A majority of business respondents to a survey did not foresee reducing employee costs due to the coronavirus (COVID-19) slowdown in India as of mid-March 2020. However, about 17 percent each considered freezing incentives and benefits for the year, and reducing headcount based on performance.

India went into lockdown on March 25, 2020, the largest in the world, restricting 1.3 billion people.

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

This page is no longer updated. It has been superseded by the Business insights and impacts on the UK economy dataset page (see link in Notices).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.

In a 2020 survey, roughly ** percent of surveyed people revealed that their cost of doing business due to coronavirus (COVID-19) pandemic increased by *** to **** percent. During that same survey, ** percent of surveyed people revealed that their post COVID-19 expected revenue for 2020 will be over ** percent lower compared to pre-crisis revenue expectations for 2020.

Sweden Business Survey: COVID-19 Effect: Turnover: Total Business (TB): Response Rate data was reported at 41.000 % in 11 Aug 2021. This stayed constant from the previous number of 41.000 % for 15 Jul 2021. Sweden Business Survey: COVID-19 Effect: Turnover: Total Business (TB): Response Rate data is updated daily, averaging 47.000 % from May 2020 (Median) to 11 Aug 2021, with 21 observations. The data reached an all-time high of 51.000 % in 10 Feb 2021 and a record low of 26.000 % in 29 Jul 2020. Sweden Business Survey: COVID-19 Effect: Turnover: Total Business (TB): Response Rate data remains active status in CEIC and is reported by National Institute of Economic Research. The data is categorized under Global Database’s Sweden – Table SE.S008: Business Survey: COVID-19 Effect: Turnover (Discontinued).

To create the dataset, the top 10 countries leading in the incidence of COVID-19 in the world were selected as of October 22, 2020 (on the eve of the second full of pandemics), which are presented in the Global 500 ranking for 2020: USA, India, Brazil, Russia, Spain, France and Mexico. For each of these countries, no more than 10 of the largest transnational corporations included in the Global 500 rating for 2020 and 2019 were selected separately. The arithmetic averages were calculated and the change (increase) in indicators such as profitability and profitability of enterprises, their ranking position (competitiveness), asset value and number of employees. The arithmetic mean values of these indicators for all countries of the sample were found, characterizing the situation in international entrepreneurship as a whole in the context of the COVID-19 crisis in 2020 on the eve of the second wave of the pandemic. The data is collected in a general Microsoft Excel table. Dataset is a unique database that combines COVID-19 statistics and entrepreneurship statistics. The dataset is flexible data that can be supplemented with data from other countries and newer statistics on the COVID-19 pandemic. Due to the fact that the data in the dataset are not ready-made numbers, but formulas, when adding and / or changing the values in the original table at the beginning of the dataset, most of the subsequent tables will be automatically recalculated and the graphs will be updated. This allows the dataset to be used not just as an array of data, but as an analytical tool for automating scientific research on the impact of the COVID-19 pandemic and crisis on international entrepreneurship. The dataset includes not only tabular data, but also charts that provide data visualization. The dataset contains not only actual, but also forecast data on morbidity and mortality from COVID-19 for the period of the second wave of the pandemic in 2020. The forecasts are presented in the form of a normal distribution of predicted values and the probability of their occurrence in practice. This allows for a broad scenario analysis of the impact of the COVID-19 pandemic and crisis on international entrepreneurship, substituting various predicted morbidity and mortality rates in risk assessment tables and obtaining automatically calculated consequences (changes) on the characteristics of international entrepreneurship. It is also possible to substitute the actual values identified in the process and following the results of the second wave of the pandemic to check the reliability of pre-made forecasts and conduct a plan-fact analysis. The dataset contains not only the numerical values of the initial and predicted values of the set of studied indicators, but also their qualitative interpretation, reflecting the presence and level of risks of a pandemic and COVID-19 crisis for international entrepreneurship.

