Gross domestic product ranking table.

The statistic shows the gross domestic product (GDP) per capita in India from 1987 to 2029. 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.

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.

This data file includes the Gini coefficient calculated for different wealth welfare aggregates constructed for all Luxembourg Wealth Study (LWS) datasets in all waves (as of March 2022). It includes Gini coefficients calculated on: • Disposable Net Worth • Value of Principal residence • Financial Assets

This project sought to renew the ESRC's invaluable financial support to LIS (formerly the Luxembourg Income Study) for a period of five more years. LIS is an independent, non-profit cross-national data archive and research institute located in Luxembourg. LIS relies on financial contributions from national science foundations, other research institutions and consortia, data-providing agencies, and supranational organisations to support data harmonisation and enable free and unlimited data access to researchers in the participating countries and to students world-wide. LIS' primary activity is to make harmonised household microdata available to researchers, thus enabling cross-national, interdisciplinary primary research into socio-economic outcomes and their determinants. Users of the Luxembourg Income Study Database and Luxembourg Wealth Study Database come from countries around the globe, including the UK. LIS has four goals: 1) to harmonise microdatasets from high- and middle-income countries that include data on income, wealth, employment, and demography; 2) to provide a secure method for researchers to query data that would otherwise be unavailable due to country-specific privacy restrictions; 3) to create and maintain a remote-execution system that sends research query results quickly back to users at off-site locations; and 4) to enable, facilitate, promote and conduct crossnational comparative research on the social and economic wellbeing of populations across countries. LIS contains the Luxembourg Income Study (LIS) Database, which includes income data, and the Luxembourg Wealth Study (LWS) Database, which focuses on wealth data. LIS currently includes microdata from 46 countries in Europe, the Americas, Africa, Asia and Australasia. LIS contains over 250 datasets, organised into eight time "waves," spanning the years 1968 to 2011. Since 2007, seventeen more countries have been added to LIS, including the BRICS countries (Brazil, Russia, India, China, South Africa), Japan, South Korea and a number of other Latin American countries. LWS contains 20 wealth datasets from 12 countries, including the UK, and covers the period 1994 to 2007. All told, LIS and LWS datasets together cover 86% of world GDP and 64% of world population. Users submit statistical queries to the microdatabases using a Java-based job submission interface or standard email. The databases are especially valuable for primary research in that they offer access to cross-national data at the micro-level - at the level of households and persons. Users are economists, sociologists, political scientists, and policy analysts, among others, and they employ a range of statistical approaches and methods. LIS also provides extensive documentation - metadata - for both LIS and LWS, concerning technical aspects of the survey data, the harmonisation process, and the social institutions of income and wealth provision in participating countries. In the next five years, for which support is sought, LIS will: - expand LIS, adding Waves IX (2013) and X (2016), and add new middle-income countries; - develop LWS, adding another wave of datasets to existing countries; acquire new wealth datasets for 14 more countries in cooperation with the European Central Bank (based on the Household Finance and Consumption Survey); - create a state-of-the-art metadata search and storage system; - maintain international standards in data security and data infrastructure systems; - provide high-quality harmonised household microdata to researchers around the world; - enable interdisciplinary cross-national social science research covering 45+ countries, including the UK; - aim to broaden its reach and impact in academic and non-academic circles through focused communications strategies and collaborations.

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.

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

This dataset provides a summary of government spending on healthcare, presented as a share of a country's GDP, for the years 2000–2020. The summary contains data for selected European countries, including Poland, the US, China, and India.

Explore Green Bond Issuances by Country, Sovereign Green Bond Issuances, Cumulative Green Bond Issuances, and more on this dataset webpage.

Green Bond Issuances by Country, Sovereign Green Bond Issuances, Cumulative Green Bond Issuances, Cumulative Green Bond Issuances by Type of Currency, Environment, Climate Change, Financial and Physical and Transition Risk Indicators, Green Bonds, Green Bond Issuances (All Countries), US Dollars, Green Bond Issuances by Type of Issuers, Green Bonds Issuances, Green Bonds, Environment, Climate Change, Financial and Physical and Transition Risk Indicators, Green Bonds, Green Bonds Issuances, All, International Organization, State owned entities, Banks, Nonfinancial corporations, Local and state Government, Other financial corporations, Sovereign, Access to Essential Services, Acquisition, Affordable Basic Infrastructure, Capital expenditure/Financing expenses, Carbon reduction through reforestation and avoided deforestation, E-education programs - Education Projects, Economic Development, Funding new technologies to reduce GHS emissions, General Purpose/Acquisition, Pollution Control, Production/Supply of Cannabis, Sustainable Management of Living Natural Resources, Wind projects, Capital expenditure, Electric & Public Power, General Purpose/Working Capital, Green Construction/Buildings, Merger or Acquisition, Other, Project Finance, Refinance/Financing expenses, Repay Bank Loan or Bridge Financing, China Municipal Development, Employee stock ownership plan, Environmentally Sustainable Products, Equipment Upgrade/Construction, General Purpose, Industrial Development, Infrastructure, Land Preservation, Other Education, Other Public Service, Repay Intercompany Debt, Solar projects, Sustainable Management of Land Use, Sustainable Water or Wastewater management, The Belt and Road Initiative, Acquiring and distribution of vaccine, Alternative Energy, Aquatic Biodiversity Conservation, Clean Transport, Climate Change Adaptation, Environmental Protection Projects, Other Housing, Other Transportation, Pollution Prevention & Control, Redeem Existing Bonds or Securities, Water & Sewer, Working capital, Circular Economy Adapted/Eco-efficient Products, Production Technologies/Processes, Eligible Green Projects, Energy Efficiency, Financing of Subordinated Loan, Gas, General Purpose/Refinance, Property Expendit (acquisit/development), Renewable Energy Projects, Waste Management, Green bond, Sustainable finance



