GDP per capita (current US$) is an economic indicator that measures the average economic output per person in a country. It is calculated by dividing the total Gross Domestic Product (GDP) of a country by its population, both measured in current US dollars. GDP per capita provides a useful metric for comparing the economic well-being and living standards between different countries.

There are various sources where you can find GDP per capita data, including international organizations, government agencies, and financial institutions. Some prominent sources for GDP per capita data include:

1. World Bank: The World Bank provides comprehensive data on GDP per capita for countries around the world. They maintain the World Development Indicators (WDI) database, which includes GDP per capita figures for different years.

2. International Monetary Fund (IMF): The IMF also offers GDP per capita data through their World Economic Outlook (WEO) database. It provides economic indicators and forecasts, including GDP per capita figures for various countries.

3. National Statistical Agencies: Many countries have their own national statistical agencies that publish GDP per capita data. These agencies collect and analyze economic data, including GDP and population figures, to calculate GDP per capita.

4. Central Banks: In some cases, central banks may also provide GDP per capita data for their respective countries. They often publish economic indicators and reports that include GDP per capita figures.

When using GDP per capita data, it's important to note that it represents an average measure and does not necessarily reflect the distribution of wealth within a country. Additionally, GDP per capita figures are often adjusted for inflation to provide real GDP per capita, which accounts for changes in the purchasing power of money over time.

To access the most up-to-date and accurate GDP per capita data, it is recommended to refer to reputable sources mentioned above or consult the official websites of international organizations, government agencies, or central banks that specialize in economic data and analysis.

This dataset provides both quarterly and annual estimates of the value of the goods and services produced in Iowa as provided by the U.S. Department of Commerce, Bureau of Economic Analysis in tables SAGDP2N, SAGDP9N, SAGDP10N, SQGDP2, and SQGDP9. Annual data is available beginning in 1997, and quarterly beginning 2005. The data include breakdowns of industries' contributions. Quarterly estimates are presented as an annual rate. Gross domestic product (GDP) is the measure of the market value of all final goods and services produced within Iowa in a particular period of time. In concept, an industry's GDP by state, referred to as its "value added", is equivalent to its gross output (sales or receipts and other operating income, commodity taxes, and inventory change) minus its intermediate inputs (consumption of goods and services purchased from other U.S. industries or imported). The Iowa GDP a state counterpart to the Nation's GDP, the Bureau's featured and most comprehensive measure of U.S. economic activity. Iowa GDP differs from national GDP for the following reasons: Iowa GDP excludes and national GDP includes the compensation of federal civilian and military personnel stationed abroad and government consumption of fixed capital for military structures located abroad and for military equipment, except office equipment; and Iowa GDP and national GDP have different revision schedules. GDP is reported in millions of current dollars. Real GDP is an inflation-adjusted measure of Iowa's gross product that is based on national prices for the goods and services produced within Iowa. The real estimates of gross domestic product (GDP) are measured in millions of chained dollars. The annual per capita real GDP is also provided and is measured in chained dollars. In calculating the per capita real GDP, the real GDP is divided by the Census Bureau’s annual midyear (July 1) population estimates for the year.

505 Economics is on a mission to make academic economics accessible. We've developed the first monthly sub-national GDP data for EU and UK regions from January 2015 onwards.

Our GDP dataset uses luminosity as a proxy for GDP. The brighter a place, the more economic activity that place tends to have.

We produce the data using high-resolution night time satellite imagery and Artificial Intelligence.

This builds on our academic research at the London School of Economics, and we're producing the dataset in collaboration with the European Space Agency BIC UK.

We have published peer-reviewed academic articles on the usage of luminosity as an accurate proxy for GDP.

Key features:

• Granular: Data is provided at the following geographical units:
  • NUTS3 (e.g. London Boroughs),
  • NUTS2 (e.g. London),
  • NUTS1 (e.g. England), and
  • NUTS0 (e.g. United Kingdom) levels.
• Frequent: Data is provided every month from January 2015. This is more frequent than the annualised official datasets.
• Timely: Data is provided with a one month lag (i.e. the data for January 2021 was published at the end of February 2021). This is substantially quicker than the 18 month lag of official datasets.
• Accurate: Our dataset uses Deep Learning to maximise accuracy (RMSE 1.2%).

