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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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TwitterFocusEconomics' economic data is provided by official state statistical reporting agencies as well as our global network of leading banks, think tanks and consultancies. Our datasets provide not only historical data, but also Consensus Forecasts and individual forecasts from the aformentioned global network of economic analysts. This includes the latest forecasts as well as historical forecasts going back to 2010. Our global network consists of over 1000 world-renowned economic analysts from which we calculate our Consensus Forecasts. In this specific dataset you will find economic data for Slovakia.
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TwitterNovember 2024: For DCMS sector data, please see: Economic Estimates: Employment and APS earnings in DCMS sectors, January 2023 to December 2023
For Digital sector data, please see: Economic Estimates: Employment in DCMS sectors and Digital sector, January 2022 to December 2022
October 2024: Following the identification of a minor error, the Labour Force Survey, July to September 2016 to 2020 data tables have been re-published for the digital sector. This affects data for 2019 only - data for 2016 and 2020 are not affected.
Updated estimates for DCMS sectors have been re-published.
Economic Estimates: Employment in DCMS sectors, April 2022 to March 2024.
Although the original versions of the tables were published before the Machinery of Government changes in February 2023, these corrected tables have been re-published for DCMS sectors and the digital sector separately. This is because the digital sector is now a Department for Science, Innovation and Technology (DSIT) responsibility.
The Economic Estimates in this release are a combination of National, Official, and experimental statistics used to provide an estimate of the contribution of DCMS Sectors to the UK economy.
These statistics cover the economic contribution of the following DCMS sectors to the UK economy:
Tourism and Civil Society are included where possible.
Users should note that there is overlap between DCMS sector definitions and that the Telecoms sector sits wholly within the Digital sector.
The release also includes estimates for the Audio Visual sector and Computer Games sector for some measures.
A definition for each sector is available in the associated methodology note along with details of methods and data limitations.
Following updates to the underlying methodology used to produce the estimates for Weekly Gross Pay, Annual Gross Pay and the Gender Pay Gap, we have published revised estimates for employee earnings in the DCMS Sectors and Digital Sector from 2016 to 2020.
We’ve published revised estimates for Weekly Gross Pay, Annual Gross Pay and the Gender Pay Gap. This was necessary for a number of reasons, including:
These statistics were first published on 23 December 2021
DCMS aims to continuously improve the quality of estimates and better meet user needs. DCMS welcomes feedback on this release. Feedback should be sent to DCMS via email at evidence@dcms.gov.uk.
This release is published in accordance with the Code of Practice for Statistics (2018) produced by the UK Statistics Authority (UKSA). The UKSA has the overall objective of promoting and safeguarding the production and publication of official statistics that serve the public good. It monitors and reports on all official statistics, and promotes good practice in this area.
The accompanying pre-release access document lists ministers and officials who have received privileged early access to this release. In line with best practice, the list has been kept to a minimum and those given access for briefing purposes had a maximum of 24 hours.
Responsible statistician: Rachel Moyce.
For any queries or feedback, contact <a href="mailto
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Economic Policy Uncertainty : News-Based for the United States was 282.42142 Index in October of 2025, according to the United States Federal Reserve. Historically, Economic Policy Uncertainty : News-Based for the United States reached a record high of 725.03117 in April of 2025 and a record low of 21.94447 in September of 1956. Trading Economics provides the current actual value, an historical data chart and related indicators for Economic Policy Uncertainty : News-Based for the United States - last updated from the United States Federal Reserve on November of 2025.
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TwitterThis dataset provides a historical overview of key global indicators, including Gross Domestic Product (GDP), population growth, and CO2 emissions. It captures economic trends, demographic shifts, and environmental impacts over multiple decades, making it useful for researchers, analysts, and policymakers.
The dataset includes Real GDP (inflation-adjusted), allowing for economic trend analysis while accounting for inflation effects. Additionally, it incorporates CO2 emissions data, enabling studies on the relationship between economic growth and environmental impact.
This dataset is valuable for multiple research areas:
✅ Macroeconomic Analysis – Study global economic growth, recessions, and recovery trends.
✅ Inflation & Monetary Policy – Compare nominal vs. real GDP to assess inflationary trends.
