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.

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).

🧾 About Dataset

🌍 Global GDP by Country — 2024 Edition

📖 Overview

The Global GDP by Country (2024) dataset provides an up-to-date snapshot of worldwide economic performance, summarizing each country’s nominal GDP, growth rate, population, and global economic contribution.

This dataset is ideal for economic analysis, data visualization, policy modeling, and machine learning applications related to global development and financial forecasting.

📊 Dataset Information

• Total Records: 181 countries
• Time Period: 2024 (latest available global data)
• Geographic Coverage: Worldwide
• File Format: CSV
• File Size: ~10 KB
• Missing Values: None (100% complete dataset)

🎯 Target Use-Cases:
- Economic growth trend analysis
- GDP-based country clustering
- Per capita wealth comparison
- Share of world economy visualization

🧩 Key Features

📈 Statistical Summary

Population Overview

• Mean Population: 43.6 million
• Standard Deviation: 155.5 million
• Minimum Population: 9,816 (small island nations)
• Median Population: 9.1 million
• Maximum Population: 1.43 billion (China)

🌟 Highlights

💰 Top Economies (Nominal GDP):
United States, China, Japan, Germany, India

📈 Fastest Growing Economies:
India, Bangladesh, Vietnam, and Rwanda

🌐 Global Insights:
- The dataset covers 181 countries representing 100% of global GDP.
- Suitable for data visualization dashboards, AI-driven economic forecasting, and educational research.

💡 Example Use-Cases

• Build a choropleth map showing GDP distribution across continents.
• Train a regression model to predict GDP per capita based on population and growth.
• Compare economic inequality using population vs GDP share.

📚 Dataset Citation

Source: Worldometers — GDP by Country (2024)
Dataset compiled and cleaned by: Asadullah Shehbaz
For open research and data analysis.

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.

TThe ERS International Macroeconomic Data Set provides historical and projected data for 181 countries that account for more than 99 percent of the world economy. These data and projections are assembled explicitly to serve as underlying assumptions for the annual USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term, 10-year scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks.

Explore the International Macroeconomic Data Set 2015 for annual growth rates, consumer price indices, real GDP per capita, exchange rates, and more. Get detailed projections and forecasts for countries worldwide.

Annual growth rates, Consumer price indices (CPI), Real GDP per capita, Real exchange rates, Population, GDP deflator, Real gross domestic product (GDP), Real GDP shares, GDP, projections, Forecast, Real Estate, Per capita, Deflator, share, Exchange Rates, CPI

Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe, WORLD Follow data.kapsarc.org for timely data to advance energy economics research. Notes:

Developed countries/1 Australia, New Zealand, Japan, Other Western Europe, European Union 27, North America

Developed countries less USA/2 Australia, New Zealand, Japan, Other Western Europe, European Union 27, Canada

Developing countries/3 Africa, Middle East, Other Oceania, Asia less Japan, Latin America;

Low-income developing countries/4 Haiti, Afghanistan, Nepal, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda, Zimbabwe;

Emerging markets/5 Mexico, Brazil, Chile, Czech Republic, Hungary, Poland, Slovakia, Russia, China, India, Korea, Taiwan, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Singapore

BRIICs/5 Brazil, Russia, India, Indonesia, China; Former Centrally Planned Economies

Former centrally planned economies/7 Cyprus, Malta, Recently acceded countries, Other Central Europe, Former Soviet Union

USMCA/8 Canada, Mexico, United States

Europe and Central Asia/9 Europe, Former Soviet Union

Middle East and North Africa/10 Middle East and North Africa

Other Southeast Asia outlook/11 Malaysia, Philippines, Thailand, Vietnam

Other South America outlook/12 Chile, Colombia, Peru, Bolivia, Paraguay, Uruguay

Indicator Source

Real gross domestic product (GDP) World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service all converted to a 2015 base year.

Real GDP per capita U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table and Population table.

