100+ datasets found
  1. T

    United States GDP Growth Rate

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 26, 2025
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    TRADING ECONOMICS (2025). United States GDP Growth Rate [Dataset]. https://tradingeconomics.com/united-states/gdp-growth
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 30, 1947 - Mar 31, 2025
    Area covered
    United States
    Description

    The Gross Domestic Product (GDP) in the United States contracted 0.50 percent in the first 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.

  2. T

    United States GDP

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States GDP [Dataset]. https://tradingeconomics.com/united-states/gdp
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    United States
    Description

    The Gross Domestic Product (GDP) in the United States was worth 27720.71 billion US dollars in 2023, according to official data from the World Bank. The GDP value of the United States represents 26.29 percent of the world economy. This dataset provides - United States GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  3. United States US: GDP: Growth: Gross Value Added: Services

    • ceicdata.com
    Updated Oct 15, 2003
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    CEICdata.com (2003). United States US: GDP: Growth: Gross Value Added: Services [Dataset]. https://www.ceicdata.com/en/united-states/gross-domestic-product-annual-growth-rate/us-gdp-growth-gross-value-added-services
    Explore at:
    Dataset updated
    Oct 15, 2003
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2004 - Dec 1, 2015
    Area covered
    United States
    Variables measured
    Gross Domestic Product
    Description

    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.

  4. F

    Gross Domestic Product

    • fred.stlouisfed.org
    • trends.sourcemedium.com
    json
    Updated May 29, 2025
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    (2025). Gross Domestic Product [Dataset]. https://fred.stlouisfed.org/series/GDP
    Explore at:
    jsonAvailable download formats
    Dataset updated
    May 29, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

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

  5. T

    United States GDP Annual Growth Rate

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States GDP Annual Growth Rate [Dataset]. https://tradingeconomics.com/united-states/gdp-growth-annual
    Explore at:
    excel, csv, xml, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 31, 1948 - Mar 31, 2025
    Area covered
    United States
    Description

    The Gross Domestic Product (GDP) in the United States expanded 2 percent in the first 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.

  6. N

    Economy, PA Age Group Population Dataset: A Complete Breakdown of Economy...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
    + more versions
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    Neilsberg Research (2025). Economy, PA Age Group Population Dataset: A Complete Breakdown of Economy Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/45200925-f122-11ef-8c1b-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Feb 22, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Economy, Pennsylvania
    Variables measured
    Population Under 5 Years, Population over 85 years, Population Between 5 and 9 years, Population Between 10 and 14 years, Population Between 15 and 19 years, Population Between 20 and 24 years, Population Between 25 and 29 years, Population Between 30 and 34 years, Population Between 35 and 39 years, Population Between 40 and 44 years, and 9 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the age groups. For age groups we divided it into roughly a 5 year bucket for ages between 0 and 85. For over 85, we aggregated data into a single group for all ages. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Economy population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Economy. The dataset can be utilized to understand the population distribution of Economy by age. For example, using this dataset, we can identify the largest age group in Economy.

    Key observations

    The largest age group in Economy, PA was for the group of age 65 to 69 years years with a population of 943 (10.43%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Economy, PA was the 85 years and over years with a population of 230 (2.54%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 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

    Variables / Data Columns

    • Age Group: This column displays the age group in consideration
    • Population: The population for the specific age group in the Economy is shown in this column.
    • % of Total Population: This column displays the population of each age group as a proportion of Economy total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    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 Age. You can refer the same here

  7. United States US: GDP: % of Manufacturing: Medium and High Tech Industry

    • ceicdata.com
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    CEICdata.com, United States US: GDP: % of Manufacturing: Medium and High Tech Industry [Dataset]. https://www.ceicdata.com/en/united-states/gross-domestic-product-share-of-gdp/us-gdp--of-manufacturing-medium-and-high-tech-industry
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2004 - Dec 1, 2015
    Area covered
    United States
    Variables measured
    Gross Domestic Product
    Description

    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; ;

  8. Rankings of Countries Dataset

    • kaggle.com
    Updated Jul 17, 2023
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    Shuv😈 (2023). Rankings of Countries Dataset [Dataset]. https://www.kaggle.com/datasets/shuvammandal121/global-country-rankings-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 17, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Shuv😈
    Description

    Content

    The "Global Country Rankings Dataset" is a comprehensive collection of metrics and indicators that ranks countries worldwide based on their socioeconomic performance. This datasets are providing valuable insights into the relative standings of nations in terms of key factors such as GDP per capita, economic growth, and various other relevant criteria.

