The Gross Domestic Product (GDP) in China expanded 4.80 percent in the third quarter of 2025 over the same quarter of the previous year. This dataset provides - China GDP Annual Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Gross Domestic Product (GDP) in China was worth 18743.80 billion US dollars in 2024, according to official data from the World Bank. The GDP value of China represents 17.65 percent of the world economy. This dataset provides - China GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Consumer Confidence in China increased to 89.60 points in September from 89.20 points in August of 2025. This dataset provides - China Consumer Confidence - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Power shortages are faced by developing countries in the Belt and Road region. Since the Belt and Road initiative was put forward, Chinese companies have invested and built a large number of electrical power projects in countries and areas with power shortages in this region. Due to the large number and wide distribution of projects and continuous increases in the number of new power projects, a large amount of project information has been generated. Accordingly, it is urgent to collect and summarize One Belt and One Road overseas power project information. In this study, web crawler technology was used to obtain overseas power project information. A One Belt and One Road dataset of overseas power projects was formed by further supplementing and improving the project information using documents from ministries, embassies, counselors of the ministry of economy and commerce, local news reports in Chinese and English, and case studies and field studies conducted by scholars and non-governmental organizations. The dataset includes information on 376 power projects from 80 countries in Asia, Africa, Europe, America, and Oceania. Each project’s information includes the project number, project name, construction status, enterprise name, installed capacity, continent, country, project category, and bid information. The collection and improvement of this dataset will help with understanding the distribution of One Belt, One Road overseas power projects, as well as development trends in overseas power investment and construction in recent years. This can provide a basis for China’s power companies to “go global” and become “One Belt, One Road” overseas. It also provides a reference for power project development planning and government department decision-making.

Small and medium-sized enterprises (SMEs) were an important part of China’s economy, but they faced challenges to growth due to financing difficulties. Government subsidies are considered as a potential way to address this problem. This study aims to assess the effectiveness of the Chinese government’s subsidy program aimed at improving the accessibility of financing for SMEs. We analyze a comprehensive dataset of Chinese firms’ subsidy programs from 2011 to 2020. We classify subsidies into unconditional and conditional categories and use fixed-effects regression models to control for the effects of time and between-group variation to more accurately assess the effectiveness of government subsidies. In addition, we use a PSM-DID model to reduce the effect of selectivity bias to more accurately estimate the causal effect of subsidies on financing strategies. We also use a mediated effects model to help understand the mechanisms by which different types of subsidies affect financing strategies. The results show that government subsidies can significantly improve SMEs’ financing ability, but different types of subsidies produce subtle differences. Conditional subsidies support debt financing mainly through incentives, while unconditional subsidies help SMEs improve their equity financing ability through information effects. Furthermore, we find that over-reliance on a single subsidy type may reduce its effectiveness, suggesting a complex relationship between government intervention and SME financing. Thus, well-designed policies are crucial for promoting SMEs and fostering economic growth.

The repeated outbreak of COVID-19 epidemic has brought a heavy blow to the world economy. Fiscal policy is one of the important macro-control measures to pull the economy out of the quagmire, and it is necessary to study the implementation of fiscal policy under the epidemic. Due to the relatively abundant resources of the Chinese government, this study uses China as the research object to study the orientation of fiscal policy under COVID-19 epidemic. We use fiscal policies and a large amount of macroeconomic data to identify fiscal policy and macroeconomic regulation's dynamic mechanism in China. Our findings indicate a dynamic feedback relationship between expenditure-based and revenue-based fiscal policy tools, output gaps, and deficit scales. Before the global economic crisis, fiscal policy can play a good role in adversely regulating the economy, and the difficulty of adjustment after the crisis has increased significantly. During COVID-19 epidemic, the interaction time between variables related to fiscal policy increased, suggesting that the implementation of fiscal policy during the epidemic should be particularly cautious.

