Graph and download economic data for Economic Policy Uncertainty Index: Mainland Papers for China (CHNMAINLANDEPU) from Oct 1949 to Oct 2025 about uncertainty, China, and indexes.

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).

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.

List of Top Authors of China Economic Policy Review sorted by citations.

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.

China Environmental Policy Stringency Index: Non-Market Based Policies data was reported at 5.500 NA in 2020. This stayed constant from the previous number of 5.500 NA for 2019. China Environmental Policy Stringency Index: Non-Market Based Policies data is updated yearly, averaging 1.750 NA from Dec 1990 (Median) to 2020, with 31 observations. The data reached an all-time high of 5.500 NA in 2020 and a record low of 0.000 NA in 1996. China Environmental Policy Stringency Index: Non-Market Based Policies data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s China – Table CN.OECD.ESG: Environmental: Environmental Policy Stringency Index: Non OECD Member: Annual.

The observation of the transformation of the economic structure and development policy trends in mainland China, reflecting on the need to adjust our country's cross-strait strategy, includes five points: first, discussing the financial risks and prevention in mainland China; then summarizing the current situation of the "Belt and Road" policy in mainland China; analyzing the strategies and effectiveness of the dual-creation policy, and studying the promotion status of the third wave of free trade pilot zones. Finally, based on the above findings, suggestions for our country's economic policy responses are proposed.

NOTE: The included files cover the data and replication code for each of the three working papers that comprise this dissertation. By the time these files are available, it is likely that the author will have updated versions of each of these files. If you are interested in using these data, please contact the author directly or visit his website for the most updated versions. Concerns about domestic authority shape how governments conduct their foreign policies. However, this influence is often difficult to observe in highly opaque, non-democratic political systems. In the first part of the dissertation, I investigate the link between domestic authority and foreign policy in the context of diplomacy and trade in late imperial China, a period that spans the Ming (1368-1644) and Qing (1644-1911) dynasties. I argue that international diplomacy can serve leaders’ domestic political needs when it is highly visible to relevant audiences; conducted with counterparts held in relatively high esteem domestically; when certain diplomatic practices are historically associated with regime authority; or when diplomacy is wielded by leaders with relatively low levels of legitimacy. Using an original dataset of over 5,000 Ming and Qing tribute exchanges, I demonstrate that Chinese emperors newly in power conducted a disproportionately high volume of diplomatic activity. I find weaker evidence that this effect was more salient among low-legitimacy emperors. An accompanying case study illustrates how the Yongle Emperor deployed tribute diplomacy as a tool for domestic authority consolidation. Turning to the trade policies of the same period, I argue that beyond leaders, other autocratic elites who participate in foreign policy making are motivated by similar authority concerns. Extant research on non-democratic trade policy has largely neglected this group of actors. I develop a theory that predicts variation in elite policy preferences based on top-down and bottom-up authority relations with the leader and local trading communities, respectively. To assess these claims, I introduce a dataset on the maritime trade preferences of several hundred individual elite officials in late imperial China created through 10 months of archival work in Beijing and Taipei. The data suggest that coastal provincial officials became key pro-trade advocates during the Qing dynasty. The findings offer an example of how trade preferences can vary within a non-democratic regime, and how historical cases can be especially useful for empirically studying these preferences. In the third paper, the dissertation then flips the focus from the domestic politics of Chinese foreign policy to how other states’ internal politics shape their engagement with contemporary China. I argue that leaders of small developing countries can seek greater domestic authority by acquiring “prestige projects,” defined as highly visible, nationally salient international development projects. After identifying a set of Chinese government-financed prestige projects using a new dataset on Chinese development finance, I show that these projects are overwhelmingly concentrated in the world’s poorest and smallest countries, and that their implementation may be associated with higher public support for recipient governments. I also find that China’s government supplies more prestige projects to states that increase their support for Chinese diplomatic objectives.

Policy rate, percent in China, October, 2025 The most recent value is 3 percent as of October 2025, no change compared to the previous value of 3 percent. Historically, the average for China from January 2000 to October 2025 is 5.09 percent. The minimum of 3 percent was recorded in May 2025, while the maximum of 7.47 percent was reached in December 2007. | TheGlobalEconomy.com

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.