The dataset can be used by:

• Governments and policy makers - to monitor the performance of local economies, to measure the localised impact of policies, and to get a real-time indication of economic activity.
• Financial services - to get an indication of national-level GDP before official GDP statistics are released
• Engineering companies - to monitor and evaluate the localised impact of infrastructure projects
• Consultancies - to forecast the localised impact of specific projects, to retrospectively monitor and evaluate the localised impact of existing projects
• Economics firms - to create macro forecasts at the national and sub-national level, to assess the impact of policy interventions.
• Academia / Think Tanks - to conduct novel research at the local level. E.g. our dataset can be used to measure the impact of localised COVID-19 lockdowns.

We have created this dataset for all UK sub-national regions, 28 EU Countries and Switzerland.

Gross Domestic Product (GDP) is a measure of the economic production which takes place within the geographical boundaries of a province or country. It can be measured at basic prices (by industry) or at market prices.

Gross Domestic Product (GDP) is one of the best known indicators of economic activity and is widely used to monitor economic performance. GDP statistics for Scotland are produced by the Scottish Government and have been designated as National Statistics. This dataset contains statistics for the output approach to GDP and growth in real terms, and includes results for the whole economy (Total GDP) and industry sectors. GDP can also be broken down using the income and expenditure approaches, which are available as separate datasets. There are two updates to the output by industry statistics each quarter. The First Estimate of GDP growth is published around 80 days after the quarter’s end, and an updated second estimate is published in the Quarterly National Accounts around 120 days after the quarter’s end. The First Estimate of GDP statistics will be published on this website as open data; the Second Estimate will not currently be available as open data, but will be available on the Scottish Government website. Results for previous periods are also open to revision each quarter. Further details on Scottish GDP statistics, including methodology notes and the revisions policy, are available. The Industry Sector dimension in this dataset contains the broad industry sectors used on GDP statistics for Scotland the UK. These are based on industry sections from the Standard Industrial Classification (SIC, 2007). Further information can be found here The Measure Type dimension in this dataset contains four GDP measures, detailed below. The index measure is rounded to 4 decimal places and the growth rate measures are rounded to 1 decimal place. It is not always possible to replicate the published growth rates using rounded data, but all results are also available unrounded in the downloadable spreadsheets from the latest publication. • 4Q-on-4Q is the percentage change (growth rate) for the latest four quarters compared to the previous four non-overlapping quarters. This rolling annual growth rate gives a smoothed measure of recent trends. This growth rate is calculated from the Index measure. • Index represents the level of output in real, or volume, terms for each industry or total GDP, relative to the base year (2019). An index value of more than 100 means that output is higher than in the base year, and a value of less than 100 means that output is lower than in the base year. • q-on-q is the percentage change (growth rate) for the latest quarter compared to the previous quarter. This quarterly growth rate is usually taken as the headline measure of GDP growth. This growth rate is calculated from the Index measure. • q-on-q year ago is the percentage change (growth rate) for the latest quarter compared to the same quarter in the previous year. This growth rate over the year is usually compared to other statistics such as earnings or price inflation. This growth rate is calculated from the Index measure. The Reference Period dimension relates to standard calendar quarters. Quarter 1 refers to the period from January to March, Quarter 2 refers to April to June, Quarter 3 refers to July to September, and Quarter 4 refers to October to December. The Reference Area dimension for this dataset only contains results for Scotland, with no breakdowns to other areas. In this dataset, all results relate to Scotland’s onshore economy and do not include the output of offshore oil and gas extraction in Scottish Adjacent Waters. Each industry sector is indexed to make them comparable. For each sector, the value during 2019 is taken as the base year, and given the value of 100. All indexed values are chainlinked volume measures, and given relative to the base year.

Quarterly levels for UK gross domestic product (GDP), in chained volume measures at market prices.

The dataset provides annual insights into the economic performance of Trinidad and Tobago, focusing on Gross Domestic Product (GDP) at producer prices and other related indicators. Gross domestic product (GDP) is the total monetary or market value of all the finished goods and services produced within a country’s borders in a specific time period. As a broad measure of overall domestic production, it is a comprehensive scorecard of a country’s economic health.

Annual and quarterly data for UK gross domestic product (GDP) estimates, in chained volume measures and current market prices.

