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.

Both global and national economies were negatively impacted by the COVID-19 pandemic. Throughout summer 2021, sentiments about economic improvement were pretty high with ** percent of the respondents expecting global economy to improve in the next six months. In the following surveys, these expectations gradually lowered, with only ** and ** percent of respondents expecting economic recovery on a global scale as of ************.

The Japanese government announced a new economic stimulus package on November 19, 2021, in response to the growing impact of coronavirus disease (COVID-19) on Japan's economy. A total of around ** trillion Japanese yen was planned for the whole operation, approximately **** trillion yen of which was designated for the prevention of the spread of the disease. The government also announced an emergency relief package in April 2020 and December 2020.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated facts and figures page.

The UK economy grew by 0.1 percent in the third quarter of 2025, compared with 0.3 percent growth in the previous quarter. After ending 2023 in recession, the UK economy grew strongly in the first half of 2024, growing by 0.8 percent in Q1, and 0.6 percent in Q2, with growth slowing in the second half of the year. In the third quarter of 2020 the UK experienced record setting growth of 16.8 percent, which itself followed the record 20.3 percent contraction in Q2 2020. Growing economy key to Labour's plans Since winning the 2024 general election, the UK's Labour Party have seen their popularity fall substantially. In February 2025, the government's approval rating fell to a low of -54 percent, making them almost as disliked as the Conservatives just before the last election. A string of unpopular policies since taking office have taken a heavy toll on support for the government. Labour hope they can reverse their declining popularity by growing the economy, which has underperformed for several years, and when measured in GDP per capita, fell in 2023, and 2024. Steady labor market trends set to continue? After a robust 2022, the UK labor market remained resilient throughout 2023 and 2024. The unemployment rate at the end of 2024 was 4.4 percent, up from four percent at the start of the year, but still one of the lowest rates on record. While the average number of job vacancies has been falling since a May 2022 peak, there was a slight increase in January 2025 when compared with the previous month. The more concerning aspect of the labor market, from the government's perspective, are the high levels of economic inactivity due to long-term sickness, which reached a peak of 2.84 million in late 2023, and remained at high levels throughout 2024.

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

MA: TE: Resources: Taxes on Products & Imports (PI) data was reported at 11,069.653 EUR mn in Dec 2024. This records a decrease from the previous number of 11,166.111 EUR mn for Sep 2024. MA: TE: Resources: Taxes on Products & Imports (PI) data is updated quarterly, averaging 6,292.356 EUR mn from Mar 1999 (Median) to Dec 2024, with 104 observations. The data reached an all-time high of 11,166.111 EUR mn in Sep 2024 and a record low of 4,007.173 EUR mn in Mar 1999. MA: TE: Resources: Taxes on Products & Imports (PI) data remains active status in CEIC and is reported by Statistics Portugal. The data is categorized under Global Database’s Portugal – Table PT.A019: ESA 2010: Main Aggregates: 2021 Base: Total Economy.

Release Date: 2024-03-14.Release Schedule:.The NES data in this file will be released on March 14, 2024...Key Table Information:.Beginning with reference year 2005, Nonemployer data are released using the Noise Infusion methodology to protect confidentiality. See Program Methodology for complete information on the coverage and methodology of the Nonemployer Statistics data series....Data Items and Other Identifying Records:.This table contains data on the total number of firms and receipts..Number of nonemployer establishments.Nonemployer sales, value of shipments, or revenue ($1,000).Noise range for nonemployer sales, value of shipments, or revenue...Geography Coverage:.The data are shown at the U.S. and State level for LFO and the U.S. level for Receipt Size Class. All other data is shown at the U.S., State, County, Combined Statistical Area, and Metropolitan/Micropolitan Statistical Areas....Industry Coverage:.The data are shown at the 2- through (where available) 6-digit NAICS code levels for all sectors with published data. Data for nonemployers generally are provided at broader levels of industry detail than data for employers. For specific exclusions and inclusions, see Program Methodology...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/nonemployer-statistics/data/2021/NS2100NONEMP.zip...API Information:.Nonemployer Statistics data are housed in the Nonemployer Statistics API. For more information, see Nonemployer Statistics APIs....Methodology:.The universe of this file is all firms with no paid employees or payroll with receipts of $1,000 or more (or $1 for the construction sector) and are subject to federal income tax. The universe is limited to industries in approximately 470 of the nearly 1,200 recognized North American Industry Classification System industries. The universe contains only those codes that are available through administrative records sources and are common to all three legal forms of organization applicable to nonemployer businesses. This is generally a broader level of detail than would typically be provided for employer data. For specific exclusions and inclusions, see Program Methodology.....Nonemployer Statistics originate from tax return information of the Internal Revenue Service. The data are subject to nonsampling error such as errors of self-classification by industry on tax forms, as well as errors of response, nonreporting and coverage. Values provided by each firm are slightly modified to protect the respondent's confidentiality. For further information about methodology and data limitations, see Program Methodology...Symbols:.G - Low noise; cell value was changed by less than 2 percent by the application of noise.H - Moderate noise; cell value was changed by 2 percent or more but less than 5 percent by the application of noise.J - High noise; cell value was changed by 5 percent or more by the application of noise..S - Withheld because estimate did not meet publication standards.N - Not available or not comparable.For a complete list of symbols, see Program Glossary: Abbreviations and Symbols....Source:..U.S. Census Bureau, 2021 Nonemployer Statistics..For more information about Nonemployer Statistics, see Nonemployer Statistics website...Contact Information:..U.S. Census Bureau.Economy-Wide Statistics Division .Business Statistics Branch .(301) 763-2580 .ewd.nonemployer.statistics@census.gov

