In 2020, global gross domestic product declined by 6.7 percent as a result of the coronavirus (COVID-19) pandemic outbreak. In Latin America, overall GDP loss amounted to 8.5 percent.

Brazilian and Indian share prices became the highest performing of the major developed and emerging economies as of June 2023, with index values of 235.25 and 230.91 respectively in that month. Conversely, the lowest-performing were China and the Germany, both with index values of 86.98 and 113.04 respectively at this time. The index value is calculated with 2015 values as the baseline (i.e. 2015 = 100).

This 6MB download is a zip file containing 5 pdf documents and 2 xlsx spreadsheets. Presentation on COVID-19 and the potential impacts on employment

May 2020Waka Kotahi wants to better understand the potential implications of the COVID-19 downturn on the land transport system, particularly the potential impacts on regional economies and communities.

To do this, in May 2020 Waka Kotahi commissioned Martin Jenkins and Infometrics to consider the potential impacts of COVID-19 on New Zealand’s economy and demographics, as these are two key drivers of transport demand. In addition to providing a scan of national and international COVID-19 trends, the research involved modelling the economic impacts of three of the Treasury’s COVID-19 scenarios, to a regional scale, to help us understand where the impacts might be greatest.

Waka Kotahi studied this modelling by comparing the percentage difference in employment forecasts from the Treasury’s three COVID-19 scenarios compared to the business as usual scenario.

The source tables from the modelling (Tables 1-40), and the percentage difference in employment forecasts (Tables 41-43), are available as spreadsheets.

Arataki - potential impacts of COVID-19 Final Report

Employment modelling - interactive dashboard

The modelling produced employment forecasts for each region and district over three time periods – 2021, 2025 and 2031. In May 2020, the forecasts for 2021 carried greater certainty as they reflected the impacts of current events, such as border restrictions, reduction in international visitors and students etc. The 2025 and 2031 forecasts were less certain because of the potential for significant shifts in the socio-economic situation over the intervening years. While these later forecasts were useful in helping to understand the relative scale and duration of potential COVID-19 related impacts around the country, they needed to be treated with care recognising the higher levels of uncertainty.

The May 2020 research suggested that the ‘slow recovery scenario’ (Treasury’s scenario 5) was the most likely due to continuing high levels of uncertainty regarding global efforts to manage the pandemic (and the duration and scale of the resulting economic downturn).

The updates to Arataki V2 were framed around the ‘Slower Recovery Scenario’, as that scenario remained the most closely aligned with the unfolding impacts of COVID-19 in New Zealand and globally at that time.

Find out more about Arataki, our 10-year plan for the land transport system

May 2021The May 2021 update to employment modelling used to inform Arataki Version 2 is now available. Employment modelling dashboard - updated 2021Arataki used the May 2020 information to compare how various regions and industries might be impacted by COVID-19. Almost a year later, it is clear that New Zealand fared better than forecast in May 2020.Waka Kotahi therefore commissioned an update to the projections through a high-level review of:the original projections for 2020/21 against performancethe implications of the most recent global (eg International monetary fund world economic Outlook) and national economic forecasts (eg Treasury half year economic and fiscal update)The treasury updated its scenarios in its December half year fiscal and economic update (HYEFU) and these new scenarios have been used for the revised projections.Considerable uncertainty remains about the potential scale and duration of the COVID-19 downturn, for example with regards to the duration of border restrictions, update of immunisation programmes. The updated analysis provides us with additional information regarding which sectors and parts of the country are likely to be most impacted. We continue to monitor the situation and keep up to date with other cross-Government scenario development and COVID-19 related work. The updated modelling has produced employment forecasts for each region and district over three time periods - 2022, 2025, 2031.The 2022 forecasts carry greater certainty as they reflect the impacts of current events. The 2025 and 2031 forecasts are less certain because of the potential for significant shifts over that time.

Data reuse caveats: as per license.

Additionally, please read / use this data in conjunction with the Infometrics and Martin Jenkins reports, to understand the uncertainties and assumptions involved in modelling the potential impacts of COVID-19.