GDP deflator World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Real GDP shares U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table.

Real exchange rates U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, CPI table, and Nominal XR and Trade Weights tables developed by the Economic Research Service.

Consumer price indices (CPI) International Financial Statistics International Monetary Fund, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Population Department of Commerce, Bureau of the Census, U.S. Department of Agriculture, Economic Research Service, International Data Base.

U.S. Public Debt vs. GDP

Trends and Comparisons

By Charlie Hutcheson [source]

About this dataset

This dataset contains quarterly data on the US Gross Domestic Product (GDP) and Total Public Debt from 1947 through 2020. It provides a comprehensive view into the development of debt versus GDP over the years, offering insights into how our economy has grown and changed since The Great Depression. Explore this valuable information to answer questions such as: How do debt and GDP relate to one another? Has US government spending been outpacing wealth throughout history? From what sources does our national debt originate? This dataset can be utilized by economists, governments, researchers, investors, financial institutions, journalists — anyone looking to gain a better understanding of where our economy stands today compared to past decades

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset, U.S. GDP vs Debt Over Time, contains quarterly data on the Gross Domestic Product (GDP) and Total Public Debt of the United States between 1947 to 2020. This can be useful for conducting research into how the total public debt relates to economic growth in the US.

The dataset includes 4 columns: Quarter , Gross Domestic Product ($mil), Total Public Debt ($mil). The Quarter column consists of strings that represent each quarter from 1947-2020 with a corresponding number (e.g., “Q1-1947”). The Gross Domestic Product ($mil) and Total Public Debt ($mil) columns consist of numbers that indicate the respective amounts in millions for each quarter during this same time period.

By analyzing this dataset you can explore various trends over different periods as it relates to public debt versus economic growth in America and make informed decisions about how certain policies may affect future outcomes. Additionally, you could also compare these two values with other variables such as unemployment rate or inflation rate to gain deeper insights into America’s economy over time

Research Ideas

• Comparing the quarterly growth in GDP with public debt to show the correlation between economic growth and government spending.
• Creating a bar or line visualization that compares the US’s total public debt to comparable economic powers like China, Japan, and Europe over time.
• Examining how changes in government deficit have contributed towards an increase in public debt by analyzing which quarters saw significant leaps of growth from one year to the next

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: US GDP vs Debt.csv | Column name | Description | |:----------------------------------|:-------------------------------------------------------------------------------------------| | Quarter | The quarter of the year in which the data was collected. (String) | | Gross Domestic Product ($mil) | The total value of all goods and services produced by the US in a given quarter. (Integer) | | Total Public Debt ($mil) | The total amount owed by the federal government. (Integer) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Charlie Hutcheson.

Explore real GDP growth projections dataset, including insights into the impact of COVID-19 on economic trends. This dataset covers countries such as Spain, Australia, France, Italy, Brazil, and more.

growth rate, Real, COVID-19, GDP

Spain, Australia, France, Italy, Brazil, Argentina, United Kingdom, United States, Canada, Russia, Turkiye, World, China, Mexico, Korea, India, Saudi Arabia, South Africa, Germany, Indonesia, JapanFollow data.kapsarc.org for timely data to advance energy economics research..Source: OECD Economic Outlook database.- India projections are based on fiscal years, starting in April. The European Union is a full member of the G20, but the G20 aggregate only includes countries that are also members in their own right. Spain is a permanent invitee to the G20. World and G20 aggregates use moving nominal GDP weights at purchasing power parities. Difference in percentage points, based on rounded figures.

This dataset offers a detailed comparison of key global players like USA, Russia, China, India, Canada, Australia, and others across various economic, social, and environmental metrics. By comparing countries on indicators such as GDP, population, healthcare access, education levels, internet penetration, military spending, and much more, this dataset provides valuable insights for researchers, policymakers, and analysts.

