The Gross Domestic Product (GDP) in China expanded 5.40 percent in the first 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 India expanded 7.40 percent in the first quarter of 2025 over the same quarter of the previous year. This dataset provides - India GDP Annual Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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 is about book subjects. It has 12 rows and is filtered where the books is A political economy of the United States, China, and India : prosperity with inequality. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

The statistic shows the gross domestic product (GDP) per capita in India from 1987 to 2030. In 2020, the estimated gross domestic product per capita in India amounted to about 1,915.55 U.S. dollars. See figures on India's economic growth here. For comparison, per capita GDP in China had reached about 6,995.25 U.S. dollars in 2013. India's economic progress India’s progress as a country over the past decade can be attributed to a global dependency on cheaper production of goods and services from developed countries around the world. India’s economy is built upon its agriculture, manufacturing and services sector, which, along with its drastic rise in population and demand for employment, led to a significant increase of the nation’s GDP per capita. Despite experiencing rather momentous economic gains since the mid 2000s, the Indian economy stagnated around 2012, with a decrease in general growth as well as the value of its currency. Residents and consumers in India have recently shown pessimism regarding the future of the Indian economy as well as their own financial situation, and with the recent economic standstill, consumer confidence in the country could potentially lower in the near future. Typical Indian exports consist of agricultural products, jewelry, chemicals and ores. Imports consist primarily of crude oil, gold and precious stones, used primarily in the manufacturing of jewelry. As a result, India has seen a rather highly increased demand of several gems in order to boost their jewelry industry and in general their exports. Although India does not export an extensive amount of goods, especially when considering the stature of the country, India has remained as one of the world’s largest exporters.

Explore the Saudi Arabia World Development Indicators dataset , including key indicators such as Access to clean fuels, Adjusted net enrollment rate, CO2 emissions, and more. Find valuable insights and trends for Saudi Arabia, Bahrain, Kuwait, Oman, Qatar, China, and India.