COVID-19’s effect on industry and regional economic outcomes for NZ Transport Agency [PDF 620 KB]

Data quality statement: while the modelling undertaken is high quality, it represents two point-in-time analyses undertaken during a period of considerable uncertainty. This uncertainty comes from several factors relating to the COVID-19 pandemic, including:

a lack of clarity about the size of the global downturn and how quickly the international economy might recover differing views about the ability of the New Zealand economy to bounce back from the significant job losses that are occurring and how much of a structural change in the economy is required the possibility of a further wave of COVID-19 cases within New Zealand that might require a return to Alert Levels 3 or 4.

While high levels of uncertainty remain around the scale of impacts from the pandemic, particularly in coming years, the modelling is useful in indicating the direction of travel and the relative scale of impacts in different parts of the country.

Data quality caveats: as noted above, there is considerable uncertainty about the potential scale and duration of the COVID-19 downturn. Please treat the specific results of the modelling carefully, particularly in the forecasts to later years (2025, 2031), given the potential for significant shifts in New Zealand's socio-economic situation before then.

As such, please use the modelling results as a guide to the potential scale of the impacts of the downturn in different locations, rather than as a precise assessment of impacts over the coming decade.

In July 2024, the global merchandise imports index, excluding the U.S., stood at 192.6. This is compared to a value of 121 for the United States in the same period. In emerging economies, it reached an index level of nearly 291.4.The merchandise imports index is the U.S. dollar value of goods bought from the rest of the world, deflated by the U.S. Consumer Price Index (CPI).

In July 2024, the merchandise exports index worldwide, excluding the U.S., stood at 204.8. This is compared to an index value of 143 for the United States in the same month. The index was highest in emerging economies, reaching an index score of 353. Moreover, the merchandise imports index was also highest in emerging economies. The merchandise exports index is the U.S. dollar value of goods sold to the rest of the world, deflated by the U.S. Consumer Price Index (CPI).

United States - Government current expenditures: Economic affairs: Other economic affairs: Agriculture was 36.41700 Bil. of $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Government current expenditures: Economic affairs: Other economic affairs: Agriculture reached a record high of 65.10400 in January of 2020 and a record low of 2.67800 in January of 1960. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Government current expenditures: Economic affairs: Other economic affairs: Agriculture - last updated from the United States Federal Reserve on July of 2025.

United States - Government current expenditures: Economic affairs was 479.46300 Bil. of $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Government current expenditures: Economic affairs reached a record high of 1035.68500 in January of 2020 and a record low of 11.39800 in January of 1960. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Government current expenditures: Economic affairs - last updated from the United States Federal Reserve on August of 2025.

Abstract

The Future of Business Survey is a new source of information on small and medium-sized enterprises (SMEs). Launched in February 2016, the monthly survey - a partnership between Facebook, OECD, and The World Bank - provides a timely pulse on the economic environment in which businesses operate and who those businesses are to help inform decision-making at all levels and to deliver insights that can help businesses grow. The Future of Business Survey provides a perspective from newer and long-standing digitalized businesses and provides a unique window into a new mobilized economy.

Policymakers, researchers and businesses share a common interest in the environment in which SMEs operate, as well their outlook on the future, not least because young and innovative SMEs in particular are often an important source of considerable economic and employment growth. Better insights and timely information about SMEs improve our understanding of economic trends, and can provide new insights that can further stimulate and help these businesses grow.

To help provide these insights, Facebook, OECD and The World Bank have collaborated to develop a monthly survey that attempts to improve our understanding of SMEs in a timely and forward-looking manner. The three organizations share a desire to create new ways to hear from businesses and help them succeed in the emerging digitally-connected economy. The shared goal is to help policymakers, researchers, and businesses better understand business sentiment, and to leverage a digital platform to provide a unique source of information to complement existing indicators.

With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest.

Geographic coverage

When the survey was initially launched in February 2016, it included 22 countries. When the survey was initially launched in February 2016, it included 22 countries. The Future of Business Survey is now conducted in over 90 countries in every region of the world.