🔍 Key Comparisons:

Economic Indicators: GDP, inflation rates, unemployment rates, etc. Social Indicators: Literacy rates, healthcare quality, life expectancy, etc. Environmental Indicators: CO2 emissions, renewable energy usage, protected areas, etc. Technological Advancements: Internet users, mobile subscriptions, tech exports, etc. Military Spending: Defense budgets, military personnel numbers, etc. This dataset is perfect for those who want to compare countries in terms of development, growth, and global standing. It can be used for data analysis, policy planning, research, and even education.

✨ Key Features:

Comprehensive Coverage: Includes multiple countries with key metrics. Multiple Domains: Economic, social, environmental, technological, and military data. Up-to-date Information: Covers data from the last decade to provide recent insights. Research Ready: Suitable for academic research, visualizations, and analysis.

Explore annual GDP growth rates for various countries with this dataset. Analyze trends and patterns related to GDP growth to make informed decisions. Click here for more information!

GDP growth (annual %), GDP, Growth Rates

Kenya, Spain, Syrian Arab Republic, Bosnia and Herzegovina, El Salvador, Italy, Sint Maarten (Dutch part), Comoros, Kosovo, Argentina, Bulgaria, Guinea-Bissau, Slovenia, Guinea, Belize, Low income, Lower middle income, New Caledonia, St. Kitts and Nevis, Benin, World, Kyrgyz Republic, United Arab Emirates, Ethiopia, Burundi, Korea, Rep., Low & middle income, Euro area, Libya, Luxembourg, Namibia, Kiribati, India, Burkina Faso, East Asia & Pacific (excluding high income), Tajikistan, Lao PDR, Equatorial Guinea, Niger, Liechtenstein, Palau, Hong Kong SAR, China, Switzerland, Tonga, Qatar, Turkiye, Middle East & North Africa (excluding high income), Indonesia, Iraq, Fiji, Central Europe and the Baltics, Isle of Man, Costa Rica, Finland, Small states, Singapore, Slovak Republic, Netherlands, Turks and Caicos Islands, Europe & Central Asia (IDA & IBRD countries), Japan, Bhutan, Belgium, Australia, Denmark, Heavily indebted poor countries (HIPC), Middle East & North Africa (IDA & IBRD countries), Uzbekistan, Pacific island small states, Mongolia, Gabon, St. Vincent and the Grenadines, Ukraine, Venezuela, RB, Latvia, Macao SAR, China, Vietnam, Arab World, Myanmar, Latin America & Caribbean (excluding high income), Haiti, Micronesia, Fed. Sts., Nicaragua, Panama, San Marino, Gambia, The, Guatemala, IDA & IBRD total, Azerbaijan, Chad, Zimbabwe, Mali, Bolivia, Grenada, Mexico, East Asia & Pacific (IDA & IBRD countries), Timor-Leste, Dominica, Peru, Malawi, Trinidad and Tobago, Nauru, Monaco, Tuvalu, Egypt, Arab Rep., Virgin Islands (U.S.), Sao Tome and Principe, Cabo Verde, IDA only, Mozambique, Oman, Yemen, Rep., Albania, New Zealand, Latin America & Caribbean, Rwanda, Cameroon, Lesotho, Solomon Islands, Germany, Bangladesh, Papua New Guinea, Maldives, Moldova, Antigua and Barbuda, Congo, Dem. Rep., Romania, Portugal, Africa Western and Central, Mauritius, France, Uruguay, Tanzania, Colombia, South Asia (IDA & IBRD), Honduras, South Sudan, Sudan, Cuba, Least developed countries: UN classification, South Asia, Tunisia, Guyana, Nepal, Barbados, Brunei Darussalam, United States, Canada, Lebanon, Africa Eastern and Southern, Sub-Saharan Africa (excluding high income), Angola, Bahamas, The, Fragile and conflict affected situations, Malta, Middle East & North Africa, Turkmenistan, Cote d'Ivoire, Northern Mariana Islands, Thailand, Seychelles, North Macedonia, Afghanistan, Russian Federation, IBRD only, Iran, Islamic Rep., Malaysia, Djibouti, Europe & Central Asia (excluding high income), Norway, Dominican Republic, French Polynesia, Jordan, Nigeria, Lithuania, Estonia, Eswatini, Vanuatu, Late-demographic dividend, St. Lucia, Cambodia, Curacao, Kuwait, Belarus, American Samoa, Bahrain, Somalia, Pre-demographic dividend, Ghana, Sierra Leone, Jamaica, Ecuador, European Union, Post-demographic dividend, Brazil, Central African Republic, Chile, Puerto Rico, Pakistan, Uganda, United Kingdom, IDA total, Marshall Islands, Czechia, Channel Islands, Poland, Togo, Latin America & the Caribbean (IDA & IBRD countries), Sweden, Iceland, Armenia, Georgia, Montenegro, Europe & Central Asia, Hungary, IDA blend, Sub-Saharan Africa (IDA & IBRD countries), Paraguay, Zambia, Andorra, OECD members, Bermuda, Early-demographic dividend, Croatia, Upper middle income, Algeria, Samoa, Eritrea, Suriname, Mauritania, Guam, China, Sri Lanka, Congo, Rep., Liberia, Greece, Botswana, East Asia & Pacific, West Bank and Gaza, Philippines, Cayman Islands, Saudi Arabia, South Africa, High income, Serbia, Caribbean small states, Greenland, Cyprus, Aruba, Ireland, Israel, Kazakhstan, Morocco, Madagascar, Other small states, Sub-Saharan Africa, Senegal, Middle income, Austria, North America Follow data.kapsarc.org for timely data to advance energy economics research.

