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TwitterAccording to a survey fielded in Mexico in ***********, ** percent of respondents stated having to close their businesses as a result of the COVID-19 pandemic. This represents a noticeable decrease compared to April, when ** percent of participants said they had to shut down their businesses.
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TwitterDuring an online survey, *** percent of surveyed small businesses in the United States said they had temporarily closed a location due to the COVID-19 pandemic during the week ending April 17, 2022. Another *** percent of respondents said that they had opened a previously closed location during the same week.
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TwitterAlmost one quarter of all businesses have temporarily closed or paused trading due to the Coronavirus (COVID-19) pandemic in the United Kingdom as of April 2020. The sector with the highest share of business closures were those in the arts, entertainment, and recreation sector, with over ** percent of them currently closed, compared with just *** percent of human health, and social work businesses.
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TwitterODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
This dataset is no longer being updated as of 7/1/2021. It is being retained on the Open Data Portal for its potential historical interest.
A list of retail stores, restaurants, personal services and other businesses open and closed during the COVID-19 pandemic. Also indicates if business is offering delivery, pick up or on-line sales.
Updated at least biweekly during Covid-19 Pandemic.
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TwitterThese are the key findings from the second of three rounds of the DCMS Coronavirus Business Survey. These surveys are being conducted to help DCMS understand how our sectors are responding to the ongoing Coronavirus pandemic. The data collected is not longitudinal as responses are voluntary, meaning that businesses have no obligation to complete multiple rounds of the survey and businesses that did not submit a response to one round are not excluded from response collection in following rounds.
The indicators and analysis presented in this bulletin are based on responses from the voluntary business survey, which captures organisations responses on how their turnover, costs, workforce and resilience have been affected by the coronavirus (COVID-19) outbreak. The results presented in this release are based on 3,870 completed responses collected between 17 August and 8 September 2020.
This is the first time we have published these results as Official Statistics. An earlier round of the business survey can be found on gov.uk.
We have designated these as Experimental Statistics, which are newly developed or innovative statistics. These are published so that users and stakeholders can be involved in the assessment of their suitability and quality at an early stage.
We expect to publish a third round of the survey before the end of the financial year. To inform that release, we would welcome any user feedback on the presentation of these results to evidence@dcms.gov.uk by the end of November 2020.
The survey was run simultaneously through DCMS stakeholder engagement channels and via a YouGov panel.
The two sets of results have been merged to create one final dataset.
Invitations to submit a response to the survey were circulated to businesses in relevant sectors through DCMS stakeholder engagement channels, prompting 2,579 responses.
YouGov’s business omnibus panel elicited a further 1,288 responses. YouGov’s respondents are part of their panel of over one million adults in the UK. A series of pre-screened information on these panellists allows YouGov to target senior decision-makers of organisations in DCMS sectors.
One purpose of the survey is to highlight the characteristics of organisations in DCMS sectors whose viability is under threat in order to shape further government support. The timeliness of these results is essential, and there are some limitations, arising from the need for this timely information:
This release is published in accordance with the Code of Practice for Statistics, as produced by the UK Statistics Authority. The Authority 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 responsible statistician for this release is Alex Bjorkegren. For further details about the estimates, or to be added to a distribution list for future updates, please email us at evidence@dcms.gov.uk.
The document above contains a list of 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.
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TwitterChanges businesses have made to adapt to the COVID-19 pandemic, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership.
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
The indicators and analysis presented in this bulletin are based on responses from the new voluntary fortnightly business survey, which captures businesses responses on how their turnover, workforce prices, trade and business resilience have been affected in the two week reference period. These data relate to the period 6 April 2020 to 19 April 2020.
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TwitterCompanies in the arts, entertainment and recreation sector have had to shut down their activity the most, since the beginning of the coronavirus crisis (COVID-19). Companies in this sector have been closed for an average of almost 100 days. The hotel industry was the second sector most affected by closures. The pharmaceutical industry was the least affected by closures. On average, French companies were closed for ** days in France.
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TwitterData on the number and value of grants to small and medium sized businesses (SMEs) in response to the coronavirus pandemic.
The spreadsheets show the total amount of money that each local authority and parliamentary constituency in England has:
The ARG scheme is open for payments until 31 March 2022 and following the closure of this scheme a final update to the data will be published.
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Local authorities have received and distributed funding to support small and medium businesses in England during coronavirus. The datasets cover schemes managed by local authorities: Additional Restrictions Support Grant (ARG) Restart Grant - closed June 2021 Local Restrictions Support Grants (LRSG) and Christmas support payments - closed 2021 Small Business Grants Fund (SBGF) - closed August 2020 Retail, Hospitality and Leisure Business Grants Fund (RHLGF) - closed August 2020 Local Authority Discretionary Grants Fund (LADGF) - closed August 2020 The spreadsheets show the total amount of money that each local authority in England: received from central government distributed to SMEs 20 December 2021 update We have published the latest estimates by local authorities for payments made under this grant programme: Additional Restrictions Grants (up to and including 28 November 2021) The number of grants paid out is not necessarily the same as the number of businesses paid. The data has not received full verification.
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TwitterNOTE: This program is no longer active. This dataset is only for historical reference. This directory contains businesses that have joined VAX CHI NATION, meaning they committed to ensuring that their staff and patrons are vaccinated. These businesses completed the City of Chicago self-certification.