Countries included in at least one wave: Albania Algeria American Samoa Andorra Angola Anguilla Antigua and Barbuda Argentina Aruba Australia Austria Azerbaijan Bahamas (the) Bangladesh Barbados Belarus Belgium Belize Benin Bolivia (Plurinational State of) Bonaire, Sint Eustatius and Saba Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cabo Verde Cambodia Cameroon Canada Cayman Islands (the) Central African Republic (the) Chad Chile Colombia Congo (the) Curaçao Cyprus Czechia Côte d'Ivoire Denmark Djibouti Dominica Dominican Republic (the) Ecuador Egypt El Salvador Equatorial Guinea Estonia Eswatini Ethiopia Faroe Islands (the) Fiji Finland France French Polynesia Gabon Gambia (the) Germany Ghana Gibraltar Greece Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Honduras Hong Kong Hungary Iceland India Indonesia Iraq Ireland Isle of Man Israel Italy Jamaica Japan Jersey Jordan Kenya Korea (the Republic of) Kuwait Lao People's Democratic Republic (the) Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Malawi Malaysia Mali Malta Martinique Mauritania Mauritius Mayotte Mexico Monaco Montenegro Morocco Mozambique Myanmar Namibia Nepal Netherlands (the) New Caledonia New Zealand Nicaragua Niger (the) Nigeria North Macedonia Northern Mariana Islands (the) Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines (the) Poland Portugal Qatar Romania Russian Federation (the) Rwanda Réunion Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Sint Maarten (Dutch part) Slovakia Slovenia Solomon Islands South Africa Spain Sweden Switzerland Taiwan Tanzania, the United Republic of Thailand Timor-Leste Togo Tonga Trinidad and Tobago Tunisia Turkey Turks and Caicos Islands (the) Uganda United Arab Emirates (the) United Kingdom of Great Britain and Northern Ireland (the) United States of America (the) Uruguay Vanuatu Viet Nam Virgin Islands (British) Virgin Islands (U.S.) Zambia.

Analysis unit

The study describes small and medium-sized enterprises.

Universe

The target population consists of SMEs that have an active Facebook business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest.

Kind of data

Sample survey data [ssd]

Sampling procedure

Twice a year in over 97 countries, the Facebook Survey Team sends the Future of Business to admins and owners of Facebook-designated small business pages. When we share data from this survey, we anonymize responses to all survey questions and only share country-level data publicly. To achieve better representation of the broader small business population, we also weight our results based on known characteristics of the Facebook Page admin population.

A random sample of firms, representing the target population in each country, is selected to respond to the Future of Business Survey each month.

Mode of data collection

Internet [int]

Research instrument

The survey includes questions about perceptions of current and future economic activity, challenges, business characteristics and strategy. Custom modules include questions related to regulation, access to finance, digital payments, and digital skills. The full questionnaire is available for download.

Response rate

Response rates to online surveys vary widely depending on a number of factors including survey length, region, strength of the relationship with invitees, incentive mechanisms, invite copy, interest of respondents in the topic and survey design.

Note: Response rates are calculated as the number of respondents who completed the survey divided by the total number of SMEs invited.

Sampling error estimates

Any survey data is prone to several forms of error and biases that need to be considered to understand how closely the results reflect the intended population. In particular, the following components of the total survey error are noteworthy:

Sampling error is a natural characteristic of every survey based on samples and reflects the uncertainty in any survey result that is attributable to the fact that not the whole population is surveyed.

Other factors beyond sampling error that contribute to such potential differences are frame or coverage error (sampling frame of page owners does not include all relevant businesses but also may include individuals that don't represent businesses), and nonresponse error.

Note that the sample is meant to reflect the population of businesses on Facebook, not the population of small businesses in general. This group of digitized SMEs is itself a community worthy of deeper consideration and of considerable policy interest. However, care should be taken when extrapolating to the population of SMEs in general. Moreover, future work should evaluate the external validity of the sample. Particularly, respondents should be compared to the broader population of SMEs on Facebook, and the economy as a whole.