CONTENT

This dataset contains data on key indicators of world's top 6 Economies (by GDP) which includes USA, China, Japan, Germany, United Kingdom, India between the time interval of 30 years from 1990 to 2020. Data scraped from World Bank Data website and processed using Python Pandas library. This dataset could be used to do Time Series Analysis and Forecasting.

Code notebook:

https://deepnote.com/workspace/charan-chandrasekaran-9b7f-9e1375d3-f150-44ca-a9fb-feb08a1e8585/project/Data-extraction-from-World-bank-data-on-Top-6-Economies-2cdf8112-d412-4044-a58e-5e464804e9b6

INDICATORS

1. GDP (current US$)
2. GDP, PPP (current international $)
3. GDP per capita (current US$)
4. GDP growth (annual %)
5. Imports of goods and services (% of GDP)
6. Exports of goods and services (% of GDP)
7. Central government debt, total (% of GDP)
8. Total reserves (includes gold, current US$)
9. Unemployment, total (% of total labor force) (modelled ILO estimate)
10. Inflation, consumer prices (annual %)
11. Personal remittances, received (% of GDP)
12. Population, total
13. Population growth (annual %)
14. Life expectancy at birth, total (years)
15. Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population)

SOURCE

The World Bank : https://data.worldbank.org/country

The Gross Domestic Product per capita in China was last recorded at 23845.62 US dollars in 2024, when adjusted by purchasing power parity (PPP). The GDP per Capita, in China, when adjusted by Purchasing Power Parity is equivalent to 134 percent of the world's average. This dataset provides - China GDP per capita PPP - actual values, historical data, forecast, chart, statistics, economic calendar 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.

The Gross Domestic Product (GDP) of countries and regions from 1960 to 2020 provides a comprehensive view of economic development over six decades. GDP measures the total value of goods and services produced in a country or region over a specific period and is an important indicator of economic health and growth. Below is a summary of the GDP trends for major regions and selected countries:

Global Overview (1960-2020) 1- 1960s-1980s: During this period, many developed economies such as the United States, Japan, and Western European countries experienced robust economic growth. This was a time of post-World War II reconstruction, technological advancement, and increasing globalization.

