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 3.30 percent in the second quarter of 2025 over the previous quarter. This dataset provides the latest reported value for - United States GDP Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

View economic output, reported as the nominal value of all new goods and services produced by labor and property located in the U.S.

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.

The Economic Census is the U.S. Government's official five-year measure of American business and the economy. It is conducted by the U.S. Census Bureau, and response is required by law. In October through December of the census year, forms are sent out to nearly 4 million businesses, including large, medium and small companies representing all U.S. locations and industries. Respondents were asked to provide a range of operational and performance data for their companies.

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.

In 2024, the U.S. GDP increased from the previous year to about 29.18 trillion U.S. dollars. Gross domestic product (GDP) refers to the market value of all goods and services produced within a country. In 2024, the United States has the largest economy in the world. What is GDP? Gross domestic product is one of the most important indicators used to analyze the health of an economy. GDP is defined by the BEA as the market value of goods and services produced by labor and property in the United States, regardless of nationality. It is the primary measure of U.S. production. The OECD defines GDP as an aggregate measure of production equal to the sum of the gross values added of all resident, institutional units engaged in production (plus any taxes, and minus any subsidies, on products not included in the value of their outputs). GDP and national debt Although the United States had the highest Gross Domestic Product (GDP) in the world in 2022, this does not tell us much about the quality of life in any given country. GDP per capita at purchasing power parity (PPP) is an economic measurement that is thought to be a better method for comparing living standards across countries because it accounts for domestic inflation and variations in the cost of living. While the United States might have the largest economy, the country that ranked highest in terms of GDP at PPP was Luxembourg, amounting to around 141,333 international dollars per capita. Singapore, Ireland, and Qatar also ranked highly on the GDP PPP list, and the United States ranked 9th in 2022.

Graph and download economic data for Real gross domestic product per capita (A939RX0Q048SBEA) from Q1 1947 to Q2 2025 about per capita, real, GDP, and USA.

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.

The United States recorded a Government Debt to GDP of 124.30 percent of the country's Gross Domestic Product in 2024. This dataset provides - United States Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Key information about United States Government Debt: % of GDP

• United States Government debt accounted for 124.0 % of the country's Nominal GDP in Dec 2024, compared with the ratio of 123.1 % in the previous quarter.
• US government debt to GDP ratio data is updated quarterly, available from Mar 1969 to Dec 2024.
• The data reached an all-time high of 130.4 % in Mar 2021 and a record low of 31.8 % in Sep 1974.

CEIC calculates quarterly Government Debt as % of Nominal GDP from monthly Government Debt and rolling sum of quarterly Nominal GDP. The Bureau of the Fiscal Service provides Government Debt in USD. The Bureau of Economic Analysis provides Nominal GDP in USD. Government Debt covers Central Government only.


Related information about United States Government Debt: % of GDP

• In the latest reports, US National Government Debt reached 36,220.2 USD bn in Jan 2025.
• The country's Nominal GDP reached 6,632.4 USD bn in Mar 2023.

The Business Dynamics Statistics (BDS) is a public use data set providing annual aggregate measures of establishment openings and closings, firm startups and shutdowns, and job creation and destruction. These measures are available for the entire economy, and by industrial sector, 3-digit and 4-digit NAICS, state, MSA, and county. They are also available by firm and establishment size and age. For more information about the dataset see: https://www.census.gov/programs-surveys/bds.html

Context

This dataset expands on my earlier New York City Census Data dataset. It includes data from the entire country instead of just New York City. The expanded data will allow for much more interesting analyses and will also be much more useful at supporting other data sets.

Content

The data here are taken from the DP03 and DP05 tables of the 2015 American Community Survey 5-year estimates. The full datasets and much more can be found at the American Factfinder website. Currently, I include two data files:

1. acs2015_census_tract_data.csv: Data for each census tract in the US, including DC and Puerto Rico.
2. acs2015_county_data.csv: Data for each county or county equivalent in the US, including DC and Puerto Rico.

The two files have the same structure, with just a small difference in the name of the id column. Counties are political subdivisions, and the boundaries of some have been set for centuries. Census tracts, however, are defined by the census bureau and will have a much more consistent size. A typical census tract has around 5000 or so residents.

The Census Bureau updates the estimates approximately every year. At least some of the 2016 data is already available, so I will likely update this in the near future.

Acknowledgements

The data here were collected by the US Census Bureau. As a product of the US federal government, this is not subject to copyright within the US.

Inspiration

There are many questions that we could try to answer with the data here. Can we predict things such as the state (classification) or household income (regression)? What kinds of clusters can we find in the data? What other datasets can be improved by the addition of census data?

In July 2024, the merchandise exports index worldwide, excluding the U.S., stood at 204.8. This is compared to an index value of 143 for the United States in the same month. The index was highest in emerging economies, reaching an index score of 353. Moreover, the merchandise imports index was also highest in emerging economies. The merchandise exports index is the U.S. dollar value of goods sold to the rest of the world, deflated by the U.S. Consumer Price Index (CPI).

