Poland had the largest digital economy among the presented Central and Eastern European (CEE) countries, measuring at ** billion euros in 2021. Between 2017 and 2021, Poland's digital economy grew by nearly ** percent. Furthermore, in 2030, it was expected to be approximately *** times larger than in 2021. Other major digital economies in CEE included Czechia and Romania.

In 2021, the agriculture sector contributed around 0.94 percent to the Gross Domestic Product (GDP) of the United States. In that same year, 17.61 percent came from industry, and the service sector contributed the most to the GDP, at 76.4 percent.

Non-observed economy refers to all the productive activities that may not be recorded in the data sources used for calculating national accounts. It includes the underground economy, the informal economy, and the illegal economy. The underground economy is constituted mainly by illicit employment and false tax declarations. The latter were the major component of Italy's non-observed economic activities in 2021. The value of the shadow economy from under-declaration amounted to ** billion euros. The total value of the underground economy was equal to *** billion euros.

This dataset comprises spatial and temporal economic data compiled from the Annual Regional Database of the European Commission (ARDECO) and education attainment from Eurostat, covering the period from 1980 to 2021(2024). The dataset consists of three files, each corresponding to a different level of NUTS coding (NUTS 1-3) according to the 2016 NUTS specification.

For each file, the following columns are included: Identifier:

NUTS Code: The unique identifier for the NUTS (2016) region

Year: The year of the data point

Variables:

 3. - 8. Hours Worked by NACE sector in 1000 hours (empHour_*)   9. - 15. Employment by NACE sector in 1000 jobs (emp_*)   16. Total employment in 1000 jobs (empl)   17. GDP at constant prices ref. 2015 in mio EUR (gdp)   18. - 23. GVA by NACE sector at constant prices ref. 2015 in mio EUR (gva_*)   24. Total Labour Force in 1000 jobs (labour)   25. Total Population (Regional Accounts) in persons (pop)   26. - 31. Compensation of Employees by NACE sector at constant prices ref. 2015 in mio EUR (wage_*)   32. Share of low education workers in per cent (loweduc) [not available for NUTS3]   33. Share of high education workers in per cent (terteduc) [not available for NUTS3]

The temporal dimension is yearly, ranging from 1980 to 2021(2024). The spatial dimension is identified by NUTS codes (2016), with granularity ranging from level 1 to level 3.

This dataset has been created as part of LAMASUS Project under the scope of Deliverable 3.2 titled "Database on EU policies and payments for agriculture, forest, and other LUM related drivers ". The data is directly linked to the work described on pages 45-47 belonging to section 3.3 Sectoral Income and Employment. The full text of the deliverable can be accessed via: https://www.lamasus.eu/wp-content/uploads/LAMASUS_D3.2_policy-and-payment-database.pdf.

Please note that this dataset is intended for research and analysis in the fields of climatology, environmental science, and related disciplines. Users are encouraged to cite this dataset appropriately if utilized in academic or scientific publications.

As of November 2021, the U.S. goverment dedicated ***** percent of the GDP to soften the effects of the coronavirus pandemic. This translates to stimulus packages worth **** trillion U.S. dollars Economic impact of the Coronavirus pandemic The impact of the COVID-19 pandemic was felt throughout the whole world. Lockdowns forced many industries to close completely for many months and restrictions were put on almost all economic activity. In 2020, the worldwide GDP loss due to Covid was *** percent. The global unemployment rate rocketed to **** percent in 2020 and confidence in governments’ ability to deal with the crisis diminished significantly. Governmental response In order to stimulate the economies and bring them out of recession, many countries have decided to release so called stimulus packages. These are fiscal and monetary policies used to support the recovery process. Through application of lower taxes and interest rates, direct financial aid, or facilitated access to funding, the governments aim to boost the employment, investment, and demand. Stimulus packages Until November 2021, Japan has dedicated the largest share of the GDP to stimulus packages among the G20 countries, with ***** percent (*** trillion Yen or **** trillion U.S. dollars). While the first help package aimed at maintaining employment and securing businesses, the second and third ones focused more on structural changes and positive developments in the country in the post-pandemic future.