Sweden Business Survey: COVID-19 Effect: Turnover: Manufacturing: Consumer Goods (CG): Response Rate data was reported at 53.000 % in 11 Aug 2021. This records a decrease from the previous number of 54.000 % for 15 Jul 2021. Sweden Business Survey: COVID-19 Effect: Turnover: Manufacturing: Consumer Goods (CG): Response Rate data is updated daily, averaging 66.000 % from May 2020 to 11 Aug 2021, with 21 observations. The data reached an all-time high of 71.000 % in 26 Aug 2020 and a record low of 21.000 % in 29 Jul 2020. Sweden Business Survey: COVID-19 Effect: Turnover: Manufacturing: Consumer Goods (CG): Response Rate data remains active status in CEIC and is reported by National Institute of Economic Research. The data is categorized under Global Database’s Sweden – Table SE.S008: Business Survey: COVID-19 Effect: Turnover (Discontinued).

Business Activity Trends During COVID-19 uses the rate that businesses post on Facebook compared to pre-crisis levels to measure how crisis events are affecting different economic sectors each day.

Learn more details here: https://dataforgood.facebook.com/dfg/tools/business-activity-trends and https://dataforgood.facebook.com/dfg/resources/business-activity-trends-methodology-paper

https://data.humdata.org/dataset/facebook-business-activity-trends-during-covid19?force_layout=desktop

Among businesses in Nigeria, the most significant sources of hardship due to the pandemic are the restriction of movement, the increase in cost of transport and of raw materials. The restriction of movement was pointed out more frequently by informal businesses as the most relevant cause. Formal businesses, instead, indicated the decline in sales revenue more often than informal enterprises.

Eight out of ten businesses in South Africa predicted in April 2020 they could survive up to three months, if the coronavirus would leave them without any form of revenue. This based on response to a survey which asked companies from various industries on the impact of COVID-19. For roughly ** percent of businesses, the situation was already tense as they said they could survive for maximum *** month without any turnover. Furthermore, over half of the respondents said to survive for one to three months without any incoming financial resources, whereas just *** percent mentioned to survive for longer than three months without any turnover.

In April 2020, the economic situation in Poland was assessed as the worst in all presented areas of the economy due to the coronavirus pandemic. The most pessimistic assessments were formulated by those operating in the field of accommodation and catering. Companies reported the lowest deterioration of ratings from the financial and insurance activity, as well as from information and communication sections. In May, the economic situation is assessed less pessimistic than in April in most of the presented sectors. The most pessimistic assessments are made by those operating in the field of accommodation and catering. In contrast, companies from the information and communication section, and financial and insurance activities made the least pessimistic ones.

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

The Paycheck Protection Program (PPP) is a $953-billion business loan program established by the United States federal government, led by the Donald Trump administration in 2020 through the Coronavirus Aid, Relief, and Economic Security Act (CARES Act) to help certain businesses, self-employed workers, sole proprietors, certain non-profit organizations, and tribal businesses continue paying their workers.

The Paycheck Protection Program allows entities to apply for low-interest private loans to pay for their payroll and certain other costs. The amount of a PPP loan is approximately equal to 2.5 times the applicant's average monthly payroll costs. In some cases, an applicant may receive a second draw typically equal to the first. The loan proceeds may be used to cover payroll costs, rent, interest, and utilities. The loan may be partially or fully forgiven if the business keeps its employee counts and employee wages stable. The program is implemented by the U.S. Small Business Administration. The deadline to apply for a PPP loan was March 31, 2021.

Some economists have found that the PPP did not save as many jobs as purported and aided too many businesses that were not at risk of going under. They noted that other programs, such as unemployment insurance, food assistance, and aid to state and local governments, would have been more efficient at strengthening the economy. Opponents to this view note that the PPP functioned well to prevent business closures and cannot be measured on the number of jobs saved alone.

