The Gross Domestic Product (GDP) in the United States was worth 29184.89 billion US dollars in 2024, according to official data from the World Bank. The GDP value of the United States represents 27.49 percent of the world economy. This dataset provides - United States GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Gross Domestic Product (GDP) in the United States expanded 2 percent in the second quarter of 2025 over the same quarter of the previous year. This dataset provides the latest reported value for - United States GDP Annual Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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 Global 15x15 Minute Grids of the Downscaled GDP Based on the Special Report on Emissions Scenarios (SRES) B2 Scenario, 1990 and 2025, are geospatial distributions of Gross Domestic Product (GDP) per Unit area (GDP densities). These global grids were generated using the Country-level GDP and Downscaled Projections Based on the SRES B2 Scenario, 1990-2100 data set, and CIESIN's Gridded Population of World, Version 2 (GPWv2) data set as the base map. First, the GDP per capita was developed at a country-level for 1990 and 2025. Then the gridded GDP was developed within each country by applying the GDP per capita to each grid cell of the GPW, under the assumption that the GDP per capita was uniform within a country. This data set is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

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 main components according to the expenditure approach. Data is presented as growth rates. In the expenditure approach, the components of GDP are: final consumption expenditure of households and non-profit institutions serving households (NPISH) plus final consumption expenditure of General Government plus gross fixed capital formation (or investment) plus net trade (exports minus imports).

When using the filters, please note that final consumption expenditure is shown separately for the Households/NPISH and General Government sectors, not for the whole economy. All other components of GDP are shown for the whole economy, not for the sector breakdowns.

The data is presented for OECD countries individually, as well as the OECD total, G20, G7, OECD Europe, United States - Mexico - Canada Agreement (USMCA), European Union and euro area.

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

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.

The dataset provides quarterly insights into the economic performance of Trinidad and Tobago, focusing on Gross Domestic Product (GDP) at producer prices and other related indicators.

On October 29, 1929, the U.S. experienced the most devastating stock market crash in it's history. The Wall Street Crash of 1929 set in motion the Great Depression, which lasted for twelve years and affected virtually all industrialized countries. In the United States, GDP fell to it's lowest recorded level of just 57 billion U.S dollars in 1933, before rising again shortly before the Second World War. After the war, GDP fluctuated, but it increased gradually until the Great Recession in 2008. Real GDP Real GDP allows us to compare GDP over time, by adjusting all figures for inflation. In this case, all numbers have been adjusted to the value of the US dollar in FY2012. While GDP rose every year between 1946 and 2008, when this is adjusted for inflation it can see that the real GDP dropped at least once in every decade except the 1960s and 2010s. The Great Recession Apart from the Great Depression, and immediately after WWII, there have been two times where both GDP and real GDP dropped together. The first was during the Great Recession, which lasted from December 2007 until June 2009 in the US, although its impact was felt for years after this. After the collapse of the financial sector in the US, the government famously bailed out some of the country's largest banking and lending institutions. Since recovery began in late 2009, US GDP has grown year-on-year, and reached 21.4 trillion dollars in 2019. The coronavirus pandemic and the associated lockdowns then saw GDP fall again, for the first time in a decade. As economic recovery from the pandemic has been compounded by supply chain issues, inflation, and rising global geopolitical instability, it remains to be seen what the future holds for the U.S. economy.

This dataset shows the Gross Domestic Product (GDP) by Kind of Economic Activity at Current Prices, 1987- 2022 (Annual) the value 2021 are estimate the value 2022 are preliminary No. of Views : 111

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.

Graph and download economic data for Nominal Gross Domestic Product for United States (NGDPSAXDCUSQ) from Q1 1950 to Q1 2025 about GDP and USA.

This dataset provides information on the Real GDP per capita for 30 countries and regions across Europe, from 1995 to 2023. The dataset includes real GDP per capita data, which is adjusted for inflation (constant prices), allowing comparisons over time across different countries. This data is critical for economic analysis, providing insights into the economic performance and living standards in these countries and regions.

Countries included are:

• Austria (AT)
• Belgium (BE)
• Bulgaria (BG)
• Cyprus (CY)
• Czech Republic (CZ)
• Germany (DE)
• Denmark (DK)
• Euro Area (EA20) – The 20 countries using the euro
• Estonia (EE)
• Greece (EL)
• Spain (ES)
• European Union 27 (EU27_2020) – EU countries excluding the UK (post-Brexit)
• Finland (FI)
• France (FR)
• Croatia (HR)
• Hungary (HU)
• Ireland (IE)
• Italy (IT)
• Lithuania (LT)
• Luxembourg (LU)
• Latvia (LV)
• Malta (MT)
• Netherlands (NL)
• Poland (PL)
• Portugal (PT)
• Romania (RO)
• Sweden (SE)
• Slovenia (SI)
• Slovakia (SK)

Source:

• Eurostat API (via Python Eurostat library)

Time Period:

• 1995 - 2023

Year:

• The year of the data (1995 to 2023)

Usage:

• This dataset is suitable for economic research, data analysis, and forecasting. It can be used to study trends in economic growth, compare the performance of different European economies, and examine the effects of historical events on national GDP.

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.

Gross domestic product (GDP) measures the value of goods and services produced in the UK. It estimates the size of and growth in the economy. This dataset also contains the Index of Services (monthly movements in output for the services industries) and the Index of Production (movements in the volume of production for the UK production industries: manufacturing, mining and quarrying, energy supply, and water and waste management). Figures are seasonally adjusted.

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

Government spending in the United States was last recorded at 39.7 percent of GDP in 2024 . This dataset provides - United States Government Spending To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

United States US: GDP: % of Manufacturing: Medium and High Tech Industry data was reported at 41.166 % in 2015. This stayed constant from the previous number of 41.166 % for 2014. United States US: GDP: % of Manufacturing: Medium and High Tech Industry data is updated yearly, averaging 49.199 % from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 51.786 % in 1998 and a record low of 38.398 % in 1996. United States US: GDP: % of Manufacturing: Medium and High Tech Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Share of GDP. The proportion of medium and high-tech industry value added in total value added of manufacturing; ; United Nations Industrial Development Organization (UNIDO), Competitive Industrial Performance (CIP) database; ;

This dataset contains Annual GDP using chained dollars from previous period by sector from 1997 to present (most recent as reported by U.S. Bureau of Economic Analysis) for Maryland and United States.

The dataset "tipsau20" has been replaced by "tipsna15" since 10/01/2025. Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units. 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 ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology. Data are seasonally adjusted and presented in million units of national currency.