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This page is no longer updated. It has been superseded by the Business insights and impacts on the UK economy dataset page (see link in Notices). It contains comprehensive weighted datasets for Wave 7 onwards. All future BICS datasets will be available there. The datasets on this page include mainly unweighted responses from the voluntary fortnightly business survey, which captures businesses’ responses on how their turnover, workforce prices, trade and business resilience have been affected in the two-week reference period, up to Wave 17.
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TwitterOpen Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Textual analysis of responses from the Business Impacts of Coronavirus (COVID-19) Survey (BICS), providing further insights into the experiences of individual businesses.
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TwitterAs of September 2021, around ** percent of business that closed temporarily due to the COVID-19 pandemic in the United States have reopened. Businesses in the beauty services industries showed the best recovery with ** percent of their previously closed business locations reopened by September 2021.
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TwitterIn March, 2020 U.S. state governors in 44 states issued "do not leave home" orders and assigned "essential" designations to specific industries. We developed a catalog of closure policies (open, open with restrictions, closed) by state for industries whose designation was publicly questioned. The database which accompanies the article identifies restrictions imposed by each state.
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TwitterThe Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of loss of work due to illness with coronavirus for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included a question about the inability to work due to being sick or having a family member sick with COVID-19. The National Health Interview Survey, conducted by NCHS, is the source for high-quality data to monitor work-loss days and work limitations in the United States. For example, in 2018, 42.7% of adults aged 18 and over missed at least 1 day of work in the previous year due to illness or injury and 9.3% of adults aged 18 to 69 were limited in their ability to work or unable to work due to physical, mental, or emotional problems. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who did not work for pay at a job or business, at any point, in the previous week because either they or someone in their family was sick with COVID-19. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/work.htm#limitations
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TwitterAs part of the efforts of the World Bank Group to understand the impact of COVID-19 on the private sector, the Enterprise Analysis unit is conducting follow-up surveys on recently completed Enterprise Surveys (ES) in several countries. These short surveys follow the baseline ES and are designed to provide quick information on the impact and adjustments that COVID-19 has brought about in the private sector. The Zimbabwe Informal Businesses COVID-19 Impact Survey is different from the standard follow-up survey conducted by the unit in other countries, the major difference veing that this is not a follow-up survey.
National
Enterprise
The universe of inference is all registered establishments with five or more employees that are engaged in one of the following activities defined using ISIC Rev. 3.1: manufacturing (groupd D), construction (group F), services sector (groups G and H), transport, storage, and communcations sector (group I) and information technology (division 72 of group K)
Sample survey data [ssd]
The sample for the survey was selected using stratified random sampling, broadly following similar methodology explained in the ES Sampling Note. However, unlike ES that uses three levels of stratification (size, location, and sector), this survey uses two levels of stratification, namely location/region of the informal busines and the gender of the main business owner.
Stratifies random sampling was preferred over simple random sampling for several reasons: a. To obtain unbiased estimates for different subdivisions of the population with some known level of precision b. To obtain unbiased estimates for the whole population. The whole population, or universe of the study, is informal sector businesses operating in Zimbabwe. Informality is defined as any business that doesn't have registration from Zimbabwe Registrar of Companies. c. To make sure that the final total sample includes establishments from different regions and from businesses owned by male and femal. d. To exploit the benefits of stratifies sampling where population estimates, in most cases, will be more precise than using a simple random sampling method (i.e. lower standard errors, other things being equal.) e. Stratification may produce a smaller bound on the error of estimation than would be produced by a simple random sample of the same size. This result is particularly true if measurements within strata are homogeneous. f. The cost per observation in the survey may be reduced by stratification of the population elements into convenient groupings.
Total sample target: 1020
Computer Assisted Telephone Interview [cati]
The questionnaire contains the following modules: - Control information and introduction - General information - Sales and operations - Production - Labor force - Finance - Policies and prospects - Registration - Information on permanently closed establishments - Interview protocol
37.8%
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TwitterPercentage of workforce laid off because of COVID-19, by North American Industry Classification System (NAICS) code, business employment size, type of business and majority ownership.
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TwitterThe American Rescue Plan Act established the Restaurant Revitalization Fund (RRF) to provide funding to help restaurants and other eligible businesses keep their doors open. The American Rescue Plan Act established the Restaurant Revitalization Fund (RRF) to provide funding to help restaurants and other eligible businesses keep their doors open. This program provided restaurants with funding equal to their pandemic-related revenue loss up to $10 million per business and no more than $5 million per physical location. Recipients are not required to repay the funding as long as funds are used for eligible uses no later than March 11, 2023. This dataset details New York State recipients of RRF funds.
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Twitterhttps://www.etalab.gouv.fr/licence-ouverte-open-licencehttps://www.etalab.gouv.fr/licence-ouverte-open-licence
This dataset contains the articles published on the Covid-19 FAQ for companies published by the Directorate-General for Enterprises at https://info-entreprises-covid19.economie.fr
The data are presented in the JSON format as follows: JSON [ { “title”: “Example article for documentation”, “content”: [ this is the first page of the article. here the second, “‘div’these articles incorporate some HTML formatting‘/div’” ], “path”: [ “File to visit in the FAQ”, “to join the article”] }, ... ] “'” The update is done every day at 6:00 UTC. This data is extracted directly from the site, the source code of the script used to extract the data is available here: https://github.com/chrnin/docCovidDGE
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TwitterAccording to a survey fielded in Mexico in ***********, ** percent of respondents stated having to close their businesses as a result of the COVID-19 pandemic. This represents a noticeable decrease compared to April, when ** percent of participants said they had to shut down their businesses.