100+ datasets found
  1. U

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

    • ceicdata.com
    Updated Nov 27, 2021
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    CEICdata.com (2021). 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
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    Dataset updated
    Nov 27, 2021
    Dataset provided by
    CEICdata.com
    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.

  2. k

    International Macroeconomic Dataset (2015 Base)

    • datasource.kapsarc.org
    Updated Oct 26, 2025
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    (2025). International Macroeconomic Dataset (2015 Base) [Dataset]. https://datasource.kapsarc.org/explore/dataset/international-macroeconomic-data-set-2015/
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    Dataset updated
    Oct 26, 2025
    Description

    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.

  3. U

    United States US: GDP: USD: Gross National Income

    • ceicdata.com
    Updated Oct 15, 2025
    + more versions
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    CEICdata.com (2025). United States US: GDP: USD: Gross National Income [Dataset]. https://www.ceicdata.com/en/united-states/gross-domestic-product-nominal/us-gdp-usd-gross-national-income
    Explore at:
    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    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: 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;

  4. F

    Exports of Services: Financial services

    • fred.stlouisfed.org
    json
    Updated Sep 23, 2025
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    (2025). Exports of Services: Financial services [Dataset]. https://fred.stlouisfed.org/series/IEAXSF
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    jsonAvailable download formats
    Dataset updated
    Sep 23, 2025
    License

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

    Description

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

  5. U.S. value added to GDP 2024, by industry

    • statista.com
    Updated Nov 28, 2025
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    Statista (2025). U.S. value added to GDP 2024, by industry [Dataset]. https://www.statista.com/statistics/247991/value-added-to-the-us-gdp-by-industry/
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    Dataset updated
    Nov 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    United States
    Description

    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.

  6. o

    Replication data for: How to Restore Equitable and Sustainable Economic...

    • openicpsr.org
    Updated May 1, 2016
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    Joseph E. Stiglitz (2016). Replication data for: How to Restore Equitable and Sustainable Economic Growth in the United States [Dataset]. http://doi.org/10.3886/E113431V1
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    Dataset updated
    May 1, 2016
    Dataset provided by
    American Economic Association
    Authors
    Joseph E. Stiglitz
    Area covered
    United States
    Description

    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.

  7. U

    United States US: Broad Money: Average Annual Growth Rate

    • ceicdata.com
    Updated Apr 21, 2011
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    CEICdata.com (2011). United States US: Broad Money: Average Annual Growth Rate [Dataset]. https://www.ceicdata.com/en/united-states/money-supply/us-broad-money-average-annual-growth-rate
    Explore at:
    Dataset updated
    Apr 21, 2011
    Dataset provided by
    CEICdata.com
    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
    Monetary Aggregates/Money Supply/Money Stock
    Description

    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.; ;

  8. F

    Quarterly Financial Report: U.S. Corporations: All Information: Total Assets...

    • fred.stlouisfed.org
    json
    Updated Sep 9, 2025
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    (2025). Quarterly Financial Report: U.S. Corporations: All Information: Total Assets [Dataset]. https://fred.stlouisfed.org/series/QFR223INFUSNO
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    jsonAvailable download formats
    Dataset updated
    Sep 9, 2025
    License

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

    Area covered
    United States
    Description

    Graph and download economic data for Quarterly Financial Report: U.S. Corporations: All Information: Total Assets (QFR223INFUSNO) from Q4 2009 to Q2 2025 about information, finance, corporate, assets, industry, and USA.

  9. Distribution of land in U.S. farms 2024, by economic sales class

    • statista.com
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    Statista, Distribution of land in U.S. farms 2024, by economic sales class [Dataset]. https://www.statista.com/statistics/196110/us-distribution-of-land-in-farms-by-economic-sales-class/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    United States
    Description

    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.