    Researchers, analysts, and policymakers can leverage this dataset to gain a deeper understanding of the global economic landscape and track the progress of countries over time. The dataset covers a wide range of metrics, including but not limited to:

    Economic growth: the rate of change of real GDP- Country rankings: The average for 2021 based on 184 countries was 5.26 percent.The highest value was in the Maldives: 41.75 percent and the lowest value was in Afghanistan: -20.74 percent. The indicator is available from 1961 to 2021.

    GDP per capita, Purchasing Power Parity - Country rankings: The average for 2021 based on 182 countries was 21283.21 U.S. dollars.The highest value was in Luxembourg: 115683.49 U.S. dollars and the lowest value was in Burundi: 705.03 U.S. dollars. The indicator is available from 1990 to 2021.

    GDP per capita, current U.S. dollars - Country rankings: The average for 2021 based on 186 countries was 17937.03 U.S. dollars.The highest value was in Monaco: 234315.45 U.S. dollars and the lowest value was in Burundi: 221.48 U.S. dollars. The indicator is available from 1960 to 2021.

    GDP per capita, constant 2010 dollars - Country rankings: The average for 2021 based on 184 countries was 15605.8 U.S. dollars.The highest value was in Monaco: 204190.16 U.S. dollars and the lowest value was in Burundi: 261.02 U.S. dollars. The indicator is available from 1960 to 2021.

    source: https://www.theglobaleconomy.com/

  9. T

    United States GDP per capita

    • tradingeconomics.com
    • fr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States GDP per capita [Dataset]. https://tradingeconomics.com/united-states/gdp-per-capita
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    United States
    Description

    The Gross Domestic Product per capita in the United States was last recorded at 65875.18 US dollars in 2023. The GDP per Capita in the United States is equivalent to 522 percent of the world's average. This dataset provides - United States GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  10. United States US: GDP: PPP

    • ceicdata.com
    + more versions
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    CEICdata.com, United States US: GDP: PPP [Dataset]. https://www.ceicdata.com/en/united-states/gross-domestic-product-purchasing-power-parity/us-gdp-ppp
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    United States
    Variables measured
    Gross Domestic Product
    Description

    United States US: GDP: PPP data was reported at 19,390,604.000 Intl $ mn in 2017. This records an increase from the previous number of 18,624,475.000 Intl $ mn for 2016. United States US: GDP: PPP data is updated yearly, averaging 11,892,799.000 Intl $ mn from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 19,390,604.000 Intl $ mn in 2017 and a record low of 5,979,589.000 Intl $ mn in 1990. United States US: GDP: PPP 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: Gross Domestic Product: Purchasing Power Parity. PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current international dollars. For most economies PPP figures are extrapolated from the 2011 International Comparison Program (ICP) benchmark estimates or imputed using a statistical model based on the 2011 ICP. For 47 high- and upper middle-income economies conversion factors are provided by Eurostat and the Organisation for Economic Co-operation and Development (OECD).; ; World Bank, International Comparison Program database.; Gap-filled total;

  11. F

    Real gross domestic product per capita

    • fred.stlouisfed.org
    json
    Updated Jun 26, 2025
    + more versions
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    (2025). Real gross domestic product per capita [Dataset]. https://fred.stlouisfed.org/series/A939RX0Q048SBEA
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 26, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

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

  12. d

    Oil Prices and the U.S. Economy: Where Is the Boom? \"Replication Data for\"...

    • search.dataone.org
    Updated Nov 21, 2023
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    Arora, Vipin (2023). Oil Prices and the U.S. Economy: Where Is the Boom? \"Replication Data for\" [Dataset]. http://doi.org/10.7910/DVN/UDM9TX
    Explore at:
    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Arora, Vipin
    Description

    The author argues that the economic benefits of low gasoline prices for the U.S. economy have fallen substantially since the reemergence of America as a major oil producer. The old rule-of thumb that a 10% fall in the oil price raises inflation-adjusted U.S. GDP by 0.2% is too large—the impact on economic activity should be closer to zero, and may even be negative if consumption grows slowly. The reasons for this change are straightforward, if underappreciated: (i) the value of oil production accounts for a larger share of the U.S. economy; and (ii) consumers are not spending the windfall like they used to because of higher debt levels, limited access to credit, slow wage rowth, and an older population.