The Gross Domestic Product (GDP) in Japan was worth 4026.21 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Japan represents 3.79 percent of the world economy. This dataset provides - Japan GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This table presents annual data on the output components, the final expenditure categories and the income components of gross domestic product of the Netherlands. In the national accounts gross domestic product is approached from three points of view: from the output, from the generation of income and from the final expenditure. Gross domestic product is a main macroeconomic indicator. The volume change of gross domestic product is a measure for the economic growth of a country. Data available from: 1969 up to and including 2016. Status of the figures: Data from 1969 up to and including 2015 are final. Data of 2016 are provisional. Since this table has been discontinued, data of 2016 will not become final. Changes as of June 22nd 2018: None. This table has been discontinued. Statistics Netherlands has carried out a revision of the national accounts. New statistical sources and estimation methods have been used during the revision. Therefore this table has been replaced by table Approaches of domestic product (GDP); National Accounts. For further information see section 3. When will new figures be published? Not applicable anymore.

505 Economics is on a mission to make academic economics accessible. We've developed the first monthly sub-national GDP data for EU and UK regions from January 2015 onwards.

Our GDP dataset uses luminosity as a proxy for GDP. The brighter a place, the more economic activity that place tends to have.

We produce the data using high-resolution night time satellite imagery and Artificial Intelligence.

This builds on our academic research at the London School of Economics, and we're producing the dataset in collaboration with the European Space Agency BIC UK.

We have published peer-reviewed academic articles on the usage of luminosity as an accurate proxy for GDP.

Key features: - Frequent: Data is provided every month from January 2015. This is more frequent than quarterly official datasets. - Timely: Data is provided with a three week lag (i.e. the data for January 2021 was published at the end of February 2021). This is substantially quicker than the 3-6 month lag of official datasets. - Accurate: Our dataset uses Deep Learning to maximise accuracy (RMSE 1.2%).

The dataset can be used by:

• Financial services - to get an indication of national-level GDP before official GDP statistics are released
• Governments and policy makers - to monitor the performance of economies, to measure the impact of policies, and to get a real-time indication of economic activity.
• Engineering companies - to monitor and evaluate the national impact of infrastructure projects
• Consultancies - to forecast the national impact of specific projects, to retrospectively monitor and evaluate the localised impact of existing projects
• Economics firms - to create macro forecasts at the national, to assess the impact of policy interventions.
• Academia / Think Tanks - to conduct novel research with more-frequent GDP data than is available from official sources. E.g. our dataset can be used to measure the impact of localised COVID-19 lockdowns.

We have created this dataset for the UK, Switzerland and 28 EU Countries.

505 Economics is on a mission to make academic economics accessible. We've developed the first monthly sub-national GDP data for EU and UK regions from January 2015 onwards.

Our GDP dataset uses luminosity as a proxy for GDP. The brighter a place, the more economic activity that place tends to have.

We produce the data using high-resolution night time satellite imagery and Artificial Intelligence.

This builds on our academic research at the London School of Economics, and we're producing the dataset in collaboration with the European Space Agency BIC UK.

We have published peer-reviewed academic articles on the usage of luminosity as an accurate proxy for GDP.

Key features:

• Granular: Data is provided at the following geographical units:
  • NUTS3 (e.g. Barcelona),
  • NUTS2 (e.g. Cataluna),
  • NUTS1 (e.g. Este), and
  • NUTS0 (e.g. Spain) levels.
• Frequent: Data is provided every month from January 2015. This is more frequent than the annualised official datasets.
• Timely: Data is provided with a one month lag (i.e. the data for January 2021 was published at the end of February 2021). This is substantially quicker than the 18 month lag of official datasets.
• Accurate: Our dataset uses Deep Learning to maximise accuracy (RMSE 1.2%).

The dataset can be used by:

• Governments and policy makers - to monitor the performance of local economies, to measure the localised impact of policies, and to get a real-time indication of economic activity.
• Financial services - to get an indication of national-level GDP before official GDP statistics are released
• Engineering companies - to monitor and evaluate the localised impact of infrastructure projects
• Consultancies - to forecast the localised impact of specific projects, to retrospectively monitor and evaluate the localised impact of existing projects
• Economics firms - to create macro forecasts at the national and sub-national level, to assess the impact of policy interventions.
• Academia / Think Tanks - to conduct novel research at the local level. E.g. our dataset can be used to measure the impact of localised COVID-19 lockdowns.

We have created this dataset for all UK sub-national regions, 28 EU Countries and Switzerland.

505 Economics is on a mission to make academic economics accessible. We've developed the first monthly sub-national GDP data for EU and UK regions from January 2015 onwards.

Our GDP dataset uses luminosity as a proxy for GDP. The brighter a place, the more economic activity that place tends to have.

We produce the data using high-resolution night time satellite imagery and Artificial Intelligence.

This builds on our academic research at the London School of Economics, and we're producing the dataset in collaboration with the European Space Agency BIC UK.