Weather Conditions and Economic Analysis

Investigating the Relationship between Weather and Economic Activity

By [source]

About this dataset

This dataset consists of detailed information about the weather conditions in different cities from one of the official weather websites. It includes several variables including temperature, humidity, pressure, wind speed and direction, precipitation levels, cloud cover etc. which can be used to analyze the correlation between economic activities in these cities and their weather conditions. For example, this data can help us understand how certain types of business like tourism, retail or leisure activities are affected by changes in temperature and humidity levels. Additionally, it allows us to identify which specific kind of weather has more economic impact in a certain region and thus create accurate forecasts which could further improve commercial performances. All in all, this dataset is an invaluable source of information for people interested in understanding the relation between climate dynamics and economic outcomes

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How to use the dataset

• City Name: This column provides the name of the cities covered in this dataset.
• Weather Condition: This column lists the weather conditions associated with each city, such as sunny, cloudy, windy, etc.
• Temperature (C): This column provides the temperature (in Celsius) of each city as provided by official weather sources.
• Population: This column lists the population size (in millions) of each city covered in this dataset.
• GDP Per Capita: This column presents GDP per capita (measured in US Dollars) for each city included in our dataset 6 Economic Activity Index: This index measures economic activity levels for a particular state or region and can be used to analyze how different weather conditions affect economic activities such as tourism, retail, and leisure activities

How to use this dataset?

This dataset can be used to explore relationships between different factors that might influence economic activity levels at a regional level—namely population size and wealth as well as weather condition—or across countries over time and certain seasons or months to identify trends in regional differences between regions regarding their respective economics activities levels due to varying climates or meteorological events . Some specific analysis that could be done includes:

• Use City Name & Weather Condition columns together to calculate correlations between types of weather patterns/conditions seen throughout different locales; temperatures could also potentially be included for more comprehensive data exploration/analysis on climate dynamics - research on how “cold” vs “warm” periods affect local economies overall would also benefit from including these two columns together;

• Analyze Population & Economic Activity Index together - use these variables together to see if any correlation exists between populations sizes within a given region versus their respective economic performance level; other related variables such as GDP Per Capita could also potentially provide valuable insight into how economic activity varies depending on population density;

• Using all 6 columns together would enable even more comprehensive analysis e..g comparing temperatures & storm information versus expected tourist visits data or analyzing effects/correlations between strong winds & droughts versus changes seen within agricultural outputs . With careful combination of all 6 columns you could easily create some interesting models & computations for understanding broad implications which climate dynamics have upon global economics ; conversely you may explore individual cities too!

Research Ideas

• Use this dataset to analyze the correlation between weather conditions and consumer sentiment by comparing customer purchasing decisions in different cities under different weather conditions.
• Use this dataset to identify the optimal temperature for selling certain products, so that retailers can optimize their prices accordingly.
• Use this dataset to study how changes in weather influencers the types of transportation used by the population of a certain city, and help suggest improvements to public systems for better customer experience in changing climate situations

Acknowledgements

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

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In July 2024, the global merchandise imports index, excluding the U.S., stood at 192.6. This is compared to a value of 121 for the United States in the same period. In emerging economies, it reached an index level of nearly 291.4.The merchandise imports index is the U.S. dollar value of goods bought from the rest of the world, deflated by the U.S. Consumer Price Index (CPI).

In July 2024, global industrial production, excluding the United States, increased by 1.5 percent compared to the same time in the previous year, based on three month moving averages. This is compared to an increase of 0.2 percent in advanced economies (excluding the United States) for the same time period. The global industrial production collapsed after the outbreak of COVID-19, but increased steadily in the months after, peaking at 23 percent in June 2021. Industrial growth rate tracks the output production in the industrial sector.

Consumer Spending in the United States increased to 16350.20 USD Billion in the second quarter of 2025 from 16291.80 USD Billion in the first quarter of 2025. This dataset provides the latest reported value for - United States Consumer Spending - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study measures the size and structure of the underground commercial sex economy in eight major US cities: San Diego, Seattle, Dallas, Denver, Washington, DC, Kansas City, Atlanta, and Miami. The goals of this study were to derive a more rigorous estimate of the underground commercial sex economy (UCSE) in eight major US cities and to provide an understanding of the structure of this underground economy. Researchers relied on a multi-method approach using both qualitative and quantitative data to estimate the size of UCSE including: Collecting official data on crime related to the underground weapons and drugs economies Conducting semi-structured interviews with convicted traffickers, pimps, child pornographers, and sex workers at the federal, state, and local levels Conducting semi-structured interviews with local and federal police investigators and prosecutors to inform our analysis of the interrelationship across different types of underground commercial sex activity.

Graph and download economic data for Dates of U.S. recessions as inferred by GDP-based recession indicator (JHDUSRGDPBR) from Q4 1967 to Q1 2025 about recession indicators, GDP, and USA.