✅ Climate Change Research – Analyze CO2 emissions alongside economic growth to identify sustainability challenges.
✅ Predictive Modeling – Train machine learning models for forecasting GDP, population, or emissions.
✅ Public Policy & Development – Evaluate the impact of economic and environmental policies over time.
This dataset is shared for educational and analytical purposes only.
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TwitterOpen Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
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Denton economic data from the American Community Survey (ACS)
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TwitterTo collect data on an angler's last trip for revealed preference models and economic valuation purposes. Typically done as an add-on to the MRIP intercept survey and done as needed, periodically
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TwitterThe Comprehensive Annual Financial Reports are presented in three main sections; the Introductory Section, the Financial Section, and the Statistical Section. The Introductory Section includes a financial overview, discussion of Iowa's economy and an organizational chart for State government. The Financial Section includes the state auditor's report, management's discussion and analysis, audited basic financial statements and notes thereto, and the underlying combining and individual fund financial statements and supporting schedules. The Statistical Section sets forth selected unaudited economic, financial trend and demographic information for the state on a multi-year basis. Reports for multiple fiscal years are available.
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TwitterThe median age indicates the age separating the population group into two halves of equal size.
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TwitterThe ZEW Economic Sentiment Index for the EuroZone is a leading indicator that measures the economic outlook of institutional investors and analysts for the next six months.
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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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TwitterFocusEconomics' economic data is provided by official state statistical reporting agencies as well as our global network of leading banks, think tanks and consultancies. Our datasets provide not only historical data, but also Consensus Forecasts and individual forecasts from the aformentioned global network of economic analysts. This includes the latest forecasts as well as historical forecasts going back to 2010. Our global network consists of over 1000 world-renowned economic analysts from which we calculate our Consensus Forecasts. In this specific dataset you will find economic data for Armenia GDP.
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TwitterThe ZEW Economic Sentiment Index for the EuroZone is a leading indicator that measures the economic outlook of institutional investors and analysts for the next six months.-2025-01-21
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TwitterToday'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.
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Twitterhttps://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal
Economically Active Population Survey: Employed persons by economic sector, sex and Autonomous Community. Percentages with respect to the total of each Community. Quarterly. Autonomous Communities and Cities.
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TwitterComparison matrix of economic criteria.
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Chad: Uneven economic development index, 0 (low) - 10 (high): The latest value from 2024 is 8.4 index points, a decline from 8.7 index points in 2023. In comparison, the world average is 5.28 index points, based on data from 176 countries. Historically, the average for Chad from 2007 to 2024 is 8.96 index points. The minimum value, 8.4 index points, was reached in 2024 while the maximum of 9.3 index points was recorded in 2009.
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TwitterThe 2006 Second Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage for a single TIGER/Line file is a county or statistical equivalent entity, with the coverage area based on the latest available governmental unit boundaries. The Census TIGER database represents a seamless national file with no overlaps or gaps between parts. However, each county-based TIGER/Line file is designed to stand alone as an independent data set or the files can be combined to cover the whole Nation. The 2006 Second Edition TIGER/Line files consist of line segments representing physical features and governmental and statistical boundaries. This shapefile represents the County Economic Census for Luna County stored in the 2006 TIGER Second Edition dataset.
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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.
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Poland Number of National Economy Entities: Registered: Natural Persons Conducting Economic Activity data was reported at 3,081,190.000 Unit in Sep 2018. This records an increase from the previous number of 3,043,282.000 Unit for Jun 2018. Poland Number of National Economy Entities: Registered: Natural Persons Conducting Economic Activity data is updated quarterly, averaging 2,871,457.000 Unit from Sep 2002 (Median) to Sep 2018, with 65 observations. The data reached an all-time high of 3,081,190.000 Unit in Sep 2018 and a record low of 2,677,537.000 Unit in Sep 2002. Poland Number of National Economy Entities: Registered: Natural Persons Conducting Economic Activity data remains active status in CEIC and is reported by Central Statistical Office. The data is categorized under Global Database’s Poland – Table PL.O013: Number of Economic Entities: Registered: by Ownership and Legal Form.
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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.