About the Project The KAPSARC Energy Model of China (KEM China) project began in 2014 to study energy and environmental issues in China, focusing initially on the coal supply industry. KEM China has been developed to understand China’s energy economy and fuel mix, how they are impacted by government intervention, as well as their interaction with global markets. It optimizes supply decisions, minimizing fuel and technology costs, while taking into account the effect of government regulation on prices and the environment.Key Points The extraordinary pace of development of China’s coal industry created transportation bottlenecks, which increased the price of delivered domestic coal and impacted global seaborne coal prices. Congestion costs added extra costs of energy supply to the Chinese economy, calculated to be RMB 228 billion in 2011. Debottlenecking has reduced the price of Chinese domestic coal delivered to the coastal regions and contributed to the reduction in global seaborne prices since 2011. Our analysis suggests that the existing tariff structure retains most of the economic efficiency of marginal cost pricing. Though many of the infrastructure expansions delivered strongly positive rates of return, some may represent pre-investment in future needs.

What are the political implications of Chinese loans to borrowing countries? Our argument is that similar to other forms of international finance, loans from China provide leaders with additional resources to maintain their power. The nature of China's lending practices---characterized by an absence of good governance conditions---offers a unique advantage to political leaders, allowing corrupt leaders who receive loans from China to stay in power for longer periods. To support this argument, we conducted an analysis of a dataset of 115 developing countries from 2000 to 2015, focusing on the relationship between Chinese loans and leaders' political survival. Our findings indicate that Chinese loans positively impact leader survival, with the strongest effects observed in more corrupt regimes. To address endogeneity concerns, we employ a shift-share instrumentation strategy and several additional tests. Our analysis underscores the importance of Chinese lending to both international and domestic politics.

When permitted by law, employers sometimes state the preferred age and gender of their employees in job ads. The researchers study the interaction of advertised requests for age and gender on one Mexican and three Chinese job boards, showing that firms’ explicit gender requests shift dramatically away from women and towards men when firms are seeking older (as opposed to younger) workers. This ‘age twist’ in advertised gender preferences occurs in all four of our datasets and survives controls for occupation, firm, and job title fixed effects. Chinese Data The two new Chinese data sources used are job boards serving the city of Xiamen. In part because Xiamen was one of the five economic zones established immediately after China’s 1979 economic reforms, it is highly modernized relative to other Chinese cities, with an economy based on electronics, machinery and chemical engineering. One of these job boards, XMZYJS (the Xia-Zhang-Quan city public job board) is operated directly by government employees of the local labor bureau. Like state-operated Job Centers in the U.S., XMZYJS has a history as a brick-and-mortar employment service. XMZYJS’s mandate is to serve the less-skilled portion of the area’s labor market, and operates purely as a jobposting service: workers cannot post resumes or apply to jobs on the site. In fact, while XMZYJS now posts all its job ads online, many of these ads are viewed in XMZYJS‘s offices by workers who visit in person. This is done both on individual computer terminals and on a large electronic wall display. Applications are made by calling the company that placed the ad or by coming to a specific window on XMZYJS’s premises that has been reserved by the employer at a posted date and time. The second Xiamen-based job board, XMRC , is a for-profit, privately-operated company that is sponsored by the local government. Its mandate is to serve the market for skilled workers in the Xiamen metropolitan area. XMRC operates like a typical U.S. job board: both job ads and resumes are posted online, workers can submit applications to specific jobs via the site, and firms can contact individual workers through the site as well. By design, XMZYJS aggregates job postings from all local and specialized job boards for less-skilled workers in the metropolitan area, and XMRC is the main job board for skilled workers in the area. While there is potentially some cross-posting of job ads across the two sites, descriptive statistics on the types of jobs on offer suggest the sites do, indeed, serve very different populations. Like all our data sets, XMZYJS and XMRC serve private sector employers almost exclusively. Recruiting for public sector jobs, and most recruiting for State-Owned-Enterprises (SOEs) takes place via a different process. The third Chinese database represents Zhaopin as the third-largest Internet job board in China; it operates nationally and serves workers who on average are considerably more skilled than even those on XMRC. This sample is based on all unique ads posted in four five-week observation periods in 2008-2010. In contrast to XMRC and XMZYJS where the data were supplied by the job boards, the Zhaopin data were collected by a web crawler. The sample is based on all unique ads posted in four five-week observation periods in 2008-2010. The Chinese data have 141,188, 39,727, and 1,051,038 ads in the XMZYJS, XMRC and Zhaopin samples respectively. Mexican Data The Mexican data allows to ascertain whether main results extend to a nation with different economic conditions, labor market institutions and culture. The Mexican data is a sample of job ads posted on Computrabajo. Of the new data sets explored, the Computrabajo data are most similar to Zhaopin in the sense that they come from a national online site that disproportionately serves highly skilled workers. To construct an analysis sample from the Computrabajo website, the authors collected advertisements daily for approximately 18 months between early 2011 and mid-2012 using a web crawler. Both the standardized fields and the open text portions of each ad were parsed to extract variables for the analysis. Computrabajo analysis sample contains 90,487 ads.

