United States US: GDP: Growth: Gross Value Added: Services data was reported at 2.621 % in 2015. This records an increase from the previous number of 2.221 % for 2014. United States US: GDP: Growth: Gross Value Added: Services data is updated yearly, averaging 2.335 % from Dec 1998 (Median) to 2015, with 18 observations. The data reached an all-time high of 4.456 % in 1999 and a record low of -1.772 % in 2009. United States US: GDP: Growth: Gross Value Added: Services 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: Annual Growth Rate. Annual growth rate for value added in services based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers as well as discrepancies arising from rescaling. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted Average; Note: Data for OECD countries are based on ISIC, revision 4.

In 2024, the finance, real estate, insurance, rental, and leasing industry added the most value to the GDP of the United States. In that year, this industry added 6.2 trillion U.S. dollars to the national GDP. Gross Domestic Product Gross domestic product is a measure of how much a country produces in a certain amount of time. Countries with a high GDP tend to have large economies, for example, the United States. However, GDP does not take into consideration the cost of living and inflation rates, so it is not a good measure of the standard of living. GDP per capita at purchasing power parity is thought to be more reflective of living conditions within a particular country. U.S. GDP California added the largest amount of value to the real GDP of the U.S. in 2022. California was followed by Texas and New York. In California, the professional and business services industry was the most valuable to GDP in 2022. In New York, the finance, insurance, real estate, rental, and leasing industry added the most value to the state GDP. While the business sector added the highest value to the U.S. real GDP in 2021, it was the information industry that had the biggest percentage change in value added to the GDP between 2010 and 2021.

United States US: GDP: USD: Gross National Income data was reported at 19,607.598 USD bn in 2017. This records an increase from the previous number of 18,968.714 USD bn for 2016. United States US: GDP: USD: Gross National Income data is updated yearly, averaging 5,447.032 USD bn from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 19,607.598 USD bn in 2017 and a record low of 546.400 USD bn in 1960. United States US: GDP: USD: Gross National Income 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: Nominal. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current U.S. dollars.; ; World Bank national accounts data, and OECD National Accounts data files.; Gap-filled total;

Graph and download economic data for Shares of gross domestic product: Exports of goods (A253RE1Q156NBEA) from Q1 1947 to Q2 2025 about Shares of GDP, exports, goods, GDP, and USA.

TThe ERS International Macroeconomic Data Set provides historical and projected data for 181 countries that account for more than 99 percent of the world economy. These data and projections are assembled explicitly to serve as underlying assumptions for the annual USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term, 10-year scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks.

Explore the International Macroeconomic Data Set 2015 for annual growth rates, consumer price indices, real GDP per capita, exchange rates, and more. Get detailed projections and forecasts for countries worldwide.

Annual growth rates, Consumer price indices (CPI), Real GDP per capita, Real exchange rates, Population, GDP deflator, Real gross domestic product (GDP), Real GDP shares, GDP, projections, Forecast, Real Estate, Per capita, Deflator, share, Exchange Rates, CPI

Afghanistan, Albania, Algeria, 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, Congo, Costa Rica, Croatia, Cuba, Cyprus, 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, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe, WORLD Follow data.kapsarc.org for timely data to advance energy economics research. Notes:

Developed countries/1 Australia, New Zealand, Japan, Other Western Europe, European Union 27, North America

Developed countries less USA/2 Australia, New Zealand, Japan, Other Western Europe, European Union 27, Canada

Developing countries/3 Africa, Middle East, Other Oceania, Asia less Japan, Latin America;

Low-income developing countries/4 Haiti, Afghanistan, Nepal, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda, Zimbabwe;

Emerging markets/5 Mexico, Brazil, Chile, Czech Republic, Hungary, Poland, Slovakia, Russia, China, India, Korea, Taiwan, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Singapore

BRIICs/5 Brazil, Russia, India, Indonesia, China; Former Centrally Planned Economies