Indicator, Access to clean fuels and technologies for cooking, rural (% of rural population), Access to electricity (% of population), Adjusted net enrollment rate, primary, female (% of primary school age children), Adjusted net national income (annual % growth), Adjusted savings: education expenditure (% of GNI), Adjusted savings: mineral depletion (current US$), Adjusted savings: natural resources depletion (% of GNI), Adjusted savings: net national savings (current US$), Adolescents out of school (% of lower secondary school age), Adolescents out of school, female (% of female lower secondary school age), Age dependency ratio (% of working-age population), Agricultural methane emissions (% of total), Agriculture, forestry, and fishing, value added (current US$), Agriculture, forestry, and fishing, value added per worker (constant 2015 US$), Alternative and nuclear energy (% of total energy use), Annualized average growth rate in per capita real survey mean consumption or income, total population (%), Arms exports (SIPRI trend indicator values), Arms imports (SIPRI trend indicator values), Average working hours of children, working only, ages 7-14 (hours per week), Average working hours of children, working only, male, ages 7-14 (hours per week), Cause of death, by injury (% of total), Cereal yield (kg per hectare), Changes in inventories (current US$), Chemicals (% of value added in manufacturing), Child employment in agriculture (% of economically active children ages 7-14), Child employment in manufacturing, female (% of female economically active children ages 7-14), Child employment in manufacturing, male (% of male economically active children ages 7-14), Child employment in services (% of economically active children ages 7-14), Child employment in services, female (% of female economically active children ages 7-14), Children (ages 0-14) newly infected with HIV, Children in employment, study and work (% of children in employment, ages 7-14), Children in employment, unpaid family workers (% of children in employment, ages 7-14), Children in employment, wage workers (% of children in employment, ages 7-14), Children out of school, primary, Children out of school, primary, male, Claims on other sectors of the domestic economy (annual growth as % of broad money), CO2 emissions (kg per 2015 US$ of GDP), CO2 emissions (kt), CO2 emissions from other sectors, excluding residential buildings and commercial and public services (% of total fuel combustion), CO2 emissions from transport (% of total fuel combustion), Communications, computer, etc. (% of service exports, BoP), Condom use, population ages 15-24, female (% of females ages 15-24), Container port traffic (TEU: 20 foot equivalent units), Contraceptive prevalence, any method (% of married women ages 15-49), Control of Corruption: Estimate, Control of Corruption: Percentile Rank, Upper Bound of 90% Confidence Interval, Control of Corruption: Standard Error, Coverage of social insurance programs in 4th quintile (% of population), CPIA building human resources rating (1=low to 6=high), CPIA debt policy rating (1=low to 6=high), CPIA policies for social inclusion/equity cluster average (1=low to 6=high), CPIA public sector management and institutions cluster average (1=low to 6=high), CPIA quality of budgetary and financial management rating (1=low to 6=high), CPIA transparency, accountability, and corruption in the public sector rating (1=low to 6=high), Current education expenditure, secondary (% of total expenditure in secondary public institutions), DEC alternative conversion factor (LCU per US$), Deposit interest rate (%), Depth of credit information index (0=low to 8=high), Diarrhea treatment (% of children under 5 who received ORS packet), Discrepancy in expenditure estimate of GDP (current LCU), Domestic private health expenditure per capita, PPP (current international $), Droughts, floods, extreme temperatures (% of population, average 1990-2009), Educational attainment, at least Bachelor's or equivalent, population 25+, female (%) (cumulative), Educational attainment, at least Bachelor's or equivalent, population 25+, male (%) (cumulative), Educational attainment, at least completed lower secondary, population 25+, female (%) (cumulative), Educational attainment, at least completed primary, population 25+ years, total (%) (cumulative), Educational attainment, at least Master's or equivalent, population 25+, male (%) (cumulative), Educational attainment, at least Master's or equivalent, population 25+, total (%) (cumulative), Electricity production from coal sources (% of total), Electricity production from nuclear sources (% of total), Employers, total (% of total employment) (modeled ILO estimate), Employment in industry (% of total employment) (modeled ILO estimate), Employment in services, female (% of female employment) (modeled ILO estimate), Employment to population ratio, 15+, male (%) (modeled ILO estimate), Employment to population ratio, ages 15-24, total (%) (national estimate), Energy use (kg of oil equivalent per capita), Export unit value index (2015 = 100), Exports of goods and services (% of GDP), Exports of goods, services and primary income (BoP, current US$), External debt stocks (% of GNI), External health expenditure (% of current health expenditure), Female primary school age children out-of-school (%), Female share of employment in senior and middle management (%), Final consumption expenditure (constant 2015 US$), Firms expected to give gifts in meetings with tax officials (% of firms), Firms experiencing losses due to theft and vandalism (% of firms), Firms formally registered when operations started (% of firms), Fixed broadband subscriptions, Fixed telephone subscriptions (per 100 people), Foreign direct investment, net outflows (% of GDP), Forest area (% of land area), Forest area (sq. km), Forest rents (% of GDP), GDP growth (annual %), GDP per capita (constant LCU), GDP per unit of energy use (PPP $ per kg of oil equivalent), GDP, PPP (constant 2017 international $), General government final consumption expenditure (current LCU), GHG net emissions/removals by LUCF (Mt of CO2 equivalent), GNI growth (annual %), GNI per capita (constant LCU), GNI, PPP (current international $), Goods and services expense (current LCU), Government Effectiveness: Percentile Rank, Government Effectiveness: Percentile Rank, Lower Bound of 90% Confidence Interval, Government Effectiveness: Standard Error, Gross capital formation (annual % growth), Gross capital formation (constant 2015 US$), Gross capital formation (current LCU), Gross fixed capital formation, private sector (% of GDP), Gross intake ratio in first grade of primary education, male (% of relevant age group), Gross intake ratio in first grade of primary education, total (% of relevant age group), Gross national expenditure (current LCU), Gross national expenditure (current US$), Households and NPISHs Final consumption expenditure (constant LCU), Households and NPISHs Final consumption expenditure (current US$), Households and NPISHs Final consumption expenditure, PPP (constant 2017 international $), Households and NPISHs final consumption expenditure: linked series (current LCU), Human capital index (HCI) (scale 0-1), Human capital index (HCI), male (scale 0-1), Immunization, DPT (% of children ages 12-23 months), Import value index (2015 = 100), Imports of goods and services (% of GDP), Incidence of HIV, ages 15-24 (per 1,000 uninfected population ages 15-24), Incidence of HIV, all (per 1,000 uninfected population), Income share held by highest 20%, Income share held by lowest 20%, Income share held by third 20%, Individuals using the Internet (% of population), Industry (including construction), value added (constant LCU), Informal payments to public officials (% of firms), Intentional homicides, male (per 100,000 male), Interest payments (% of expense), Interest rate spread (lending rate minus deposit rate, %), Internally displaced persons, new displacement associated with conflict and violence (number of cases), International tourism, expenditures for passenger transport items (current US$), International tourism, expenditures for travel items (current US$), Investment in energy with private participation (current US$), Labor force participation rate for ages 15-24, female (%) (modeled ILO estimate), Development