According to a 2022 study, the PPP: cumulatively preserved between 2 and 3 million job-years of employment over 14 months at a cost of $169K to $258K per job-year retained. These numbers imply that only 23 to 34 percent of PPP dollars went directly to workers who would otherwise have lost jobs; the balance flowed to business owners and shareholders, including creditors and suppliers of PPP-receiving firms. Program incidence was ultimately highly regressive, with about three-quarters of PPP funds accruing to the top quintile of households. PPP's breakneck scale-up, its high cost per job saved, and its regressive incidence have a common origin: PPP was essentially untargeted because the United States lacked the administrative infrastructure to do otherwise. Harnessing modern administrative systems, other high-income countries were able to better target pandemic business aid to firms in financial distress. Building similar capacity in the U.S. would enable improved targeting when the next pandemic or other large-scale economic emergency inevitably arises.

Additional Information Field: Value Created: April 5, 2022 Format: CSV License: Other (Public Domain) Size: 428.6 MiB

Decisions to shutdown economic activities to control the spread of COVID-19 early in the pandemic remain controversial, with negative impacts including high rates of unemployment. Here we present a counterfactual scenario for the state of California in which the economy remained open and active during the pandemic’s first year. The exercise provides a baseline against which to compare actual levels of job losses. We developed an economic-epidemiological mathematical model to simulate outbreaks of COVID-19 in ten large Californian socio-economic areas. Results show that job losses are an unavoidable consequence of the pandemic, because even in an open economy, debilitating illness and death among workers drive economic downturns. Although job losses in the counterfactual scenario were predicted to be less than those actually experienced, the cost would have been the additional death or disablement of tens of thousands of workers. Furthermore, whereas an open economy would have favoured populous, services-oriented coastal areas in terms of employment, the opposite would have been true of smaller inland areas and those with relatively larger agricultural sectors. Thus, in addition to the greater cost in lives, the benefits of maintaining economic activity would have been unequally distributed, exacerbating other realized social inequities of the disease’s impact.

Sweden Business Survey: COVID-19 Effect: Turnover: Services: Business Management Activities (BM): Response Rate data was reported at 42.000 % in 11 Aug 2021. This records an increase from the previous number of 21.000 % for 15 Jul 2021. Sweden Business Survey: COVID-19 Effect: Turnover: Services: Business Management Activities (BM): Response Rate data is updated daily, averaging 29.000 % from May 2020 (Median) to 11 Aug 2021, with 21 observations. The data reached an all-time high of 42.000 % in 11 Aug 2021 and a record low of 7.000 % in 29 Jul 2020. Sweden Business Survey: COVID-19 Effect: Turnover: Services: Business Management Activities (BM): Response Rate data remains active status in CEIC and is reported by National Institute of Economic Research. The data is categorized under Global Database’s Sweden – Table SE.S008: Business Survey: COVID-19 Effect: Turnover (Discontinued).

Context

Massachusetts has been publishing city and town COVID-19 case rate data for about three weeks now. I've been making maps out of it with R (e.g., here), and have written up a bit about how in my blog.

Content

Each week's data is complete for January 1st through the given date (April 14th, 22nd, and 29th, so far). The state publishes a case count and a rate (per 100,000) per city, plus a count for where the city was unknown and the state totals (last two rows). Raw state data columns are marked with the date. Adjusted columns have some estimates in them of case counts (where the state was vague), and rates (where the state omitted them), but otherwise match the state data. The county and population are included for each city.

Note that the population data is from the US Census and is not the same as the populations the state used to calculate their rates.

Acknowledgements

Massachusetts Department of Public Health data: current edition. I have archived the previous versions to do the diffs, but you can probably get your own copies from the WayBack Machine. (If you do so, avoid the bad data from the evening of April 22nd.) Data was extracted using the R package docxtractor.

Census data: This product uses the Census Bureau Data API but is not endorsed or certified by the Census Bureau. Data was obtained from the estimates API (2018) using the R package tidycensus.

Inspiration

I made some maps from this data, both static and with Leaflet, to try to get a better sense of what was going on in the state and where. The latest one is here. Suggestions for improvement are welcome.

The majority of the surveyed companies have increased their spending on digital and technology initiatives in the past year during the COVID-19 pandemic, while other costs generally saw a decrease. Additionally, ** percent of companies increased their number of full-time equivalent (FTEs) employees in digital/tech roles, whereas ** percent of respondents reported decrease in overall numbers of FTEs .