Argentina, Australia, Austria, Bangladesh, Belgium, Brazil, Canada, Chile, China, Colombia, Costa Rica, Denmark, Egypt, Estonia, Fiji, Finland, France, Georgia, Germany, Greece, Hungary, Iceland, India, Indonesia, Ireland, Israel, Italy, Japan, Kazakhstan, Latvia, Liechtenstein, Lithuania, Luxembourg, Malaysia, Marshall Islands, Mauritius, Mexico, Morocco, Namibia, Netherlands, New Zealand, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Peru, Philippines, Poland, Portugal, Romania, Russia, Serbia, Seychelles, Singapore, Slovenia, South Africa, South Korea, Spain, Sri Lanka, Sweden, Switzerland, Thailand, Turkey, Ukraine, United Arab Emirates, United Kingdom, Vietnam

Follow data.kapsarc.org for timely data to advance energy economics research..Important notesexcluding international organizations type of currency and type of issuers (nonfinancial corporations, other financial corporations, banks, state owned entities, sovereign, state and local governments and international organizations).

This data file includes the Inequality and Poverty Key Figures (as of March 2022), constructed for all Luxembourg Income Study (LIS) Study datasets in all waves. It includes multiple national-level measures: • on inequality measures: Gini, Atkinson coefficients, and percentile ratios • on relative poverty rates for various demographic groups • median and mean of disposable household income

This project sought to renew the ESRC's invaluable financial support to LIS (formerly the Luxembourg Income Study) for a period of five more years. LIS is an independent, non-profit cross-national data archive and research institute located in Luxembourg. LIS relies on financial contributions from national science foundations, other research institutions and consortia, data-providing agencies, and supranational organisations to support data harmonisation and enable free and unlimited data access to researchers in the participating countries and to students world-wide. LIS' primary activity is to make harmonised household microdata available to researchers, thus enabling cross-national, interdisciplinary primary research into socio-economic outcomes and their determinants. Users of the Luxembourg Income Study Database and Luxembourg Wealth Study Database come from countries around the globe, including the UK. LIS has four goals: 1) to harmonise microdatasets from high- and middle-income countries that include data on income, wealth, employment, and demography; 2) to provide a secure method for researchers to query data that would otherwise be unavailable due to country-specific privacy restrictions; 3) to create and maintain a remote-execution system that sends research query results quickly back to users at off-site locations; and 4) to enable, facilitate, promote and conduct crossnational comparative research on the social and economic wellbeing of populations across countries. LIS contains the Luxembourg Income Study (LIS) Database, which includes income data, and the Luxembourg Wealth Study (LWS) Database, which focuses on wealth data. LIS currently includes microdata from 46 countries in Europe, the Americas, Africa, Asia and Australasia. LIS contains over 250 datasets, organised into eight time "waves," spanning the years 1968 to 2011. Since 2007, seventeen more countries have been added to LIS, including the BRICS countries (Brazil, Russia, India, China, South Africa), Japan, South Korea and a number of other Latin American countries. LWS contains 20 wealth datasets from 12 countries, including the UK, and covers the period 1994 to 2007. All told, LIS and LWS datasets together cover 86% of world GDP and 64% of world population. Users submit statistical queries to the microdatabases using a Java-based job submission interface or standard email. The databases are especially valuable for primary research in that they offer access to cross-national data at the micro-level - at the level of households and persons. Users are economists, sociologists, political scientists, and policy analysts, among others, and they employ a range of statistical approaches and methods. LIS also provides extensive documentation - metadata - for both LIS and LWS, concerning technical aspects of the survey data, the harmonisation process, and the social institutions of income and wealth provision in participating countries. In the next five years, for which support is sought, LIS will: - expand LIS, adding Waves IX (2013) and X (2016), and add new middle-income countries; - develop LWS, adding another wave of datasets to existing countries; acquire new wealth datasets for 14 more countries in cooperation with the European Central Bank (based on the Household Finance and Consumption Survey); - create a state-of-the-art metadata search and storage system; - maintain international standards in data security and data infrastructure systems; - provide high-quality harmonised household microdata to researchers around the world; - enable interdisciplinary cross-national social science research covering 45+ countries, including the UK; - aim to broaden its reach and impact in academic and non-academic circles through focused communications strategies and collaborations.

Multiple regression coefficient and Pearson’s correlation coefficient of NTL density at provincial level in China.

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

The statistic shows the unemployment rate in India from 1999 to 2023. In 2023, the unemployment rate in India was estimated to be 4.17 percent. India's economy in comparison to other BRIC states India possesses one of the fastest-growing economies in the world and as a result, India is recognized as one of the G-20 major economies as well as a member of the BRIC countries, an association that is made up of rapidly growing economies. As well as India, three other countries, namely Brazil, Russia and China, are BRIC members. India’s manufacturing industry plays a large part in the development of its economy; however its services industry is the most significant economical factor. The majority of the population of India works in this sector. India’s notable economic boost can be attributed to significant gains over the past decade in regards to the efficiency of the production of goods as well as maintaining relatively low debt, particularly when compared to the total amount earned from goods and services produced throughout the years. When considering individual development as a country, India progressed significantly over the years. However, in comparison to the other emerging countries in the BRIC group, India’s progress was rather minimal. While China experienced the most apparent growth, India’s efficiency and productivity remained somewhat stagnant over the course of 3 or 4 years. India also reported a rather large trade deficit over the past decade, implying that its total imports exceeded its total amount of exports, essentially forcing the country to borrow money in order to finance the nation. Most economists consider trade deficits a negative factor, especially in the long run and for developing or emerging countries.

This page displays a table with China Exports By Country in U.S. dollars, according to the United Nations COMTRADE database on international trade.