The Chinese domestic database market is experiencing robust growth, driven by increasing government initiatives promoting digital transformation and the rising adoption of cloud computing and big data analytics across various sectors. The market, estimated at $5 billion USD in 2025, is projected to experience a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $15 billion USD by 2033. This expansion is fueled by several key factors. Firstly, the substantial investment in digital infrastructure within China, particularly in areas like smart city development and industrial automation, is creating significant demand for reliable and secure domestic database solutions. Secondly, the government's emphasis on data sovereignty and national security is pushing organizations to adopt domestically developed databases, reducing reliance on foreign technologies. Thirdly, the increasing maturity of Chinese database technology providers, coupled with their competitive pricing and localized support, is attracting both public and private sector clients. Key segments driving growth include the smart government affairs and information security sectors, followed by industry digitalization and digital industrialization. While competition is intense amongst both established players and new entrants, the long-term outlook for the Chinese domestic database market remains extremely positive. However, challenges remain. The market still faces hurdles in achieving global technological parity with established international players. Furthermore, maintaining consistent innovation and addressing issues related to data security and interoperability will be crucial for continued growth. The dependence on specific segments, like government initiatives, creates some vulnerability to policy changes. Despite these challenges, the confluence of supportive government policies, expanding digital economy, and the maturation of domestic technology providers suggests that the Chinese domestic database market is poised for substantial and sustained expansion in the coming years. Continued investment in research and development, as well as a focus on international standards compliance, will be key for Chinese companies to strengthen their position in the global database landscape.

Disclaimer: This data is only for academic research and is not intended for commercial or other purposes. If you want to cite this data, please first apply to the author for approval.The data for this study comes from the Chinese General Social Survey (CGSS), a national and comprehensive social survey project in China. This dataset covers multiple fields in China, including economy, politics, and society. On March 31, 2023, the data of the CGSS2021 annual survey was officially released to the whole society, which is the latest public data so far. Therefore, the research data for this article were selected from CGSS2021.

China’s export benefits from the significant fiscal stimulus in the United States. This paper analyzes the global spillover effect of the American economy on China’s macro-economy using the Markov Chain Monte Carlo (MCMC)-Gibbs sampling approach, with the goal of improving the ability of China’s financial system to protect against foreign threats. This paper examines the theories of the consequences of uncertainty on macroeconomics first. Then, using medium-sized economic and financial data, the uncertainty index of the American and Chinese economies is built. In order to complete the test and analysis of the dynamic relationship between American economic uncertainty and China’s macro-economy, a Time Varying Parameter-Stochastic Volatility-Vector Autoregression (TVP- VAR) model with random volatility is constructed. The model is estimated using the Gibbs sampling method based on MCMC. For the empirical analysis, samples of China’s and the United States’ economic data from January 2001 to January 2022 were taken from the WIND database and the FRED database, respectively. The data reveal that there are typically fewer than 5 erroneous components in the most estimated parameters of the MCMC model, which suggests that the model’s sampling results are good. China’s pricing level reacted to the consequences of the unpredictability of the American economy by steadily declining, reaching its lowest point during the financial crisis in 2009, and then gradually diminishing. After 2012, the greatest probability density range of 68% is extremely wide and contains 0, indicating that the impact of economic uncertainty in the United States on China’s pricing level is no longer significant. China should therefore focus on creating a community of destiny by working with nations that have economic cooperation to lower systemic financial risks and guarantee the stability of the capital market.