  13. N

    Median Household Income Variation by Family Size in Economy, PA: Comparative...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
    + more versions
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    Neilsberg Research (2025). Median Household Income Variation by Family Size in Economy, PA: Comparative analysis across 7 household sizes [Dataset]. https://www.neilsberg.com/research/datasets/23fba638-f81d-11ef-a994-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Economy, Pennsylvania
    Variables measured
    Household size, Median Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across 7 household sizes (mentioned above) following an initial analysis and categorization. Using this dataset, you can find out how household income varies with the size of the family unit. For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents median household incomes for various household sizes in Economy, PA, as reported by the U.S. Census Bureau. The dataset highlights the variation in median household income with the size of the family unit, offering valuable insights into economic trends and disparities within different household sizes, aiding in data analysis and decision-making.

    Key observations

    • Of the 7 household sizes (1 person to 7-or-more person households) reported by the census bureau, Economy did not include 7-person households. Across the different household sizes in Economy the mean income is $133,892, and the standard deviation is $57,462. The coefficient of variation (CV) is 42.92%. This high CV indicates high relative variability, suggesting that the incomes vary significantly across different sizes of households.
    • In the most recent year, 2023, The smallest household size for which the bureau reported a median household income was 1-person households, with an income of $52,533. It then further increased to $170,000 for 6-person households, the largest household size for which the bureau reported a median household income.
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Household Sizes:

    • 1-person households
    • 2-person households
    • 3-person households
    • 4-person households
    • 5-person households
    • 6-person households
    • 7-or-more-person households

    Variables / Data Columns

    • Household Size: This column showcases 7 household sizes ranging from 1-person households to 7-or-more-person households (As mentioned above).
    • Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific household size.

    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 median household income. You can refer the same here

  14. d

    Replication Data for: The Fading American Dream: Trends in Absolute Income...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 12, 2023
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    Chetty, Raj; Grusky, David; Hell, Maximilian; Hendren, Nathaniel; Manduca, Robert; Narang, Jimmy (2023). Replication Data for: The Fading American Dream: Trends in Absolute Income Mobility Since 1940 [Dataset]. http://doi.org/10.7910/DVN/B9TEWM
    Explore at:
    Dataset updated
    Nov 12, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Chetty, Raj; Grusky, David; Hell, Maximilian; Hendren, Nathaniel; Manduca, Robert; Narang, Jimmy
    Description