Saudi Arabia, Bahrain, Kuwait, Oman, Qatar, China, India Follow data.kapsarc.org for timely data to advance energy economics research..

This dataset contains selected indicators for monitoring progress towards green growth to support policy making and inform the public at large. The indicator bring together the OECD's statistics, indicators and measures of progress. The dataset covers OECD countries as well as BRIICS economies (Brazil, Russian Federation, India, Indonesia, China and South Africa), and selected countries when possible. The indicators are selected according to well specified criteria and embedded in a conceptual framework, which is structured around four groups to capture the main features of green growth: Environmental and resource productivity, to indicate whether economic growth is becoming greener with more efficient use of natural capital and to capture aspects of production which are rarely quantified in economic models and accounting frameworks; The natural asset base, to indicate the risks to growth from a declining natural asset base; Environmental quality of life, to indicate how environmental conditions affect the quality of life and wellbeing of people; Economic opportunities and policy responses, to indicate the effectiveness ofpolicies in delivering green growth and describe the societal responses needed to secure business and employment opportunities.

The Gross Domestic Product per capita in India was last recorded at 2396.71 US dollars in 2024. The GDP per Capita in India is equivalent to 19 percent of the world's average. This dataset provides - India GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

A brief description of the provided GDP data for G20 & BRICS countries from 2008 to 2021 in five lines:

The data represents the Gross Domestic Product (GDP) of G20 countries, a group of major economies, over a 15-year period from 2008 to 2022.

It shows the varying economic sizes of G20 nations, with China and the United States consistently having the largest GDP, while smaller economies like Argentina and South Africa have considerably smaller GDPs.

Notably, the COVID-19 pandemic in 2020 had a significant impact, causing some countries' GDPs to contract temporarily before rebounding in 2021.

Japan, despite its size, experienced relatively stable GDP growth, while emerging economies like India and Indonesia demonstrated notable expansion over the years.

The European Union (EU) is not individually listed but represents a significant portion of the global economy, contributing to the overall global GDP figures.

Key information about China Foreign Direct Investment

• China Foreign Direct Investment (FDI) fell by 8.3 USD bn in Sep 2024, compared with a drop of 14.9 USD bn in the previous quarter.
• China Foreign Direct Investment: USD mn net flows data is updated quarterly, available from Mar 1998 to Sep 2024.
• The data reached an all-time high of 107.2 USD bn in Mar 2022 and a record low of -14.9 USD bn in Jun 2024.

• In the latest reports of China, Current Account recorded a surplus of 147.6 USD bn in Sep 2024.
• China Direct Investment Abroad expanded by 34.5 USD bn in Sep 2024.
• Its Foreign Portfolio Investment increased by 24.0 USD bn in Sep 2024.
• The country's Nominal GDP was reported at 4,166.8 USD bn in Mar 2023.

The aim of the article is to compare health system outcomes in the BRICS countries, assess the trends of their changes in 2000−2017, and verify whether they are in any way correlated with the economic context. The indicators considered were: nominal and per capita current health expenditure, government health expenditure, gross domestic product (GDP) per capita, GDP growth, unemployment, inflation, and composition of GDP. The study covered five countries of the BRICS group over a period of 18 years. We decided to characterize countries covered with a dataset of selected indicators describing population health status, namely: life expectancy at birth, level of immunization, infant mortality rate, maternal mortality ratio, and tuberculosis case detection rate. We constructed a unified synthetic measure depicting the performance of individual health systems in terms of their outcomes with a single numerical value. Descriptive statistical analysis of quantitative traits consisted of the arithmetic mean (xsr), standard deviation (SD), and, where needed, the median. The normality of the distribution of variables was tested with the Shapiro–Wilk test. Spearman's rho and Kendall tau rank coefficients were used for correlation analysis between measures. The correlation analyses have been supplemented with factor analysis. We found that the best results in terms of health care system performance were recorded in Russia, China, and Brazil. India and South Africa are noticeably worse. However, the entire group performs visibly worse than the developed countries. The health system outcomes appeared to correlate on a statistically significant scale with health expenditures per capita, governments involvement in health expenditures, GDP per capita, and industry share in GDP; however, these correlations are relatively weak, with the highest strength in the case of government's involvement in health expenditures and GDP per capita. Due to weak correlation with economic background, other factors may play a role in determining health system outcomes in BRICS countries. More research should be recommended to find them and determine to what extent and how exactly they affect health system outcomes.