The research conducted theoretical analysis and empirical testing on the relationship between higher education and regional green productivity based on panel data from 30 Chinese provinces from 2003 to 2021. The study’s findings demonstrate that higher education can have a major impact on local green production. In order to determine whether industrial structure upgrading and the digital economy work together to promote the development of green productivity, higher education is added to these factors at the same time as the new economic growth mode transformation in the digital economy era. The research hypothesis aligns with the results, suggesting that higher education and the digital economy collaborate to enhance green productivity levels. Higher education has a more significant impact on green productivity the greater the level of regional economic growth, according to a further nonlinear test utilizing the partial linear function coefficient (PLFC) model. Higher education’s influence on green production varies by place and period, becoming more pronounced as time passes and the degree of regional economic growth rises. In order to fully utilize higher education’s capacity for scientific research, innovation, and talent, as well as to increase the direct contribution of its scientific and technological innovations to the advancement of national industry and production promotion, it is imperative that people actively promote the new type of industrialization, develop the digital economy, and work in tandem with higher education.

Abstract

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

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

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

Geographic coverage

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

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

The sample frame was obtained by SunFaith from SinoTrust.

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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

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

Cleaning operations

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

Response rate

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

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

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

The Gross Domestic Product per capita in China was last recorded at 13121.68 US dollars in 2024. The GDP per Capita in China is equivalent to 104 percent of the world's average. This dataset provides - China GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset provides the data and code for the paper: "Central Bank Green Communication and Pollution Premium: Evidence from China." The study's central hypothesis is that green communication by a central bank leads to a "pollution premium," where investors demand higher expected returns as risk compensation for holding stocks of high-polluting firms.
The data was gathered for A-share listed companies in China from Q1 2007 to Q4 2023, with firm-level financial, governance, and market data sourced from the CSMAR and RESSET databases. The core explanatory variable, the Central Bank Green Communication (DGC) index, was constructed through text analysis of the China Monetary Policy Implementation Reports issued by the People's Bank of China. This process involved creating a specialized Chinese green finance dictionary using machine learning algorithms (Word2Vec) and then quantifying the central bank's green focus by calculating the frequency of green-related terms.
The data shows that stronger central bank green communication significantly increases the expected stock returns and lowers the valuation (e.g., price-to-earnings ratio) of high-polluting firms. Notable findings reveal that this effect is transmitted through three primary channels: increasing the risk exposure of polluting firms, tightening lending restrictions from commercial banks, and shifting investor preferences toward sustainability. The folder contains the main panel dataset for baseline regressions (data.dta), as well as specific datasets for the event study (eventsd.dta), Granger causality tests (granger.dta), and portfolio analysis (portfolio.dta). For a detailed description of all files and all variables, please refer to the README document (Readme.docx) included in the package. Researchers can use this data in conjunction with the provided Stata code file (code.do) to fully replicate all tables and figures presented in the manuscript, thereby verifying its conclusions. The data can also be used to test alternative model specifications or serve as a foundation for future research in green finance, central bank communication, and asset pricing.