The Politbarometer has been conducted since 1977 on an almost monthly basis by the Research Group for Elections (Forschungsgruppe Wahlen) for the Second German Television (ZDF). Since 1990, this database has also been available for the new German states. The survey focuses on the opinions and attitudes of the voting population in the Federal Republic on current political topics, parties, politicians, and voting behavior. From 1990 to 1995 and from 1999 onward, the Politbarometer surveys were conducted separately in the eastern and western federal states (Politbarometer East and Politbarometer West). The separate monthly surveys of a year are integrated into a cumulative data set that includes all surveys of a year and all variables of the respective year. The Politbarometer short surveys, collected with varying frequency throughout the year, are integrated into the annual cumulation starting from 2003.

The timely availability of indicators to assess the current economic situation is essential for a forward-looking, rapid and appropriate economic policy response. Especially when the situation is changing as fast and as fundamentally as it was at the time of the COVID-19 shutdown, mid-March 2020. While financial market indicators priced in developments in a timely manner, it took until the economic slump was also reflected in the real economic data and leading economic indicators and thus the severity of the economic crisis could be guessed. The aim of the Monitor is therefore to create an extremely timely and meaningful information base that enables a rapid assessment of the current economic situation: 1. Timely, since always Tuesdays (or Wednesdays) the time series are supplemented by the values of the previous week and 2. Meaningful because the time series are adjusted for possible disruptive factors such as seasonal influences, mobile holidays (Easter), temperature fluctuations or other special effects in order to sharpen the relevant economic signal.

Between 2019 and 2020, the number of unemployed people worldwide increased from 191.93 million to 235.21 million, the biggest annual increase in unemployment in this provided time period. In 2022, the number of people unemployed decreased down to 205.25 million.

Russia Current Account Balance: as % of GDP data was reported at -2.100 % in 2021. This records an increase from the previous number of -2.700 % for 2020. Russia Current Account Balance: as % of GDP data is updated yearly, averaging -2.100 % from Dec 2019 (Median) to 2021, with 3 observations. The data reached an all-time high of 4.000 % in 2019 and a record low of -2.700 % in 2020. Russia Current Account Balance: as % of GDP data remains active status in CEIC and is reported by European Commission's Directorate-General for Economic and Financial Affairs. The data is categorized under Russia Premium Database’s Forecast – European Commission's Forecast.

United States - Government current expenditures: Economic affairs: Other economic affairs was 206.29800 Bil. of $ in January of 2023, according to the United States Federal Reserve. Historically, United States - Government current expenditures: Economic affairs: Other economic affairs reached a record high of 799.03600 in January of 2020 and a record low of 4.98500 in January of 1960. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Government current expenditures: Economic affairs: Other economic affairs - last updated from the United States Federal Reserve on September of 2025.