Key information about Macau SAR (China) Policy Rate

• Macau SAR (China) cash rate (Policy Rate: Month End: Discount Window Base Rate) was set at 4.75 % pa in Feb 2025, compared with 4.75 % pa in the previous Jan 2025.
• Macau SAR (China) Policy Rate averaged 2.25 % pa and is updated monthly, available from Dec 1999 to Feb 2025.
• The data reached an all-time high of 8.00 % pa in Dec 2000 and a record low of 0.50 % pa in Feb 2022.

• In the latest reports, Macau SAR (China) Short Term Interest Rate: Month End: MAIBOR: 3 Months was reported at 5.30 % pa in Jul 2023.
• Macau SAR (China) Exchange Rate against USD averaged 8.07 (USD/MOP) in Jun 2023.

The digital economy, as a new economic form with high information density, provides a new driving force for the realization of high-quality agricultural development. Panel data of 31 provinces in China from 2011 to 2020 were selected for analysis. The static panel data interaction effect model and panel threshold model were used to verify the nonlinear influence mechanism and heterogeneity of financial development in the process of the digital economy affecting high-quality agricultural development. The findings are as follows. (1) During the study period, the high-quality development of China’s agriculture showed a steady upward trend; however, the regional differences were significant, and the eastern part was larger than the central and western part. (2) The digital economy can promote high-quality agricultural development. (3) The digital economy has a double threshold effect in the process of affecting high-quality agricultural development, which depends on the level of financial development. When the threshold is exceeded, the digital economy has a more significant promoting effect on high-quality agricultural development. (4) The impact of the digital economy on high-quality agricultural development is heterogeneous. From the perspective of different regions, the impact effect is greatest in the eastern region, while the effect is smaller in the central and western regions. From different resource endowments, the positive impact effect is greatest in the major grain-selling areas, followed by the major grain producing areas, but the positive digital economy driving effect is not significant in the balance of production and sales areas. Finally, three policy suggestions are proposed. First, the Chinese government should increase investments in and support for digital technology to promote the integration of the digital economy and agriculture. Second, the Chinese government should promote the development of digital inclusive finance in areas with financial development below the threshold. Third, different regions should implement differentiated digital economies to promote high-quality agricultural development.

China Environmental Policy Stringency Index: Market Based Policies data was reported at 1.667 NA in 2020. This records an increase from the previous number of 1.333 NA for 2019. China Environmental Policy Stringency Index: Market Based Policies data is updated yearly, averaging 0.333 NA from Dec 1990 (Median) to 2020, with 31 observations. The data reached an all-time high of 1.667 NA in 2020 and a record low of 0.000 NA in 1991. China Environmental Policy Stringency Index: Market Based Policies data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s China – Table CN.OECD.ESG: Environmental: Environmental Policy Stringency Index: Non OECD Member: Annual.

China Environmental Policy Stringency Index: Market Based Policies: Diesel tax data was reported at 2.000 NA in 2020. This stayed constant from the previous number of 2.000 NA for 2019. China Environmental Policy Stringency Index: Market Based Policies: Diesel tax data is updated yearly, averaging 0.000 NA from Dec 1990 (Median) to 2020, with 31 observations. The data reached an all-time high of 2.000 NA in 2020 and a record low of 0.000 NA in 2007. China Environmental Policy Stringency Index: Market Based Policies: Diesel tax data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s China – Table CN.OECD.ESG: Environmental: Environmental Policy Stringency Index: Non OECD Member: Annual.