1. The data is based on the 2021 Chinese General Social Survey (CGSS) database, and relevant issues such as personal physical and mental health, as well as family and regional economic development levels were selected for data screening. It should be noted that the China General Social Survey Database (CGSS) is the first nationwide, comprehensive, and continuous large-scale social survey project in China. Its data has been desensitized and ethically reviewed, in compliance with the requirements of the Personal Information Protection Law. 2. Some regional data come from the government's public websites, including the statistical report on China's Internet development and the data collation of the national statistical yearbook. The three key indicators, namely, regional economic level, Internet penetration rate and aging level, are quantified according to the provinces to which the samples belong. At the same time, spatial fuzzification is carried out to aggregate provincial data into regional averages. 3. Select individuals as research subjects, and the data has been anonymized for all personal information. 4. Exclude samples with missing key variables and retain a total of 1099 pieces of data information. 5. Variable description Column 1- Province where the sample is located; Column 2-y_tz Commercial Pension Insurance Investment Decision (CGSS Questionnaire A41); Column 3-intel_1 scenario interaction level (Internet use frequency; questionnaire A28); Column 4- Sex Gender (Questionnaire A2); List 5-edu education level (questionnaire A7, fuzzy classification according to junior high school, high school, undergraduate and above); List 6- Work status (questionnaire A59a); List 7-hukou household registration (urban distribution status; questionnaire A18); Column 8-happy subjective well-being (questionnaire A36); List 9-jyb Basic Pension Insurance (Questionnaire A61; Pay attention to whether you are insured); List 10 age age (questionnaire A3; add random error ± 2 years); List 11 ethnic groups (questionnaire A4; divided into two categories: Han and minority); Column 12-jw_0 endogenous interaction (social activity frequency; questionnaire A31b); 13 Mary's marital status (questionnaire A69; divided into married and unmarried categories); Column 14- Trust Social Trust (Questionnaire A33); Column 15- ln_GDP regional economic level (logarithmized regional GDP in yuan units); Column 16-ln_pjl Internet penetration rate (log the regional Internet penetration rate); List 17- Physical Health Level (Questionnaire A16; only for self-assessment of health index 1-5 points); List 18 mental health level (questionnaire A17; only for self-assessment of health index 1-5 points); List the aging level of the region (the proportion of elderly people aged 60 and above in each province in the current year); List 20 YLGN elderly care concepts (questionnaire A41); Column 21- Household Economic Status (Perception of Household Economy at Regional Level: Divided into Above Average, Equal to Average, and Below Average; Questionnaire A64)

China recorded a trade surplus of 90.07 USD Billion in October of 2025. This dataset provides - China Balance of Trade - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The research dataset was obtained through a comprehensive survey of citrus cultivators in Ziguixian, Hubei Province,China conducted by the research team in July 2023. Ziguixian is a well-known orange production base in China with a large scale of cultivation, renowned as the “hometown of navel orange”. Ziguixian navel oranges are highly favored in domestic and international markets and have been recognized as a Chinese geographical indication product (Fig. 2). The research team randomly selected two townships, Guojiaba and Shuitianba, from the four largest orange production areas in Ziguixian, and then selected 5-6 villages from each township based on the principle of random stratified sampling. In each village, 30-40 orange growers were selected as interviewees. Before starting to fill out the questionnaire, we read out the ethics approval results of the survey to the respondents. The content of the interview will be recorded in writing, which has also been approved by the farmers. The survey yielded 406 valid responses, including 152 e-commerce-engaged households, representing 37.44% of the samples. This study was approved by the Ethics Committee of Wuhan Institute of Technology(approval number:wit20221109), the interviewee were consented by an informedconsent process that was reviewed by the Ethics Committee of Wuhan Institute of Technology and certify that the study was performed in accordancewith the ethical standards as laid down in the 1964 Declaration of Helsinki.

Although the Chinese government has implemented a variety of measures, the gender wage gap in 21st century China has not decreased. A significant body of literature has studied this phenomenon using sector segmentation theory, but these studies have overlooked the importance of the collective economy beyond the public and private sectors. Moreover, they have lacked assessment of the gender wage gap across different wage groups, hindering an accurate estimation of the gender wage gap in China, and the formulation of appropriate recommendations. Utilizing micro-level data from 2004, 2008, and 2013, this paper examines trends in the gender wage gap within the public sector, private sector, and collective economy. Employing a selection bias correction based on the multinomial logit model, this study finds that the gender wage gap is smallest and most stable within the public sector. Furthermore, the private sector surpasses the collective economy in this period, becoming the sector with the largest gender wage gap. Meanwhile, a recentered influence function regression reveals a substantial gender wage gap among the low-wage population in all three sectors, as well as among the high-wage population in the private sector. Additionally, employing Brown wage decomposition, this study concludes that inter-sector, rather than intra-sector, differences account for the largest share of the gender wage gap, with gender discrimination in certain sectors identified as the primary cause. Finally, this paper provides policy recommendations aimed at addressing the gender wage gap among low-wage groups and within the private sector.