2- 1990s-2000s: The fall of the Soviet Union in the early 1990s marked a shift in global economic dynamics. Many former Soviet states and Eastern European countries transitioned to market economies. Asia, particularly China and India, began to emerge as major economic players due to economic reforms and rapid industrialization.

3- 2010s-2020: The 2010s were marked by steady growth in advanced economies, while emerging markets such as China, India, Brazil, and others became significant contributors to global GDP. However, the COVID-19 pandemic in 2020 led to a severe global economic downturn.

This dataset provides key economic indicators for five of the world's largest economies, based on their nominal Gross Domestic Product (GDP) in 2022. It includes the GDP values, population, GDP growth rates, per capita GDP, and each country's share of the global economy.

Columns: Country: Name of the country. GDP (nominal, 2022): The total nominal GDP in 2022, represented in USD. GDP (abbrev.): The abbreviated GDP in trillions of USD. GDP growth: The percentage growth in GDP compared to the previous year. Population: Total population of each country in 2022. GDP per capita: The GDP per capita, representing average economic output per person in USD. Share of world GDP: The percentage of global GDP contributed by each country. Key Highlights: The dataset includes some of the largest global economies, such as the United States, China, Japan, Germany, and India. The data can be used to analyze the economic standing of countries in terms of overall GDP and per capita wealth. It offers insights into the relative growth rates and population sizes of these leading economies. This dataset is ideal for exploring economic trends, performing country-wise comparisons, or studying the relationship between population size and GDP growth.

Explore the World Competitiveness Ranking dataset for 2016, including key indicators such as GDP per capita, fixed telephone tariffs, and pension funding. Discover insights on social cohesion, scientific research, and digital transformation in various countries.

Social cohesion, The image abroad of your country encourages business development, Scientific articles published by origin of author, International Telecommunication Union, World Telecommunication/ICT Indicators database, Data reproduced with the kind permission of ITU, National sources, Fixed telephone tariffs, GDP (PPP) per capita, Overall, Exports of goods - growth, Pension funding is adequately addressed for the future, Companies are very good at using big data and analytics to support decision-making, Gross fixed capital formation - real growth, Economic Performance, Scientific research legislation, Percentage of GDP, Health infrastructure meets the needs of society, Estimates based on preliminary data for the most recent year., Singapore: including re-exports., Value, Laws relating to scientific research do encourage innovation, % of GDP, Gross Domestic Product (GDP), Health Infrastructure, Digital transformation in companies is generally well understood, Industrial disputes, EE, Female / male ratio, State ownership of enterprises, Total expenditure on R&D (%), Score, Colombia, Estimates for the most recent year., Percentage change, based on US$ values, Number of listed domestic companies, Tax evasion is not a threat to your economy, Scientific articles, Tax evasion, % change, Use of big data and analytics, National sources, Disposable Income, Equal opportunity, Listed domestic companies, Government budget surplus/deficit (%), Pension funding, US$ per capita at purchasing power parity, Estimates; US$ per capita at purchasing power parity, Image abroad or branding, Equal opportunity legislation in your economy encourages economic development, Number, Article counts are from a selection of journals, books, and conference proceedings in S&E from Scopus. Articles are classified by their year of publication and are assigned to a region/country/economy on the basis of the institutional address(es) listed in the article. Articles are credited on a fractional-count basis. The sum of the countries/economies may not add to the world total because of rounding. Some publications have incomplete address information for coauthored publications in the Scopus database. The unassigned category count is the sum of fractional counts for publications that cannot be assigned to a country or economy. Hong Kong: research output items by the higher education institutions funded by the University Grants Committee only., State ownership of enterprises is not a threat to business activities, Protectionism does not impair the conduct of your business, Digital transformation in companies, Total final energy consumption per capita, Social cohesion is high, Rank, MTOE per capita, Percentage change, based on constant prices, US$ billions, National sources, World Trade Organization Statistics database, Rank, Score, Value, World Rankings

Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Canada, Chile, China, Colombia, Croatia, Cyprus, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, India, Indonesia, Ireland, Israel, Italy, Japan, Jordan, Kazakhstan, Latvia, Lithuania, Luxembourg, Malaysia, Mexico, Mongolia, Netherlands, New Zealand, Norway, Oman, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Saudi Arabia, Singapore, Slovenia, South Africa, Spain, Sweden, Switzerland, Thailand, Turkey, Ukraine, United Kingdom, Venezuela

Follow data.kapsarc.org for timely data to advance energy economics research.