    This dataset contains replication files for "The Fading American Dream: Trends in Absolute Income Mobility Since 1940" by Raj Chetty, David Grusky, Maximilian Hell, Nathaniel Hendren, Robert Manduca, and Jimmy Narang. For more information, see https://opportunityinsights.org/paper/the-fading-american-dream/. A summary of the related publication follows. One of the defining features of the “American Dream” is the ideal that children have a higher standard of living than their parents. We assess whether the U.S. is living up to this ideal by estimating rates of “absolute income mobility” – the fraction of children who earn more than their parents – since 1940. We measure absolute mobility by comparing children’s household incomes at age 30 (adjusted for inflation using the Consumer Price Index) with their parents’ household incomes at age 30. We find that rates of absolute mobility have fallen from approximately 90% for children born in 1940 to 50% for children born in the 1980s. Absolute income mobility has fallen across the entire income distribution, with the largest declines for families in the middle class. These findings are unaffected by using alternative price indices to adjust for inflation, accounting for taxes and transfers, measuring income at later ages, and adjusting for changes in household size. Absolute mobility fell in all 50 states, although the rate of decline varied, with the largest declines concentrated in states in the industrial Midwest, such as Michigan and Illinois. The decline in absolute mobility is especially steep – from 95% for children born in 1940 to 41% for children born in 1984 – when we compare the sons’ earnings to their fathers’ earnings. Why have rates of upward income mobility fallen so sharply over the past half-century? There have been two important trends that have affected the incomes of children born in the 1980s relative to those born in the 1940s and 1950s: lower Gross Domestic Product (GDP) growth rates and greater inequality in the distribution of growth. We find that most of the decline in absolute mobility is driven by the more unequal distribution of economic growth rather than the slowdown in aggregate growth rates. When we simulate an economy that restores GDP growth to the levels experienced in the 1940s and 1950s but distributes that growth across income groups as it is distributed today, absolute mobility only increases to 62%. In contrast, maintaining GDP at its current level but distributing it more broadly across income groups – at it was distributed for children born in the 1940s – would increase absolute mobility to 80%, thereby reversing more than two-thirds of the decline in absolute mobility. These findings show that higher growth rates alone are insufficient to restore absolute mobility to the levels experienced in mid-century America. Under the current distribution of GDP, we would need real GDP growth rates above 6% per year to return to rates of absolute mobility in the 1940s. Intuitively, because a large fraction of GDP goes to a small fraction of high-income households today, higher GDP growth does not substantially increase the number of children who earn more than their parents. Of course, this does not mean that GDP growth does not matter: changing the distribution of growth naturally has smaller effects on absolute mobility when there is very little growth to be distributed. The key point is that increasing absolute mobility substantially would require more broad-based economic growth. We conclude that absolute mobility has declined sharply in America over the past half-century primarily because of the growth in inequality. If one wants to revive the “American Dream” of high rates of absolute mobility, one must have an interest in growth that is shared more broadly across the income distribution.

  15. Historical data

    • kaggle.com
    Updated May 11, 2024
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    willian oliveira gibin (2024). Historical data [Dataset]. http://doi.org/10.34740/kaggle/dsv/8386348
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 11, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    willian oliveira gibin
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    this graph was created in OurDataWorld:

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Fc099e1eee01f448c6c8f40c2d83de5eb%2Fgraph1.png?generation=1715453565007185&alt=media" alt="">

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Facca62b608d0c4817206ea2d9f671a77%2Fgraph3.png?generation=1715453571722599&alt=media" alt="">

    https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F16731800%2Fdb52a1fa0b9db9f7d84bacedb217e160%2Fgraph2.png?generation=1715453577861078&alt=media" alt="">

    What you should know about this indicator This GDP per capita indicator provides information on economic growth and income levels in the very long run. Some country estimates are available as far back as 1 CE and regional estimates as far back as 1820 CE. This data is adjusted for inflation and for differences in the cost of living between countries. This data is expressed in international-$ at 2011 prices, using a combination of 2011 and 1990 PPPs for historical data. Time series for former countries and territories are calculated forward in time by estimating values based on their last official borders. For more regularly updated estimates of GDP per capita, see the World Bank's indicator.

    Real GDP per capita in 2011$

    In two ways, this analysis leads to departures from the original Maddison approach and closer to the multiple benchmark approach as developed by the PWT. There is, to begin with, no doubt that the 2011 PPPs and the related estimates of GDP per capita reflect the relative levels of GDP per capita in the world economy today better than the combination of the 1990 benchmark and growth rates of GDP per capita according to national accounts. This information should be taken into account. At the same time, the underlying rule within the current Maddison Database is that economic growth rates of countries in the dataset should be identical or as close as possible to growth rates according to the national accounts (which is also the case for the pre 1990 period). For the post-1990 period we therefore decided to integrate the 2011 benchmarks by adapting the growth rates of GDP per capita in the period 1990–2011 to align the two (1990 and 2011) benchmarks. We estimated the difference between the combination of the 1990 benchmark and the growth rates of GDP (per capita) between 1990 and 2011 according to the national accounts, and annual growth rate from the 1990 benchmark to the 2011 benchmark. This difference is then evenly distributed to the growth rate of GDP per capita between 1990 and 2011; in other words, we added a country specific correction (constant for all years between 1990 and 2011) to the annual national account rate of growth to connect the 1990 benchmark to the 2011 benchmark. Growth after 2011 is, in the current update, exclusively based on the growth rates of GDP per capita according to national accounts.