Former centrally planned economies/7 Cyprus, Malta, Recently acceded countries, Other Central Europe, Former Soviet Union

USMCA/8 Canada, Mexico, United States

Europe and Central Asia/9 Europe, Former Soviet Union

Middle East and North Africa/10 Middle East and North Africa

Other Southeast Asia outlook/11 Malaysia, Philippines, Thailand, Vietnam

Other South America outlook/12 Chile, Colombia, Peru, Bolivia, Paraguay, Uruguay

Indicator Source

Real gross domestic product (GDP) World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service all converted to a 2015 base year.

Real GDP per capita U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table and Population table.

GDP deflator World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Real GDP shares U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table.

Real exchange rates U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, CPI table, and Nominal XR and Trade Weights tables developed by the Economic Research Service.

Consumer price indices (CPI) International Financial Statistics International Monetary Fund, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Population Department of Commerce, Bureau of the Census, U.S. Department of Agriculture, Economic Research Service, International Data Base.

Today's weakness in the US economy results from lack of aggregate demand, due to high and growing inequality, underinvestment in public infrastructure and technology that is complementary to private capital, continuing mild austerity, difficulties encountered in making the structural transformation from manufacturing to a service-based economy, and a financial sector failing to provide adequate funds to SMEs. An agenda to restore growth includes a carbon price, inducing climate investments; increased public investments in infrastructure and technology; fighting inequality through redistribution and rewriting the rules structuring the economy; and reforming the financial sector and the global reserve system.

Graph and download economic data for Consumer Unit Characteristics: Percent Black or African American by Income Before Taxes: $120,000 to $149,999 (CXU980270LB0216M) from 2003 to 2015 about consumer unit, African-American, tax, percent, income, and USA.

Graph and download economic data for Gross Domestic Product: Real Estate (531) in the United States (USREALNGSP) from 1997 to 2024 about leases, real estate, rent, finance, insurance, GSP, private industries, private, industry, GDP, and USA.

Examining the most heavily cited publications in labor economics from the early 1990s, I show that few of over 3,000 articles, citing them directly, replicates them. They are replicated more frequently using data from other time periods and economies, so that the validity of their central ideas has typically been verified. This pattern of scholarship suggests, beyond the currently required depositing of data and code upon publication, that there is little need for formal mechanisms for replication. The market for scholarship already produces replications of non-laboratory applied research.

Denton economic data from the American Community Survey (ACS)

This graph shows the GDP of the Los Angeles metro area in 2022, by industry. In 2022, its GDP amounted to about **** trillion U.S. dollars. About **** billion U.S. dollars were generated by the manufacturing industry. The overall quarterly GDP growth in the United States can be found here.

Gross domestic product of Los Angeles

With a population of over *** million inhabitants in 2011, Los Angeles is the second largest city in America, following only New York. The Los Angeles metro area also ranked second among U.S. metro areas in terms of gross metropolitan product, second again only to New York City metro area, which came in with a GMP of USD ***** trillion to Los Angeles’ *** billion USD in 2011. Chicago metro area ranked third with GMP of *** billion U.S. dollars. Washington metro area ranked fourth with *** billion U.S. dollars in 2011. Additional detailed statistics about GDP and GMP in the United States is available here.

Despite Los Angeles’ high GDP, L.A. did not do as well as some cities in terms of median household income. Los Angeles ranked 11th with a median household income of ****** U.S. dollars annually in 2013. This was lower than the median household income of the United States in 2013, which came in at ****** U.S. dollars annually.

Located in Southern California, Los Angeles is home to Hollywood, the famous epicenter of the U.S. film and television industries. The United States is one of the leading film markets worldwide, producing *** films in 2011, many of them produced by Hollywood-based studios. In 2012, movie ticket sales in North America generated over **** billion U.S. dollars in box office revenue. Famous Hollywood actresses earn millions annually, with the best paid, Angelina Jolie, earning ** million U.S. dollars between ********* and *********. Second on the list was Jennifer Lawrence with earnings of ** million U.S. dollars.