This dataset FDI main aggregates, BMD4 is updated every quarter and includes quarterly and annual aggregate inward and outward Foreign Direct Investment (FDI) flows, positions and income for OECD reporting economies and for non-OECD G20 countries (Argentina, Brazil, China, India, Indonesia, Saudi Arabia and South Africa).

It is a simplified dataset with fewer breakdowns compared to the other separate datasets specifically dedicated to FDI flows, FDI positions or FDI income aggregates. In this dataset, FDI statistics are presented on directional basis only (unless otherwise specified, see metadata attached at the reporting country level) and resident Special Purpose Entities (SPEs), when they exist, are excluded (unless otherwise stated, see metadata attached at the reporting country level).

FDI aggregates are measured in USD millions, in millions of national currency and as a share of GDP.

This dataset supports FDI aggregates indicators available from the FDI in Figures.

In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:

• the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); and
• the IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6)

This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals.

Historical and unrevised series of FDI aggregates under the previous BMD3 methodology can be accessed in the archived dataset FDI series of BOP and IIP aggregates

Explore macroeconomic statistics and indicators, including GDP, Gross Fixed Capital Formation, National Income, and more. This dataset covers a wide range of countries such as Afghanistan, Albania, Algeria, Australia, Brazil, China, Germany, India, United States, and many more.

GDP, Gross Domestic Product, Capita, GFCF, Gross Fixed Capital Formation, Value, Added, Gross, Output, National, Income, Manufacturing, Agriculture, Population, National Accounts

Afghanistan, Albania, Algeria, Andorra, 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, Comoros, Congo, Costa Rica, Croatia, Cuba, Cyprus, Czechia, Democratic Republic of the Congo, 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, Kiribati, Kuwait, Kyrgyzstan, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkmenistan, Tuvalu, Uganda, Ukraine, United Arab Emirates, United Kingdom, United States of America, Uruguay, Uzbekistan, Vanuatu, Venezuela, Yemen, Zambia, Zimbabwe

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

Explore gender statistics data focusing on academic staff, employment, fertility rates, GDP, poverty, and more in the GCC region. Access comprehensive information on key indicators for Bahrain, China, India, Kuwait, Oman, Qatar, and Saudi Arabia.

academic staff, Access to anti-retroviral drugs, Adjusted net enrollment rate, Administration and Law programmes, Age at first marriage, Age dependency ratio, Cause of death, Children out of school, Completeness of birth registration, consumer prices, Cost of business start-up procedures, Employers, Employment in agriculture, Employment in industry, Employment in services, employment or training, Engineering and Mathematics programmes, Female headed households, Female migrants, Fertility planning status: mistimed pregnancy, Fertility planning status: planned pregnancy, Fertility rate, Firms with female participation in ownership, Fisheries and Veterinary programmes, Forestry, GDP, GDP growth, GDP per capita, gender parity index, Gini index, GNI, GNI per capita, Government expenditure on education, Government expenditure per student, Gross graduation ratio, Households with water on the premises, Inflation, Informal employment, Labor force, Labor force with advanced education, Labor force with basic education, Labor force with intermediate education, Learning poverty, Length of paid maternity leave, Life expectancy at birth, Mandatory retirement age, Manufacturing and Construction programmes, Mathematics and Statistics programmes, Number of under-five deaths, Part time employment, Population, Poverty headcount ratio at national poverty lines, PPP, Primary completion rate, Retirement age with full benefits, Retirement age with partial benefits, Rural population, Sex ratio at birth, Unemployment, Unemployment with advanced education, Urban population

Bahrain, China, India, Kuwait, Oman, Qatar, Saudi Arabia

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

Multiple regression coefficient of total NTL in China and India.