    We also use the collected set of historical benchmark estimates to fine tune the dataset for the pre-1940 period, but only in those cases where the quality of the benchmark was high and there were multiple benchmarks to support a revision. The most important correction concerns the US/UK comparison. The conventional picture, based on the original 1990 Maddison estimates, indicated that the US overtook the UK as the world leader in the early years of the 20th century. This finding was first criticized by Ward and Devereux (2003), who argued, based on alternative measures of PPP-adjusted benchmarks between 1870 and 1930, that the United States was already leading the United Kingdom in terms of GDP per capita in the 1870s. This conclusion was criticized by Broadberry (2003).

    New evidence, however, suggests a more complex picture: in the 18th century, real incomes in the US (settler colonies only, not including indigenous populations) were probably higher than those in the UK (Lindert & Williamson, 2016a). Until about 1870, growth was both exten- sive (incorporating newly settled territory) and intensive (considering the growth of cities and industry at the east coast), but on balance, the US may—in terms of real income—have lagged behind the UK. After 1870, intensive growth becomes more important, and the US slowly gets the upper hand. This pattern is consistent with direct benchmark comparison of the income of both countries for the period 1907–1909 (Woltjer, 2015). This shows that GDP per capita for the United States in those years was 26% higher than in the United Kingdom. We have used Woltjer’s (2015) benchmark to correct the GDP series of the two countries. Projecting this benchmark into the 19th century with the series of GDP per capita of both countries results in the two countries achieving parity in 1880. This is close to Prados de la Escosura’s conjecture based on his short- cut method (Prados de la Escosura, 2000), and even closer to the Lindert and Williamson (2016a) results.

  16. c

    GDP per capita in PPS

    • opendata.marche.camcom.it
    • data.europa.eu
    json
    Updated Jun 18, 2025
    + more versions
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    ESTAT (2025). GDP per capita in PPS [Dataset]. https://opendata.marche.camcom.it/json-browser.htm?dse=tec00114?lastTimePeriod=1
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 18, 2025
    Dataset authored and provided by
    ESTAT
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2024
    Area covered
    Variables measured
    Volume indices of real expenditure per capita (in PPS_EU27_2020=100)
    Description

    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."

    Copyright notice and free re-use of data on: https://ec.europa.eu/eurostat/about-us/policies/copyright

  17. T

    United States Government Spending To GDP

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Government Spending To GDP [Dataset]. https://tradingeconomics.com/united-states/government-spending-to-gdp
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1900 - Dec 31, 2024
    Area covered
    United States
    Description

    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.

  18. m

    Data for Knowledge gaps in Latin America and the Caribbean and economic...

    • data.mendeley.com
    Updated Oct 1, 2020
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    Pablo Jarrin (2020). Data for Knowledge gaps in Latin America and the Caribbean and economic development [Dataset]. http://doi.org/10.17632/5j28czhtb7.1
    Explore at:
    Dataset updated
    Oct 1, 2020
    Authors
    Pablo Jarrin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Latin America
    Description

    We provide the data used for this research in both Excel (one file with one matrix per sheet, 'Allmatrices.xlsx'), and CSV (one file per matrix).

    Patent applications (Patent_applications.csv) Patent applications from residents and no residents per million inhabitants. Data obtained from the World Development Indicators database (World Bank 2020). Normalization by the number of inhabitants was made by the authors.

    High-tech exports (High-tech_exports.csv) The proportion of exports of high-level technology manufactures from total exports by technology intensity, obtained from the Trade Structure by Partner, Product or Service-Category database (Lall, 2000; UNCTAD, 2019)

    Expenditure on education (Expenditure_on_education.csv) Per capita government expenditure on education, total (2010 US$). The data was obtained from the government expenditure on education (total % of GDP), GDP (constant 2010 US$), and population indicators of the World Development Indicators database (World Bank 2020). Normalization by the number of inhabitants was made by the authors.

    Scientific publications (Scientific_publications.csv) Scientific and technical journal articles per million inhabitants. The data were obtained from the scientific and technical journal articles and population indicators of the World Development Indicators database (World Bank 2020). Normalization by the number of inhabitants was made by the authors.

    Expenditure on R&D (Expenditure_on_R&D.csv) Expenditure on research and development. Data obtained from the research and development expenditure (% of GDP), GDP (constant 2010 US$), and population indicators of the World Development Indicators database (World Bank 2020). Normalization by the number of inhabitants was made by the authors.