Graph and download economic data for Exports of Services: Financial services (IEAXSF) from Q1 1999 to Q2 2025 about exports, financial, services, and USA.

This statistic shows the distribution of land in U.S. farms in 2023, by economic sales class. In 2024, 11.4 percent of U.S. farmland belonged to farms categorized in the 100,000 to 249,999 U.S. dollars sales class.

About this dataset

Context

The dataset tabulates the population of Economy by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Economy. The dataset can be utilized to understand the population distribution of Economy by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Economy. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Economy.

Key observations

Largest age group (population): Male # 65-69 years (412) | Female # 60-64 years (490). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Economy population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Economy is shown in the following column.
• Population (Female): The female population in the Economy is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Economy for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Economy Population by Gender. You can refer the same here

United States US: Broad Money: Average Annual Growth Rate data was reported at 3.760 % in 2016. This records an increase from the previous number of 3.408 % for 2015. United States US: Broad Money: Average Annual Growth Rate data is updated yearly, averaging 8.143 % from Dec 1961 (Median) to 2016, with 56 observations. The data reached an all-time high of 13.955 % in 1971 and a record low of -2.741 % in 2010. United States US: Broad Money: Average Annual Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Money Supply. Broad money (IFS line 35L..ZK) is the sum of currency outside banks; demand deposits other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler’s checks; and other securities such as certificates of deposit and commercial paper.; ; International Monetary Fund, International Financial Statistics and data files.; ;

Release Date: 2020-06-09.Release Schedule:.The data in this file come from the 2017 Economic Census data files released on a flow basis starting in September 2019. As such, preliminary U.S. totals released in September 2019 will be superseded with final totals, by sector, once data for all states have been released. Users should be aware that during the release of this consolidated file, data at more detailed North American Industry Classification System (NAICS) and geographic levels may not add to higher-level totals. However, at the completion of the economic census (once all the component files have been released), the detailed data in this file will add to the totals. For more information about economic census planned data product releases, see Economic Census: About: 2017 Release Schedules...Key Table Information:.U.S. totals released in September 2019 will be superseded with final totals, by sector, once data for all states have been released. .Includes only establishments and firms with payroll..Data may be subject to employment- and/or sales-size minimums that vary by industry...Data Items and Other Identifying Records: .Number of firms.Number of establishments.Sales, value of shipments, or revenue ($1,000).Annual payroll ($1,000).First-quarter payroll ($1,000).Number of employees.Range indicating percent of total sales, value of shipments, or revenue imputed.Range indicating percent of total annual payroll imputed.Range indicating percent of total employees imputed..Geography Coverage:.The data are shown for employer establishments and firms at the U.S., State, Combined Statistical Area, Metropolitan and Micropolitan Statistical Area, Metropolitan Division, Consolidated City, County (and equivalent), and Economic Place (and equivalent; incorporated and unincorporated) levels that vary by industry. For information about economic census geographies, including changes for 2017, see Economic Census: Economic Geographies...Industry Coverage:.The data are shown at the 2- through 6-digit 2017 NAICS code levels. For information about NAICS, see Economic Census: Technical Documentation: Code Lists...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector53/EC1753BASIC.zip..API Information:.Economic census data are housed in the Census Bureau API. For more information, see Explore Data: Developers: Available APIs: Economic Census..Methodology:.To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and/or nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only...To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. For detailed information about the methods used to collect and produce statistics, including sampling, eligibility, questions, data collection and processing, data quality, review, weighting, estimation, coding operations, confidentiality protection, sampling error, nonsampling error, and more, see Economic Census: Technical Documentation: Methodology...Symbols:.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals.N - Not available or not comparable.S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page..X - Not applicable.A - Relative standard error of 100% or more.r - Revised.s - Relative standard error exceeds 40%.For a complete list of symbols, see Economic Census: Technical Documentation: Data Dictionary.. .Source:.U.S. Census Bureau, 2017 Economic Census.For information about the economic census, see Business and Economy: Economic Census...Contact Information:.U.S. Census Bureau.For general inquiries:. (800) 242-2184/ (301) 763-5154. ewd.outreach@census.gov.For specific data questions:. (800) 541-8345.For additional contacts, see Economic Census: About: Contact Us.