We have published peer-reviewed academic articles on the usage of luminosity as an accurate proxy for GDP.

Key features:

• Granular: Data is provided at the following geographical units:
  • NUTS3 (e.g. Provinces),
  • NUTS2 (e.g. Regions),
  • NUTS1 (e.g. Macroregions), and
  • NUTS0 (e.g. Italy) levels.
• Frequent: Data is provided every month from January 2015. This is more frequent than the annualised official datasets.
• Timely: Data is provided with a one month lag (i.e. the data for January 2021 was published at the end of February 2021). This is substantially quicker than the 18 month lag of official datasets.
• Accurate: Our dataset uses Deep Learning to maximise accuracy (RMSE 1.2%).

The dataset can be used by:

• Governments and policy makers - to monitor the performance of local economies, to measure the localised impact of policies, and to get a real-time indication of economic activity.
• Financial services - to get an indication of national-level GDP before official GDP statistics are released
• Engineering companies - to monitor and evaluate the localised impact of infrastructure projects
• Consultancies - to forecast the localised impact of specific projects, to retrospectively monitor and evaluate the localised impact of existing projects
• Economics firms - to create macro forecasts at the national and sub-national level, to assess the impact of policy interventions.
• Academia / Think Tanks - to conduct novel research at the local level. E.g. our dataset can be used to measure the impact of localised COVID-19 lockdowns.

We have created this dataset for all UK sub-national regions, 28 EU Countries and Switzerland.

This table presents Gross Domestic Product (GDP) and its components according to the income approach. In the income approach, GDP is measured as the sum of compensation of employees (wages and salaries paid to employees and their employers’ social contributions), plus gross operating surplus (business profits) and gross mixed income (profits of the self-employed), plus taxes on production and imports less subsidies.

Data is presented for each country in national currency as well as in euros for the European Union and the euro area. The presentation is on a country-by-country basis. Users are recommended to select one country (or area) at a time in the ‘Reference area’ filter.

These indicators were presented in the previous dissemination system in the QNA dataset.
See User Guide on Quarterly National Accounts (QNA) in OECD Data Explorer: QNA User guide
See QNA Calendar for information on advance release dates: QNA Calendar
See QNA Changes for information on changes in methodology: QNA Changes
See QNA TIPS for a better use of QNA data: QNA TIPS
Explore also the GDP and non-financial accounts webpage: GDP and non-financial accounts webpage
OECD statistics contact: STAT.Contact@oecd.org

Quarterly estimates of £ million levels from 1997 to 2015.

Breakdown of all the data sources that feed into the output measure of Gross Domestic Product.

Get data on the Ontario gross domestic product (GDP) by Goods-Producing Industries and Services Industries.

The GDP is a monetary measure of the value of all the goods and services produced in a period.

Data from 1st of June 2022. For most recent GDP data, consult dataset nama_10_gdp. Gross domestic product (GDP) is a measure for the economic activity. It is defined as the value of all goods and services produced less the value of any goods or services used in their creation. The volume index of GDP per capita in Purchasing Power Standards (PPS) is expressed in relation to the European Union average set to equal 100. If the index of a country is higher than 100, this country's level of GDP per head is higher than the EU average and vice versa. Basic figures are expressed in PPS, i.e. a common currency that eliminates the differences in price levels between countries allowing meaningful volume comparisons of GDP between countries. Please note that the index, calculated from PPS figures and expressed with respect to EU27_2020 = 100, is intended for cross-country comparisons rather than for temporal comparisons."

Gross Domestic Product (GDP) is a measure of the economic production which takes place within the geographical boundaries of a province or country. It can be measured at basic prices (by industry) or at market prices.

Recent years have seen many attempts to combine expenditure-side estimates of U.S. real output (GDE) growth with income-side estimates (GDI) to improve estimates of real GDP growth. We show how to incorporate information from multiple releases of noisy data to provide more precise estimates while avoiding some of the identifying assumptions required in earlier work. This relies on a new insight: using multiple data releases allows us to distinguish news and noise measurement errors in situations where a single vintage does not. We find that (a) the data prefer averaging across multiple releases instead of discarding early releases in favor of later ones, and (b) that initial estimates of GDI are quite informative. Our new measure, GDP++, undergoes smaller revisions and tracks expenditure measures of GDP growth more closely than either the simple average of the expenditure and income measures published by the BEA or the GDP growth measure of Aruoba et al. published by the Federal Reserve Bank of Philadelphia.