  10. U

    United States BoP: SCA: FA: Liabilities: Oth: Loans

    • ceicdata.com
    Updated Mar 15, 2018
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    CEICdata.com (2018). United States BoP: SCA: FA: Liabilities: Oth: Loans [Dataset]. https://www.ceicdata.com/en/united-states/balance-of-payments-bpm6-latin-america-and-other-western-hemisphere/bop-sca-fa-liabilities-oth-loans
    Explore at:
    Dataset updated
    Mar 15, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Jun 1, 2015 - Mar 1, 2018
    Area covered
    United States
    Description

    United States BoP: SCA: FA: Liabilities: Oth: Loans data was reported at 4.941 USD bn in Mar 2018. This records an increase from the previous number of -7.771 USD bn for Dec 2017. United States BoP: SCA: FA: Liabilities: Oth: Loans data is updated quarterly, averaging 619.000 USD mn from Mar 2003 (Median) to Mar 2018, with 61 observations. The data reached an all-time high of 9.676 USD bn in Mar 2016 and a record low of -13.434 USD bn in Sep 2004. United States BoP: SCA: FA: Liabilities: Oth: Loans data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.JB007: Balance of Payments: BPM6: Latin America and Other Western Hemisphere.

  11. o

    Replication data for: Replication in Labor Economics: Evidence from Data,...

    • openicpsr.org
    Updated May 1, 2017
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    Daniel S. Hamermesh (2017). Replication data for: Replication in Labor Economics: Evidence from Data, and What It Suggests [Dataset]. http://doi.org/10.3886/E113534V1
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    Dataset updated
    May 1, 2017
    Dataset provided by
    American Economic Association
    Authors
    Daniel S. Hamermesh
    Description

    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.

  12. T

    American Financial | 유동 자산

    • ko.tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 25, 2017
    + more versions
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    TRADING ECONOMICS (2017). American Financial | 유동 자산 [Dataset]. https://ko.tradingeconomics.com/afg:us:current-assets
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    csv, excel, json, xmlAvailable download formats
    Dataset updated
    Jul 25, 2017
    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
    Jan 1, 2000 - Dec 2, 2025
    Area covered
    United States
    Description

    American Financial 유동 자산 - 현재 값, 이력 데이터, 예측, 통계, 차트 및 경제 달력 - Dec 2025.Data for American Financial | 유동 자산 including historical, tables and charts were last updated by Trading Economics this last December in 2025.

  13. R

    Nighttime Lights Economic Indicators Market Research Report 2033

    • researchintelo.com
    csv, pdf, pptx
    Updated Oct 1, 2025
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    Research Intelo (2025). Nighttime Lights Economic Indicators Market Research Report 2033 [Dataset]. https://researchintelo.com/report/nighttime-lights-economic-indicators-market
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    pptx, csv, pdfAvailable download formats
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Research Intelo
    License

    https://researchintelo.com/privacy-and-policyhttps://researchintelo.com/privacy-and-policy

    Time period covered
    2024 - 2033
    Area covered
    Global
    Description

    Nighttime Lights Economic Indicators Market Outlook



    According to our latest research, the Global Nighttime Lights Economic Indicators market size was valued at $2.1 billion in 2024 and is projected to reach $7.8 billion by 2033, expanding at a robust CAGR of 15.2% during 2024–2033. One of the primary drivers fueling this remarkable growth is the increasing reliance on real-time, objective data for economic analysis and urban development, especially as satellite and remote sensing technologies become more accessible and sophisticated. Nighttime lights data, derived from satellite and aerial imagery, has emerged as a crucial proxy for economic activity, infrastructure development, and disaster response, empowering governments, financial institutions, and urban planners to make more informed decisions in an ever-evolving global landscape.