Water provides society with economic benefits that increasingly involve tradeoffs, making accounting for water quality, quantity, and their corresponding economic productivity more relevant in our interconnected world. In the past, physical and economic data about water have been fragmented, but integration is becoming more widely adopted internationally through application of the System of Environmental-Economic Accounts for Water (SEEA-Water), which enables the tracking of linkages between water and the economy over time and across scales. In this paper, we present the first national and subnational SEEA-Water accounts for the United States. We compile accounts for: (1) physical supply and use of water, (2) water productivity, (3) water quality, and (4) water emissions. These cover state and national levels for roughly the years 2000 to 2015. The results illustrate broad aggregate trends as well as subnational or industry-level phenomena. Specifically, the accounts show that total U.S. water use declined by 22% from 2000 to 2015, continuing a national trend seen since 1980. Total water use fell in 44 states, though groundwater use increased in 21 states. Nationally, a larger percent of water use comes from groundwater than at any time since 1950. Reductions in water use, combined with economic growth, lead to increases in water productivity for the entire national economy (65%), mining (99%), and agriculture (68%), though substantial variation occurred among states. Surface-water quality trends for the years 2002 to 2012 were most evident at regional levels, and differ by water-quality constituent and region. Chloride, nitrate, and total dissolved solids levels in groundwater had more consistent and widespread water-quality declines nationally. This work provides a baseline of recent historical water resource trends and their value in the U.S., as well as roadmap for the completion of future accounts for water, a critical ecosystem service. Our work also aids in the interpretation of ecosystem accounts in the context of long-term trends in U.S. water resources.

We analyze whether--and, if so, how--Americans reacted to the escalation of the trade war between the United States and China in June 2018. To address this issue, we leverage surveys conducted in the U.S. during this phase of the economic clash. We find a significant reduction in support for Donald Trump and his trade policy immediately following the announcement of retaliatory tariffs by the Chinese government. Moreover, respondents’ economic concerns about the trade war were primarily sociotropic and only weakly related to personal pocketbook considerations or local exposure to Chinese retaliatory tariffs. We also find that the trade war's intensification was politically consequential, decreasing support for Republican candidates in the 2018 midterm elections. Our findings indicate that trade wars can be politically costly for incumbent politicians, even among voters who are not directly affected by retaliatory tariffs.

Employment, Commuting, Occupation, Income, Health Insurance, Poverty, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: 2022 Wards (State Legislative Districts [Upper Chamber]). Current Vintage: 2019-2023. ACS Table(s): DP03. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

United States The Economist YouGov Polls: 2024 Presidential Election: Donald Trump data was reported at 46.000 % in 29 Oct 2024. This stayed constant from the previous number of 46.000 % for 22 Oct 2024. United States The Economist YouGov Polls: 2024 Presidential Election: Donald Trump data is updated weekly, averaging 43.000 % from May 2023 (Median) to 29 Oct 2024, with 61 observations. The data reached an all-time high of 46.000 % in 29 Oct 2024 and a record low of 38.000 % in 31 Oct 2023. United States The Economist YouGov Polls: 2024 Presidential Election: Donald Trump data remains active status in CEIC and is reported by YouGov PLC. The data is categorized under Global Database’s United States – Table US.PR004: The Economist YouGov Polls: 2024 Presidential Election (Discontinued). If an election for president were going to be held now and the Democratic nominee was Joe Biden and the Republican nominee was Donald Trump, would you vote for...