The formulation of science and technology financial policies directly influences the direction of national economic development. Quantitative evaluation of these policies is an important method to reflect the consistency and strengths and weaknesses of policy interrelations. This paper analyzes 16 science and technology financial policy documents issued by the Chinese central government from 2016 to 2022, using text analysis and content analysis to extract keyword frequencies, and constructs 9 primary variables and 34 secondary variables. For the first time, a PMC-AE index model for science and technology financial policies is established, and a quantitative evaluation is conducted on 5 significant policy documents out of the 16. The results show that, from an overall analysis, Policy 1 and Policy 4 are at a good level, while the other three policies are at an excellent level. From the analysis of individual policy PMC-AE indexes, the rankings in descending order are: P2 > P5 > P3 > P4 > P1. Overall, the policies effectively meet the needs of China’s science and technology financial development, with P2, P3, and P5 being at an excellent level, P4 at a good level, and P1 at an acceptable level, mainly reflecting the need for improvement in aspects such as policy synchronization with the current stage, targeted entities, guiding fields, and policy content. It is recommended that Chinese government departments should focus on five aspects in policy formulation: building a talent system for science and technology finance, improving the quality of financial services, coordinating central and local financial policies, protecting intellectual property rights in science and technology finance, and strengthening financial supervision. This will be conducive to the effective implementation of science and technology financial policies.

The paper utilizes a panel data set compiled from 4,421 Chinese listed companies, covering a period from 2007 to 2021. This comprehensive dataset allows for an extensive analysis of the relationship between economic policy uncertainty (EPU) and the dividend policies of these companies.

The benchmark interest rate in China was last recorded at 3 percent. This dataset provides the latest reported value for - China Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Key information about China Policy Rate

• China cash rate (Policy Rate: Month End: China: 7 Day Reverse Repurchase Rate) was set at 1.40 % pa in Nov 2025, compared with 1.40 % pa in the previous Oct 2025.
• China Policy Rate averaged 2.55 % pa and is updated monthly, available from May 2012 to Nov 2025.
• The data reached an all-time high of 4.40 % pa in Jul 2013 and a record low of 1.40 % pa in Nov 2025.

• In the latest reports, China Short Term Interest Rate: Month End: SHIBOR: 3 Months was reported at 1.58 % pa in Nov 2025.
• Its Long Term Interest Rate (Treasury Bond Yield: Interbank: Spot Yield: 10 year) was reported at 1.86 % pa in Nov 2025.
• China Exchange Rate against USD averaged 7.12 (USD/RMB) in Oct 2025.
• Its Real Effective Exchange Rate was 130.02 in Oct 2025.

China SPI: Pillar 2 Data Services Score: Scale 0-100 data was reported at 43.800 NA in 2023. This stayed constant from the previous number of 43.800 NA for 2022. China SPI: Pillar 2 Data Services Score: Scale 0-100 data is updated yearly, averaging 45.100 NA from Dec 2016 (Median) to 2023, with 8 observations. The data reached an all-time high of 48.533 NA in 2016 and a record low of 42.400 NA in 2021. China SPI: Pillar 2 Data Services Score: Scale 0-100 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: Governance: Policy and Institutions. The data services pillar overall score is a composite indicator based on four dimensions of data services: (i) the quality of data releases, (ii) the richness and openness of online access, (iii) the effectiveness of advisory and analytical services related to statistics, and (iv) the availability and use of data access services such as secure microdata access. Advisory and analytical services might incorporate elements related to data stewardship services including input to national data strategies, advice on data ethics and calling out misuse of data in accordance with the Fundamental Principles of Official Statistics.;Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators);Weighted average;

With the development of China’s economy entering a new stage, the quality of life, which centers on the well-being of residents, provides an essential hand in promoting the transformation of the regional economy from high-speed development to high-quality development. Based on a panel threshold regression model, we examine in this paper whether quality of life helps regional economies realize developmental convergence. The research shows that: (1) The quality of life overall can promote regional economic development and passes the series test with relatively robust results. (2) The quality of life has a non-linear effect on regional economic growth, which is mainly manifested in the fact that the impact is more significant in regions with higher levels of quality of life and weaker in regions with lagging quality of life and may widen the gap between regions at the same time. (3) We categorize the study regions to test further regional heterogeneity based on regional location and development status. At the Quality of Life Level-I regions, their influence on economic development has a more substantial pulling effect. Therefore, each region should seize the strategic opportunity to improve the quality of life, focus on the balanced development of the quality of life, strengthen policy support and social security, and strive to promote the coordinated development of China’s regional economy.