    Regional Outlook



    North America currently holds the largest share of the Nighttime Lights Economic Indicators market, accounting for approximately 38% of the global value in 2024. This dominance is attributed to the region’s mature technological infrastructure, strong investment in satellite and remote sensing capabilities, and a well-established ecosystem of data analytics firms. The United States, in particular, benefits from robust federal and state-level initiatives supporting geospatial data utilization for urban planning, economic forecasting, and disaster management. The presence of major space agencies and private satellite operators further enhances data availability and quality, enabling a wide spectrum of end-users, from government agencies to financial institutions, to leverage nighttime lights as a reliable economic indicator. Additionally, North America's advanced regulatory frameworks and public-private partnerships have fostered a climate ripe for innovation and early adoption of cutting-edge geospatial analytics solutions.



    The Asia Pacific region is anticipated to be the fastest-growing market for Nighttime Lights Economic Indicators, with a projected CAGR of 18.7% from 2024 to 2033. This acceleration is driven by rapid urbanization, burgeoning smart city initiatives, and significant investments in satellite and remote sensing technologies across countries such as China, India, and Japan. Governments and urban planners in the region are increasingly leveraging nighttime lights data to address challenges related to infrastructure development, population migration, and environmental monitoring. The proliferation of low-cost satellite launches and the expansion of national space programs have democratized access to high-resolution imagery, while regional collaborations and public-private partnerships are catalyzing the integration of geospatial analytics into mainstream economic planning. Furthermore, the Asia Pacific’s growing research community and technology startups are contributing to the development of innovative applications, further propelling market growth.



    Emerging economies in Latin America, the Middle East, and Africa are gradually embracing Nighttime Lights Economic Indicators, although adoption is tempered by challenges such as limited technical expertise, data accessibility issues, and inconsistent regulatory support. Nevertheless, there is a growing recognition of the value that satellite-derived economic indicators can bring to addressing localized challenges such as informal settlements, disaster response, and resource allocation. In Africa, for instance, nighttime lights data is increasingly used to monitor electrification progress and urban expansion. Latin American countries are leveraging such indicators for disaster management and urban planning, particularly in regions prone to natural calamities. While these regions currently account for a smaller share of the global market, targeted policy reforms, international collaborations, and investments in capacity building are expected to accelerate adoption, bridging the gap between developed and developing markets.



    Report Scope




    Attributes Details
    Report Title Nighttime Lights Economic Indicators Market Research Repo

  14. F

    Consumer Unit Characteristics: Percent Black or African American by Income...

    • fred.stlouisfed.org
    json
    Updated Jan 15, 2021
    + more versions
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    (2021). Consumer Unit Characteristics: Percent Black or African American by Income Before Taxes: $120,000 to $149,999 [Dataset]. https://fred.stlouisfed.org/series/CXU980270LB0216M
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jan 15, 2021
    License

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

    Area covered
    United States
    Description

    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.

  15. U

    United States BAC: Cash Dividends

    • ceicdata.com
    Updated Nov 22, 2021
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    CEICdata.com (2021). United States BAC: Cash Dividends [Dataset]. https://www.ceicdata.com/en/united-states/financial-data-federal-deposit-insurance-corporation-bank-of-america/bac-cash-dividends
    Explore at:
    Dataset updated
    Nov 22, 2021
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Mar 1, 2017 - Dec 1, 2019
    Area covered
    United States
    Description

    United States BAC: Cash Dividends data was reported at 5,781,000.000 USD th in Dec 2019. This records a decrease from the previous number of 7,410,000.000 USD th for Sep 2019. United States BAC: Cash Dividends data is updated quarterly, averaging 2,500,000.000 USD th from Dec 2000 (Median) to Dec 2019, with 77 observations. The data reached an all-time high of 10,672,558.000 USD th in Dec 2006 and a record low of 0.000 USD th in Mar 2019. United States BAC: Cash Dividends data remains active status in CEIC and is reported by Federal Deposit Insurance Corporation. The data is categorized under Global Database’s United States – Table US.KB055: Financial Data: Federal Deposit Insurance Corporation: Bank of America.