Dataset Description

This dataset is sourced from FAOSTAT, the comprehensive statistical database maintained by the Food and Agriculture Organization (FAO) of the United Nations. It provides detailed and reliable data on global agriculture, food security, nutrition, and related topics. The dataset covers the period from 1971 to 2022, offering a 50-year perspective on trends and changes in agricultural production, trade, resource use, and environmental impacts.

Visit the FAOSTAT website: https://www.fao.org/faostat/.

Variables :

• Year: The year for which the data is recorded (e.g., 1971, 2022).
• China: A metric (likely percentage change or growth rate) for China in the given year.
• India: A metric for India in the given year.
• Pakistan: A metric for Pakistan in the given year.
• United Arab Emirates: A metric for the UAE in the given year.
• United Kingdom: A metric for the UK in the given year.
• United States of America: A metric for the USA in the given year.

Each column (except Year) represents a country and contains numerical values, possibly indicating growth rates, percentage changes, or other metrics over time.

Possible Sources International Organizations: FAOSTAT (Food and Agriculture Organization): Provides data on agriculture, food security, and related metrics. World Bank: Offers economic, demographic, and environmental data. United Nations (UN): Publishes data on global development indicators. IMF (International Monetary Fund): Provides financial and economic data. Government Agencies: National statistical offices (e.g., Census Bureau, Ministry of Agriculture). Central banks or economic departments. Research Institutions: Universities or think tanks that collect and analyze data for specific studies

The dataset contains data for 8 countries and one special administrative region (China, France, Germany, Hong Kong, India, Japan, Spain, United Kingdom and United States of America) from 1980 through 2020. It include major macroeconomic factors like inflation, unemployment, GDP, exchange rate (base USD) and per capita income. Apart from that it has the stock prices of the respective country's major stock index which can help in analysing the data set to identify the impact of major macroeconomic variables on the movement of stock index prices.

These are research indicators of comparative empirical investigation of South Eastern European Countries (SEECs) and People’s Republic of China (PRC) that were compiled from the criteria and factors of the World Bank. This dataset consists of data for SEECs and PRC for the period of 2000 to 2016. The World Bank Research Indicators consist of (1) GNI, Atlas Method (Current US$); (2) GNI per capita, Atlas; (3) GNI PPP (Current International $); (4) GNI per capita, PPP (Current International $); (5) Energy Use (kg of Oil Equivalent per capita); (6) Electric Power Consumption (kWh per capita); (7) GDP (Current US$); (8) GDP Growth (Annual %); (9) Inflation, GDP Deflator (Annual %); (10) Agriculture, Value Added (% of GDP); (11) Industry, Value Added (% of GDP); (12) Service, etc., Value Added (% of GDP); (13) Exports of Goods and Services (% of GDP); (14) Imports of Goods and Services (% of GDP); (15) Gross Capital Formation (% of GDP); (16) Revenue, excluding Grants (% of GDP); (17) Time Required to Start a Business (Days); (18) Domestic Credit Provided by Financial Sector (% of GDP); (19) Tax Revenue (% of GDP); (20) High-Technology Exports (% of Manufactured Exports); (21) Merchandise Trade (% of GDP); (22) Net Barter Terms of Trade Index (2000 = 100); (23) External Debt Stock, Total (DOD, Current US$); (24) Total Debt Service (% of Exports of Goods, Services and Primary Income); (25) Personal Remittances, Received (Current US$); (26) Foreign Direct Investment, Net Flows (BoP, Current US$); and (27) Net Official Development Assistance and Official Aid Received (Current US$). Furthermore, statistical data of SEECs and PRC were retrieved from Atlas 2.1 – Growth Lab at the Center for International Development at Harvard University and WITS – UNSD COMPTRADE.