According to a survey on businesses and enterprises in Singapore, ** percent of the respondents pointed to costs related to foreign manpower as the additional major costs for their businesses that had arisen from combating COVID-19. A significant amount of small and medium enterprises (SME) stated that there were no extra expenses caused by the COVID-19 pandemic.

Women-owned businesses have been more affected by the outbreak of the coronavirus (COVID-19) pandemic than male-owned firms. In all regions of the world, female-owned businesses experienced higher closure rates in 2020. In South Asia, ** percent of businesses owned by females were threatened with closing, compared to ** percent of male-owned businesses.

■Purpose and Overview (Summary): The government subsidizes 2/3 or 3/4 of the costs for small businesses that are taking concrete measures (Responding to supply chain damage, shifting to a non-face-to-face business model, and creating a telework environment) to overcome the impact of COVID-19 on their business environment. They prepare a business plan based on the advice of the local chamber of commerce or industry in their area, and work steadily to develop sales channels in accordance with the plan. The maximum amount of the subsidy is 1 million JPY.

Furthermore, if measures to prevent the spread of infection based on the guidelines for each industry (business resumption quota) are implemented, a flat-rate subsidy of up to 500,000 JPY will be added. In addition, an additional limit of 500,000 JPY can be added for industries where cluster measures are considered particularly necessary.

• Small businesses operating in the Chamber of Commerce and Industry area are invited to apply to the Chamber of Commerce and Industry, which also runs a similar business. ■ Purpose and Overview: Small Businesses and Non-Profit Organizations (hereinafter referred to as "small business operators, etc.".) In order to respond to the system changes (Work style reform, expansion of employee insurance coverage, introduction of Wage Increases and invoice, etc.) that will be faced one after another over the next several years, the Government will subsidize part of the costs of efforts by small businesses to develop sales channels, etc., in order to improve productivity and achieve sustainable development of small businesses that support local employment and industries. grant Business subsidizes a portion of the expenses required for the steady efforts of small business operators, etc. to develop markets based on a management plan for sustainable management (Examples: devising ways of selling to enter new markets, improving and developing products to attract new customer segments, etc.). In addition, in this public offering, we will focus on providing support to businesses that are actively investing to overcome the impact of COVID-19 on the business environment while developing new markets.

At the same time, we will subsidize businesses to take the minimum infection prevention measures necessary to continue their business in light of the industry specific guidelines for business resumption (business resumption framework).

■ Remarks: Please refer to the COVID Special Response Public Offering Guidelines for details, including those eligible for assistance.

Note on the Immediate Payment Scheme: This scheme cannot be used by e-filing J-Grants. If you want to use it, please apply by mail.

■ Contact: Business grant Contact

If you are doing business within the jurisdiction of the Chamber, please contact your local office.

< list of local offices here >

Contact Hours:

9: 30~12:00, 13:00~17:30(Excluding weekends and holidays, year-end and New Year holidays)

■ Reference URL: Click here to download form sheet

Click here to download jGrants Application Guide

All Japan Federation of Commerce and Industry HP: http://www.shokokai.or.jp/jizokuka_t/ ,

Sweden Business Survey: COVID-19 Effect: SO: Trade: Retail: Others: Response Rate data was reported at 73.000 % in 11 Aug 2021. This records an increase from the previous number of 35.000 % for 15 Jul 2021. Sweden Business Survey: COVID-19 Effect: SO: Trade: Retail: Others: Response Rate data is updated daily, averaging 63.000 % from May 2020 (Median) to 11 Aug 2021, with 19 observations. The data reached an all-time high of 96.000 % in 13 Jan 2021 and a record low of 35.000 % in 15 Jul 2021. Sweden Business Survey: COVID-19 Effect: SO: Trade: Retail: Others: Response Rate data remains active status in CEIC and is reported by National Institute of Economic Research. The data is categorized under Global Database’s Sweden – Table SE.S009: Business Survey: COVID-19 Effect: Seizing Operations (Discontinued).

