either the Shanghai Stock Exchange or the Shenzhen Stock Exchange.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for China, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

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Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in China ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in China?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on China exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for this dataset?

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Industrial Production in China increased 0.17 percent in October of 2025 over the previous month. This dataset provides the latest reported value for - China Industrial Production Mom - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Permutable AI’s China macroeconomic sentiment dataset captures real-time reactions to GDP releases, central bank decisions, inflation data, and fiscal policy measures. Built on multilingual NLP, the dataset transforms Chinese and international news into structured sentiment scores with five-minute refresh intervals. Geopolitical intelligence quantifies election outcomes, sanctions, and trade relations, including US–China tariff actions and regional policy coordination. Natural disaster monitoring provides supply chain impact scoring across energy, manufacturing, and agriculture, helping assess China’s economic resilience. With ten years of structured historical intelligence, the dataset supports backtesting strategies across China’s growth and market cycles, accessible through the Co-Pilot API with millisecond latency.

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.

GDP from Manufacturing in China increased to 306003.60 CNY Hundred Million in the third quarter of 2025 from 202550.30 CNY Hundred Million in the second quarter of 2025. This dataset provides - China Gdp From Manufacturing- actual values, historical data, forecast, chart, statistics, economic calendar and news.

China Manufacturing: Profit Ratio from Sales Revenue: Year to Date data was reported at 6.140 % in Oct 2018. This records an increase from the previous number of 6.130 % for Sep 2018. China Manufacturing: Profit Ratio from Sales Revenue: Year to Date data is updated monthly, averaging 5.640 % from Jan 2014 (Median) to Oct 2018, with 58 observations. The data reached an all-time high of 6.350 % in Dec 2017 and a record low of 4.660 % in Feb 2015. China Manufacturing: Profit Ratio from Sales Revenue: 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.