Context:

The provided dataset is extracted from yahoo finance using pandas and yahoo finance library in python. This deals with stock market index of the world best economies. The code generated data from Jan 01, 2003 to Jun 30, 2023 that’s more than 20 years. There are 18 CSV files, dataset is generated for 16 different stock market indices comprising of 7 different countries. Below is the list of countries along with number of indices extracted through yahoo finance library, while two CSV files deals with annualized return and compound annual growth rate (CAGR) has been computed from the extracted data.

Number of Countries & Index:

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F90ce8a986761636e3edbb49464b304d8%2FNumber%20of%20Index.JPG?generation=1688490342207096&alt=media" alt="">

Content:

Unit of analysis: Stock Market Index Analysis

This dataset is useful for research purposes, particularly for conducting comparative analyses involving capital market performance and could be used along with other economic indicators.

There are 18 distinct CSV files associated with this dataset. First 16 CSV files deals with number of indices and last two CSV file deals with annualized return of each year and CAGR of each index. If data in any column is blank, it portrays that index was launch in later years, for instance: Bse500 (India), this index launch in 2007, so earlier values are blank, similarly China_Top300 index launch in year 2021 so early fields are blank too.

The extraction process involves applying different criteria, like in 16 CSV files all columns are included, Adj Close is used to calculate annualized return. The algorithm extracts data based on index name (code given by the yahoo finance) according start and end date.

Annualized return and CAGR has been calculated and illustrated in below image along with machine readable file (CSV) attached to that.

To extract the data provided in the attachment, various criteria were applied:

1. Content Filtering: The data was filtered based on several attributes, including the index name, start and end date. This filtering process ensured that only relevant data meeting the specified criteria.

2. Collaborative Filtering: Another filtering technique used was collaborative filtering using yahoo finance, which relies on index similarity. This approach involves finding indices that are similar to other index or extended dataset scope to other countries or economies. By leveraging this method, the algorithm identifies and extracts data based on similarities between indices.

In the last two CSV files, one belongs to annualized return, that was calculated based on the Adj close column and new DataFrame created to store its outcome. Below is the image of annualized returns of all index (if unreadable, machine-readable or CSV format is attached with the dataset).

Annualized Return:

As far as annualised rate of return is concerned, most of the time India stock market indices leading, followed by USA, Canada and Japan stock market indices.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F37645bd90623ea79f3708a958013c098%2FAnnualized%20Return.JPG?generation=1688525901452892&alt=media" alt="">

Compound Annual Growth Rate (CAGR):

The best performing index based on compound growth is Sensex (India) that comprises of top 30 companies is 15.60%, followed by Nifty500 (India) that is 11.34% and Nasdaq (USA) all is 10.60%.

The worst performing index is China top300, however this is launch in 2021 (post pandemic), so would not possible to examine at that stage (due to less data availability). Furthermore, UK and Russia indices are also top 5 in the worst order.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F15657145%2F58ae33f60a8800749f802b46ec1e07e7%2FCAGR.JPG?generation=1688490409606631&alt=media" alt="">

Geography: Stock Market Index of the World Top Economies

Time period: Jan 01, 2003 – June 30, 2023

Variables: Stock Market Index Title, Open, High, Low, Close, Adj Close, Volume, Year, Month, Day, Yearly_Return and CAGR

File Type: CSV file

Inspiration:

• Time series prediction model
• Investment opportunities in world best economies
• Comparative Analysis of past data with other stock market indices or other indices

Disclaimer:

This is not a financial advice; due diligence is required in each investment decision.