Abstract copyright UK Data Service and data collection copyright owner.BackgroundThe Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The Annual Population Survey, also held at the UK Data Archive, is derived from the LFS.The LFS was first conducted biennially from 1973-1983, then annually between 1984 and 1991, comprising a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter. From 1992 it moved to a quarterly cycle with a sample size approximately equivalent to that of the previous annual data. Northern Ireland was also included in the survey from December 1994. Further information on the background to the QLFS may be found in the documentation.The UK Data Service also holds a Secure Access version of the QLFS (see below); household datasets; two-quarter and five-quarter longitudinal datasets; LFS datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.LFS DocumentationThe documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each user guide volume alongside the appropriate questionnaire for the year concerned (the latest questionnaire available covers July-September 2022). Volumes are updated periodically, so users are advised to check the latest documents on the ONS Labour Force Survey - User Guidance pages before commencing analysis. This is especially important for users of older QLFS studies, where information and guidance in the user guide documents may have changed over time.LFS response to COVID-19From April 2020 to May 2022, additional non-calendar quarter LFS microdata were made available to cover the pandemic period. The first additional microdata to be released covered February to April 2020 and the final non-calendar dataset covered March-May 2022. Publication then returned to calendar quarters only. Within the additional non-calendar COVID-19 quarters, pseudonymised variables Casenop and Hserialp may contain a significant number of missing cases (set as -9). These variables may not be available in full for the additional COVID-19 datasets until the next standard calendar quarter is produced. The income weight variable, PIWT, is not available in the non-calendar quarters, although the person weight (PWT) is included. Please consult the documentation for full details.Occupation data for 2021 and 2022 data filesThe ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.2024 ReweightingIn February 2024, reweighted person-level data from July-September 2022 onwards were released. Up to July-September 2023, only the person weight was updated (PWT23); the income weight remains at 2022 (PIWT22). The 2023 income weight (PIWT23) was included from the October-December 2023 quarter. Users are encouraged to read the ONS methodological note of 5 February, Impact of reweighting on Labour Force Survey key indicators: 2024, which includes important information on the 2024 reweighting exercise.End User Licence and Secure Access QLFS dataTwo versions of the QLFS are available from UKDS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes country and Government Office Region geography, 3-digit Standard Occupational Classification (SOC) and 3-digit industry group for main, second and last job (from July-September 2015, 4-digit industry class is available for main job only).The Secure Access version contains more detailed variables relating to:age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent childfamily unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of familynationality and country of originfiner detail geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district, and other categories;health: including main health problem, and current and past health problemseducation and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeshipsindustry: including industry, industry class and industry group for main, second and last job, and industry made redundant fromoccupation: including 5-digit industry subclass and 4-digit SOC for main, second and last job and job made redundant fromsystem variables: including week number when interview took place and number of households at addressother additional detailed variables may also be included.The Secure Access datasets (SNs 6727 and 7674) have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. Weighting variablesUsers should note that this quarter includes the 2023 person and income weights, PWT23 and PIWT23. Main Topics:The QLFS questionnaire comprises a 'core' of questions which are included in every survey, together with some 'non-core' questions which vary from quarter to quarter.The questionnaire can be split into two main parts. The first part contains questions on the respondent's household, family structure, basic housing information and demographic details of household members. The second part contains questions covering economic activity, education and health, and also may include a few questions asked on behalf of other government departments (for example the Department for Work and Pensions and the Home Office). Until 1997, the questions on health covered mainly problems which affected the respondent's work. From that quarter onwards, the questions cover all health problems. Detailed questions on income have also been included in each quarter since 1993. The basic questionnaire is revised each year, and a new version published, along with a transitional version that details changes from the previous year's questionnaire. Four sampling frames are used. See documentation for details.

The purpose of the study: to analyse Lithuanian residents opinion about environmental problems and its effect to society. Major investigated questions: first, the goal was to identify the current most important socio-economic issue that Lithuania is facing, and which issue comes in second. A block of statements to choose from (Private enterprise is the best method to solve Lithuania’s economic difficulties; The government should reduce income disparities between people with high and low incomes; 5 in total) was used to elicit responses on a range of topics. A list of various socio-political issues was provided to find out which issue, according to the respondent, Lithuania should prioritize the most. Respondents were asked whether they feel like they can trust most people or do they feel that they should be extremely cautious when interacting with others. The trust in institutions among respondents was researched (Media; Universities and other research centres; 4 in total). Next, respondents in Lithuania were asked to indicate the extent to which they care about environmental issues. After providing a list of some of the environmental problems, the respondents were asked to indicate which of these problems is the most important for Lithuania as a country. The question asked about the perception of the world's climate and the idea that it has been changing in recent decades. Those who answered that the world's climate is changing were asked to assess how bad or good the effects of climate change will be for the world as a whole and for Lithuania. Next, all respondents were asked to rate a block of statements (Modern science will solve our environmental problems with little change in our way of life; 6 in total). The Lithuanian population was asked three questions on whether they would be willing to pay much higher prices, higher taxes, and accept a lower standard of living if it helped protect the environment. They were also asked whether they would be willing to accept a reduction in the size of Lithuania's protected areas to open them up for economic development. Again, a block of statements explored respondents' views on a range of environmental issues (It is too difficult for people like me to do much for the environment; 7 in total). Respondents rated the environmental hazard of various things they had been told (air pollution from cars; air pollution from industry; 7 in total). The question asked which ways would most encourage business and industry and people in Lithuania to protect the environment. The question asked respondents to indicate their level of enjoyment in being outdoors in general and how often, if at all, they engaged in any leisure activities in nature over the past 12 months. For example, activities such as hiking, bird watching, swimming, skiing, or any other outdoor activities were inquired about. The survey aimed to gather information on various aspects related to respondents' transportation habits, dietary preferences, household characteristics, environmental practices, and civic engagement regarding environmental issues. Specifically, it inquired about the number of airplane trips taken over the past 12 months, the average number of hours spent in a typical week in a motorized vehicle (excluding public transport), the frequency of consuming beef, lamb, or products containing them, and the number of rooms in respondents' homes (apartments or houses). Additionally, questions were posed regarding the frequency of sorting glass, cans, plastic, newspapers, or similar items for recycling, and whether respondents often avoided buying certain products due to environmental reasons. They were asked if they were members of any group primarily focused on environmental protection or conservation. The survey also aimed to assess the civic engagement of Lithuanian residents regarding environmental issues over the past five years, including whether they signed a petition concerning environmental problems (3 in total). Lastly, respondents were asked to evaluate how various factors, such as air pollution, affected their residential area over the past 12 months, if at all (3 in total). Socio-demographic characteristics: gender, age, level of education, membership in organizations, religion, marital status, nationality, political views, political participation, size of household, respondent's average personal income, place of residence, working situation of the respondent and of his/her spouse or partner.