  16. F

    Shares of gross domestic product: Exports of goods

    • fred.stlouisfed.org
    json
    Updated Sep 25, 2025
    + more versions
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    (2025). Shares of gross domestic product: Exports of goods [Dataset]. https://fred.stlouisfed.org/series/A253RE1Q156NBEA
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Sep 25, 2025
    License

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

    Description

    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.

  17. 2017 Economic Census: EC1753BASIC | Real Estate and Rental and Leasing:...

    • data.census.gov
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    ECN, 2017 Economic Census: EC1753BASIC | Real Estate and Rental and Leasing: Summary Statistics for the U.S., States, and Selected Geographies: 2017 (ECN Core Statistics Summary Statistics for the U.S., States, and Selected Geographies: 2017) [Dataset]. https://data.census.gov/table/ECNBASIC2017.EC1753BASIC?q=Longhorn%20Truck%20Accessories
    Explore at:
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ECN
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2017
    Area covered
    United States
    Description

    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.

  18. y

    US Personal Savings Rate

    • ycharts.com
    html
    Updated Sep 25, 2025
    + more versions
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    Bureau of Economic Analysis (2025). US Personal Savings Rate [Dataset]. https://ycharts.com/indicators/us_personal_savings_rate_yearly
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    htmlAvailable download formats
    Dataset updated
    Sep 25, 2025
    Dataset provided by
    YCharts
    Authors
    Bureau of Economic Analysis
    License

    https://www.ycharts.com/termshttps://www.ycharts.com/terms

    Time period covered
    Dec 31, 1929 - Dec 31, 2024
    Area covered
    United States
    Variables measured
    US Personal Savings Rate
    Description

    View yearly updates and historical trends for US Personal Savings Rate. from United States. Source: Bureau of Economic Analysis. Track economic data with …

  19. I

    Israel Imports: America: South: Ecuador

    • ceicdata.com
    Updated Apr 15, 2018
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    CEICdata.com (2018). Israel Imports: America: South: Ecuador [Dataset]. https://www.ceicdata.com/en/israel/imports-by-country/imports-america-south-ecuador
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    Dataset updated
    Apr 15, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Apr 1, 2017 - Mar 1, 2018
    Area covered
    Israel
    Variables measured
    Merchandise Trade
    Description

    Israel Imports: America: South: Ecuador data was reported at 0.500 USD mn in Jun 2018. This records a decrease from the previous number of 0.700 USD mn for May 2018. Israel Imports: America: South: Ecuador data is updated monthly, averaging 0.200 USD mn from Jan 1988 (Median) to Jun 2018, with 366 observations. The data reached an all-time high of 13.000 USD mn in Dec 1999 and a record low of 0.000 USD mn in Jun 2010. Israel Imports: America: South: Ecuador data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.JA019: Imports: by Country.

  20. U

    United States CPI U: Northeast: Size Class B/C

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). United States CPI U: Northeast: Size Class B/C [Dataset]. https://www.ceicdata.com/en/united-states/consumer-price-index-urban-by-region/cpi-u-northeast-size-class-bc
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Apr 1, 2017 - Mar 1, 2018
    Area covered
    United States
    Description

    United States CPI U: Northeast: Size Class B/C data was reported at 156.752 Dec1996=100 in Oct 2018. This records a decrease from the previous number of 156.961 Dec1996=100 for Sep 2018. United States CPI U: Northeast: Size Class B/C data is updated monthly, averaging 132.049 Dec1996=100 from Dec 1996 (Median) to Oct 2018, with 263 observations. The data reached an all-time high of 157.350 Dec1996=100 in Aug 2018 and a record low of 100.000 Dec1996=100 in Jan 1997. United States CPI U: Northeast: Size Class B/C data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.I014: Consumer Price Index: Urban: By Region. All metropolitan areas with population smaller than 1.5 million

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CEICdata.com (2021). 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

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

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Dataset updated
Nov 27, 2021
Dataset provided by
CEICdata.com
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.

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