Abstract

The world is witnessing rapid changes resulting from the Coronavirus pandemic (COVID-19), which it is affecting all aspects of life. It is quite obvious that such effects have negatively impacted the economic, social, environmental and health conditions. This critical situation has imposed tough challenges against the Palestinian economy that would require observation, following up and monitoring the Palestinian institutions' economic conditions during the pandemic in order to measure the size of changes that have occurred on those institutions' economic conditions, as well as being comparable with normal and exceptional conditions. To that end, the Palestinian Central Bureau of Statistics (PCBS) took the responsibility of implementing the COVID-19 Business Pulse Survey to meet the needs of policy and decision makers from both the private and public sectors, in addition to civil society and international institutions in a manner that contributes to developing programs and interventions that can mitigate the impacts and consequences of this pandemic.

Despite the closure of borders around the world and the aggressive containment measures, the Coronavirus (COVID19) continues to spread globally. Therefore, the aim of the COVID-19 Business Pulse Survey, 2020 is to assess the dynamics of the impacts of COVID-19 on small, medium and large institutions in Palestine.

Geographic coverage

National

Analysis unit

Enterprises

Universe

The survey covered a national sample of enterprises working in any of the following activities: industry, construction, internal trade, information and communication, transportation and storage, and services.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample and Frame: The sample is One-Stage Stratified Systematic Random Sample (without replacement).

Sample Strata: Three levels are used to divide the population into strata: 1. Region (North of the West Bank in addition to Jericho Governorate, Ramallah and Al-Bireh Governorate, Jerusalem Governorate, Bethlehem Governorate, Hebron Governorate, Gaza Strip) 2. Strata were created based on the fourth digit of ISIC-4, excluding services sector based on the second in which every activity presents an actual stratum. 3. Enterprise size (small, medium, large) by number of employees.

Sample Size: 13,974 enterprises were reached of which,11,243 enterprises responded on COVID-19 questions, and 10,602 enterprises responded on financial questions (baseline of economic indicators)

Mode of data collection

Face-to-face [f2f] & Computer Assisted telephone Interview [cati]

Research instrument

The survey's questionnaire was designed to achieve the objectives of this study. The questionnaire included essential variables required to study the impacts of COVID-19 on small, medium and large institutions in the West Bank and Gaza. It was oriented by joint efforts between PCBS team and the World Bank team and cooperation with GIZ and international institutions adaptation to the Palestinian situation.

Note: The questionnaire could be seen in the documentation materials tab.

Cleaning operations

Notes on Data:

1. The data was separated into two files, one file contains the data for establishment's responses on COVID-19 questions, and the other contains the data for establishment's responses on financial questions (baseline of economic indicators). The two data sets cannot be combined at this stage.

2. The financial data (baseline of economic indicators) excluded those parts of Jerusalem which were annexed by Israeli Occupation in 1967.

3. The services survey covers profit, non-profit enterprises, and output of non-profit enterprises in the National Accounts System 2008 (SNA'2008) equals to the value of intermediate consumption, and the value of employee compensation, and the value of depreciation of fixed assets, in addition to the value of net taxes and fees on production.

4. Financial data were collected in NIS

Response rate

Response Rate: For COVID-19 survey the Response rate values is: - The size of the selected sample in Palestine was 13,974 institutions. - The size of the achieved sample from the field was 11,243 institutions in Palestine. - Non-response cases: 1,491. - Over-coverage cases: 1,240. - Net sample: 12,734 - Response rate: 88.3%. - Non-response rate: 11.7 %. - Over-coverage rate: 8.9%.

For financial questions (baseline of economic indicators), the response rate values is: - The size of the achieved sample from the field was 10,643 institutions in Palestine. - Non-response cases: 2,023. - Over-coverage cases: 1,308. - Net sample: 12,666 - Response rate: 84.0%. - Non-response rate: 16.0 %. - Over-coverage rate: 9.4%