Covid-19 has affected people in various ways, directly through disease and death, and indirectly through disease containment measures. Understanding how the pandemic and countermeasures agaist it impacted quality of life is valuable for policy makers.

To address and compare the various components of quality of life, a suitable framework is needed, which the capability approach provides. This approach measures quality of life as opportunities, compared to traditional welfarist economics that defines wellbeing as utility.

For this study, we used a capability list from a Swedish governmental investigation (SOU 2015:56) that suggested relevant capabilities for the Swedish situation: Financial situation, Social relations, Health, Housing, Living environment, Occupation, Knowledge, Security, Time balance, and Political and civil rights.

The study was performed in June 2020. In an internet-based survey, we quota-sampled 500 Swedish residents from a commercial web-panel, after population proportions of age, region of residence, education, gender.

The survey started with the informed consent statement, followed by questions on participants’ current baseline capability levels in the ten capability dimensions (Low, Medium, Complete). Next followed questions about perceived changes in capability during 2020 in the ten dimensions on a five-item Likert scale (Much less, Less, Equal, Higher, Much higher). The survey ended with a number of background questions on socio-economic and demographic conditions.

Sampling large numbers of participants using a commercial web panel is administratively more feasible and quicker than other sampling methods, such as for example direct sampling from the general population. Also, the response rate may be higher and data handling easier. On the other hand, it is less transparent how recruitment into the study was performed and web panel participants may not be representative of the population. Those limitations should be kept in mind when analysing the data and interpreting results.

Data were collected with a PHP-based web application for surveys (limesurvey version 4.2.2, https://www.limesurvey.org) hosted on a Umeå university server. The data was collected anonymously.

In July 2024, global industrial production, excluding the United States, increased by 1.5 percent compared to the same time in the previous year, based on three month moving averages. This is compared to an increase of 0.2 percent in advanced economies (excluding the United States) for the same time period. The global industrial production collapsed after the outbreak of COVID-19, but increased steadily in the months after, peaking at 23 percent in June 2021. Industrial growth rate tracks the output production in the industrial sector.

Since 2013, the Federal Reserve Board has conducted the Survey of Household Economics and Decisionmaking (SHED), which measures the economic well-being of U.S. households and identifies potential risks to their finances. The survey includes modules on a range of topics of current relevance to financial well-being including credit access and behaviors, savings, retirement, economic fragility, and education and student loans. The Board's seventh annual SHED examines the economic well-being and financial lives of U.S. adults and their families. The 2019 complete survey was conducted in October 2019, offering a picture of personal finances prior to the onset of the COVID-19 pandemic. To obtain updated information in the midst of closures and stay-at-home orders, a smaller supplemental survey was conducted in April 2020, focusing on labor market effects and households' overall financial circumstances at that time. Demographic variables include age, level of education, gender, race, household income, and marital status. Users can use the industry information included in the data to obtain a perspective on financial conditions resulting from COVID-19 for individuals who work in arts and culture related fields.