    Two centuries of GDP (GDP_two_centuries.csv) GDP per capita that accounts for inflation. Data obtained from the Maddison Project Database, version 2018 (Inklaar et al. 2018), and available from the Open Numbers community (open-numbers.github.io).

    Inklaar, R., de Jong, H., Bolt, J., & van Zanden, J. (2018). Rebasing “Maddison”: new income comparisons and the shape of long-run economic development (GD-174; GGDC Research Memorandum). https://www.rug.nl/research/portal/files/53088705/gd174.pdf

    Lall, S. (2000). The Technological Structure and Performance of Developing Country Manufactured Exports, 1985‐98. Oxford Development Studies, 28(3), 337–369. https://doi.org/10.1080/713688318

    Unctad. 2019. “Trade Structure by Partner, Product or Service-Category.” 2019. https://unctadstat.unctad.org/EN/.

    World Bank. (2020). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators

  19. N

    Economy, IN Annual Population and Growth Analysis Dataset: A Comprehensive...

    • neilsberg.com
    csv, json
    Updated Jul 30, 2024
    + more versions
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    Neilsberg Research (2024). Economy, IN Annual Population and Growth Analysis Dataset: A Comprehensive Overview of Population Changes and Yearly Growth Rates in Economy from 2000 to 2023 // 2024 Edition [Dataset]. https://www.neilsberg.com/insights/economy-in-population-by-year/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Jul 30, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    IN, Economy
    Variables measured
    Annual Population Growth Rate, Population Between 2000 and 2023, Annual Population Growth Rate Percent
    Measurement technique
    The data presented in this dataset is derived from the 20 years data of U.S. Census Bureau Population Estimates Program (PEP) 2000 - 2023. To measure the variables, namely (a) population and (b) population change in ( absolute and as a percentage ), we initially analyzed and tabulated the data for each of the years between 2000 and 2023. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Economy population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Economy across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

    Key observations

    In 2023, the population of Economy was 145, a 0% decrease year-by-year from 2022. Previously, in 2022, Economy population was 145, a decline of 0.68% compared to a population of 146 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Economy decreased by 55. In this period, the peak population was 201 in the year 2002. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

    Content

    When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

    Data Coverage:

    • From 2000 to 2023

    Variables / Data Columns

    • Year: This column displays the data year (Measured annually and for years 2000 to 2023)
    • Population: The population for the specific year for the Economy is shown in this column.
    • Year on Year Change: This column displays the change in Economy population for each year compared to the previous year.
    • Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

    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 Year. You can refer the same here

  20. N

    Income Distribution by Quintile: Mean Household Income in Economy, PA //...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
    + more versions
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Economy, PA // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/48201782-f81d-11ef-a994-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Economy, Pennsylvania
    Variables measured
    Income Level, Mean Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across income quintiles (mentioned above) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the mean household income for each of the five quintiles in Economy, PA, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

    Key observations

    • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 33,587, while the mean income for the highest quintile (20% of households with the highest income) is 287,506. This indicates that the top earners earn 9 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 474,140, which is 164.91% higher compared to the highest quintile, and 1411.68% higher compared to the lowest quintile.
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income Levels:

    • Lowest Quintile
    • Second Quintile
    • Third Quintile
    • Fourth Quintile
    • Highest Quintile
    • Top 5 Percent

    Variables / Data Columns

    • Income Level: This column showcases the income levels (As mentioned above).
    • Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

    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 median household income. You can refer the same here

Share
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Email
Click to copy link
Link copied
Close
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TRADING ECONOMICS (2025). United States GDP Growth Rate [Dataset]. https://tradingeconomics.com/united-states/gdp-growth

United States GDP Growth Rate

United States GDP Growth Rate - Historical Dataset (1947-06-30/2025-03-31)

Explore at:
102 scholarly articles cite this dataset (View in Google Scholar)
json, excel, csv, xmlAvailable download formats
Dataset updated
Jun 26, 2025
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Jun 30, 1947 - Mar 31, 2025
Area covered
United States
Description

The Gross Domestic Product (GDP) in the United States contracted 0.50 percent in the first 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.

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