This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. For a deep dive into the data model including every specific metric, see the ACS 2017-2021 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e21Estimate from 2017-21 ACS_m21Margin of Error from 2017-21 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_21Change, 2010-21 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLine (buffer)BeltLine Study (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Planning Unit STV (3 NPUs merged to a single geographic unit within City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)City of Atlanta Neighborhood Statistical Areas E02E06 (2 NSAs merged to single geographic unit within City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)SPARCC = Strong, Prosperous And Resilient Communities ChallengeState of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)WFF = Westside Future Fund (subarea of City of Atlanta)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2017-2021). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2017-2021Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://garc.maps.arcgis.com/sharing/rest/content/items/34b9adfdcc294788ba9c70bf433bd4c1/data

Full Year GDP Growth in Russia increased to 4.10 percent in 2024 from 3.60 percent in 2023. This dataset includes a chart with historical data for Russia Full Year Gdp Growth.

CPI: FH: Tools & Equipment for House & Garden: Small Tools data was reported at 105.267 2021=100 in Feb 2025. This records a decrease from the previous number of 105.437 2021=100 for Jan 2025. CPI: FH: Tools & Equipment for House & Garden: Small Tools data is updated monthly, averaging 101.297 2021=100 from Jan 2002 (Median) to Feb 2025, with 278 observations. The data reached an all-time high of 106.135 2021=100 in Nov 2024 and a record low of 79.196 2021=100 in Jan 2002. CPI: FH: Tools & Equipment for House & Garden: Small Tools data remains active status in CEIC and is reported by National Statistics Institute. The data is categorized under Global Database’s Spain – Table ES.I004: Consumer Price Index: 2021=100.

Zew Economic Sentiment Index in Italy increased to 59.70 in March from 56.80 in February of 2021. This dataset provides the latest reported value for - Italy Zew Economic Sentiment Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset presents a comparative overview of key macroeconomic indicators for Qatar and selected regional and global economic groupings for the years 2021 to 2023. It includes real GDP growth rates, consumer price index (CPI) year-on-year changes, and current account balances as a percentage of GDP. The data is disaggregated by regional grouping to facilitate international benchmarking and performance assessment. This dataset supports policy analysis and strategic planning in economic development and fiscal policy.

Economic Activity Index in China decreased to 50.80 points in October from 51.70 points in September of 2021. This dataset provides - China Economic Activity Index- actual values, historical data, forecast, chart, statistics, economic calendar and news.

CPI: CF: Footwear data was reported at 102.307 2021=100 in Feb 2025. This records a decrease from the previous number of 103.721 2021=100 for Jan 2025. CPI: CF: Footwear data is updated monthly, averaging 94.340 2021=100 from Jan 2002 (Median) to Feb 2025, with 278 observations. The data reached an all-time high of 113.084 2021=100 in Nov 2024 and a record low of 77.156 2021=100 in Feb 2002. CPI: CF: Footwear data remains active status in CEIC and is reported by National Statistics Institute. The data is categorized under Global Database’s Spain – Table ES.I004: Consumer Price Index: 2021=100.

This document is the FY 2021 Performance Report for the Iowa Economic Development Authority covering the period from July 1, 2020 through June 30, 2021.

Expenditure data relating to payments State budget for the reference financial year and accounting month - Data observed in June 2021. - [PBS_SPE_M05_AMMCE_001]

This dataset provides a curated and comprehensive overview of global health, demographic, economic, and environmental metrics for 188 recognized countries over a period of 10 years (2012-2021). It was created by combining reliable data from the World Bank and the World Health Organization (WHO). Due to the absence of a single source containing all necessary indicators, over 60 datasets were analyzed, cleaned, and merged, prioritizing completeness and significance.

The dataset includes 29 key indicators, ranging from life expectancy, population metrics, and economic factors to environmental conditions and health-related behaviors. Missing values were carefully handled, and only the most relevant data with substantial coverage were retained.

This dataset is ideal for researchers, analysts, and policymakers interested in exploring relationships between economic development, health outcomes, and environmental factors at a global scale.

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: District-wide. Current Vintage: 2017-2021. ACS Table(s): DP03. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: December 12, 2022. 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.

Taiwan GDP: 2021p: Ind: SV: RE: Real Estate data was reported at 383,994.000 NTD mn in 2023. This records an increase from the previous number of 380,562.000 NTD mn for 2022. Taiwan GDP: 2021p: Ind: SV: RE: Real Estate data is updated yearly, averaging 109,015.000 NTD mn from Dec 1981 (Median) to 2023, with 43 observations. The data reached an all-time high of 383,994.000 NTD mn in 2023 and a record low of 16,827.000 NTD mn in 1981. Taiwan GDP: 2021p: Ind: SV: RE: Real Estate data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.AA018: SNA 08: Reference Year=2021: GDP: by Industry: Chain Linked (Annual).