This dataset FDI positions main aggregates, BMD4 is updated every quarter and includes annual aggregate Foreign Direct Investment (FDI) positions for OECD member countries and for non-OECD G20 countries (Argentina, Brazil, China, India, Indonesia, Saudi Arabia and South Africa), which are included in International Investment Position (IIP) accounts.

FDI positions record the total level of direct investment at a given point in time, usually the end of a quarter or of a year.

In this dataset, FDI positions are presented on two different basis:

• the asset/liability presentation: FDI statistics are organised according to whether the investment relates to an asset or a liability for the country compiling the statistics. The asset/liability presentation does not show the direction of influence as the directional presentation does.
• the directional presentation: FDI statistics are organised according to the direction of the investment for the reporting economy—either outward or inward.

For more details on the difference between the two presentations, see the OECD note Implementing latest international standards-Asset liability versus directional presentation

FDI positions aggregates in this dataset are measured in USD millions, in millions of national currency and as a share of GDP.

In 2014, many countries implemented the latest international standards for Foreign Direct Investment (FDI) statistics:

• the OECD’s Benchmark Definition of FDI, 4th edition (BMD4); and
• the IMF’s Balance of Payments and International Investment Position Manual, 6th edition (BPM6)

This OECD database was launched in March 2015 which includes the data series reported by national experts according to BMD4. The data are for the most part based on balance of payments statistics published by Central Banks and Statistical Offices following the recommendations of the IMF’s BPM6 and the OECD’s BMD4. However, some of the data relate to other sources such as notifications or approvals.

Historical and unrevised series of FDI positions aggregates under the previous BMD3 methodology can be accessed in the archived dataset FDI series of BOP and IIP aggregates

Big Ten Countries include Argentina, Brazil, China, India, Indonesia, Mexico, Poland, South Africa, South Korea, and Turkey. The annual data for the years 2002-2019 was used. Growth Rate (GR), the literature’s basic economic variable, is selected as the dependent variable. As for the independent variable, the “Global Terror Index (GTI)” was used to represent the terror indicator. Besides, due to their effect on the growth rate, the ratio of Foreign Direct Investment (FDI) to the Gross Domestic Product (GDP), and the ratio of External Balance (EB) to Gross Domestic Product (GDP) are included in the model as the control variables.

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

The dataset comprises the Quad (Australia, India, Japan, and the United States) member countries’ military expenditure (ME) and related economic indicators, 1991-2020. lnME is logarithms of the Quad member countries’ ME. lnSpillover1 is the product of the Quad member countries’ ME divided by its own ME. lnSpillover2 is logarithms of the sum of the Quad member countries’ ME minus its own ME. lnGDP is the Quad member countries’ GDP. And lnChineseME is logarithms of Chinese ME. lnME_fd is the first difference value of lnME. lnSpillover1_fd is the first difference value of lnSpillover1. lnSpillover2_fd is the first difference value of lnSpillover2. lnGDP_fd is the first difference value of ln lnGDP. And lnChineseME_fd is the first difference value of lnChineseME. IV_1_1 is the 2 periods lagged lnSpillover1_fd. IV_1_2 is logarithms of the first difference value of the product of the Quad member countries’ GDP divided by its own GDP. IV_2_1 is the 2 periods lagged lnSpillover2_fd. IV_2_2 is logarithms of the first difference value of the sum of the Quad member countries’ GDP minus its own GDP. Data on the Quad member countries’ ME (in current US dollars) from 1991–2020 were obtained from Stockholm International Peace Research Institute (2022), and data on their GDP (in current US dollars) during the same period were obtained from World Bank (2022). Further, Chinese ME (in current US dollars) from 1991–2020 were obtained from Stockholm International Peace Research Institute (2022). The data were converted to constant US dollars using the US GDP deflator taken from World Bank (2022). Data source Stockholm International Peace Research Institute. 2022. “SIPRI Military Expenditure Database.” https://www.sipri.org/databases/milex. World Bank. 2022. “World Development Indicators.” https://databank.worldbank.org/source/world-development-indicators.

Multiple regression coefficient and Pearson’s correlation coefficient of total NTL quantity at county level in China.