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.

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]

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.

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.

ABOUT THE CITY OF TEMPE BUSINESS SURVEY REPORTS DATASETThis data set includes the results from the Tempe Business Survey, conducted every other year, to gather input from businesses on what is highest in importance to businesses and to learn where businesses are the least and most satisfied.PERFORMANCE MEASURESData collected in this survey applies directly to the following Performance Measures for the City of Tempe (as of 2021):5. Financial Stability and Vitality5.01 Quality of Business ServicesThe City of Tempe Business Survey was first conducted in 2017 and will occur every two years.Additional InformationSource: Business SurveyContact (author): Wydale HolmesContact E-Mail (author): wydale_holmes@tempe.govContact (maintainer): Wydale HolmesContact E-Mail (maintainer): wydale_holmes@tempe.govData Source Type: ExcelPreparation Method: The City contracts with a vendor to conduct the survey, analyze the data and prepare for publication.Publish Frequency: Every other yearPublish Method: Manual, .pdf

Context

The purpose of this data is to provide convenience for people who are researching the economic effects of covid-19 and lockdown on tourism. this data is from 4 clusters and 4 subsets. i searched Literature about covid-19, lockdown, tourism, and economic and i collected all articles in one file

About

https://storage.googleapis.com/kaggle-datasets-images/1752805/2862580/526ad9ef232d40155e3cc338bc3d9877/data-original.png?t=2021-11-28-14-22-53" alt="Cluster">

Acknowledgements

i made 2 folder for CSV binary folder: covid-19 and economic.csv: related with covid-19 and economics. covid-19-and-lockdown.csv: related with covid-19 and lockdown. covid-19 and tourism.csv: related with covid-19 and tourism. lockdown and economic.csv: related with lockdown and economic. tourism-and-economic.csv: related with Tourism and economics. tourism-and-lockdown.csv: related with Tourism and lockdown.

• Ternary Folder: covid-19-lockdown-economic.csv: related with covid-19, lockdown, and economics. covid-19-lockdown_-tourism.csv: related with covid-19, lockdown and tourism. covid-19-tourism-economic.csv: related with covid-19, tourism, and economics. tourism-economy-lockdowns.csv: related with tourism, economics, and lockdown.

• Metadata.csv - you can find all articles inside

Citation @Misc{10.34740/kaggle/dsv/2862580, author = {ER,Anıl Vatan and ÇELİK, Rojda Buse}, title = {Economic Effects Of Covid-19 Lockdown On Tourism}, year = {2021}, address = {Turkey}, url = {https://doi.org/10.34740/kaggle/dsv/2862580}, url = {https://www.kaggle.com/pavyonfaresi/economic-effects-of-covid19-lockdown-on-tourism}, doi = {10.34740/kaggle/dsv/2862580}, abstract = {The purpose of this data is to provide convenience for people who are researching the economic effects of covid-19 and lockdown on tourism.this data is from 4 clusters and 4 subsets. i searched Literature about covid-19, lockdown, tourism, and economic and i collected all articles in one file}, keywords = {Lockdown,tourism, COVID-19,economics} }

GDP: Ind: SI: Manufacturing data was reported at 2,799,556.000 NTD mn in Sep 2025. This records an increase from the previous number of 2,722,040.000 NTD mn for Jun 2025. GDP: Ind: SI: Manufacturing data is updated quarterly, averaging 689,723.000 NTD mn from Mar 1981 (Median) to Sep 2025, with 179 observations. The data reached an all-time high of 2,799,556.000 NTD mn in Sep 2025 and a record low of 135,238.000 NTD mn in Mar 1981. GDP: Ind: SI: Manufacturing 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.AA: SNA 08: Reference Year=2021: GDP: by Industry: Current Price.