According to data from McKinsey, ** percent of respondents from the United States were optimistic about their country's economic recovery following COVID-19. ** percent of American respondents were pessimistic.

According to the findings of the survey, almost 40 percent of Hungarians expect the country's economy to recover within a year after the coronavirus (COVID-19) outbreak. Another four percent of respondents believed that Hungary's economy would never recover.

ObjectiveTo quantitatively assess the impact of COVID-19 pandemic on public health, as well as its economic and social consequences in major economies, which is an international public health concern. The objective is to provide a scientific basis for policy interventions.Subject and methodsThis study utilizes a multi-country, multi-sector CGE-COVID-19 model to analyze the repercussions of the pandemic in 2022. The re-search focuses on quantifying the effects of COVID-19 on the macroeconomy and various industry sectors within six economies: the United States, China, the EU, the United Kingdom, Japan, and South Korea.ResultsThe COVID-19 pandemic shock had the most significant impact on China and the EU, followed by notable effects observed in the United States and the United Kingdom. In contrast, South Korea and Japan experienced relatively minimal effects. The reduction in output caused by the pandemic has affected major economies in multiple sectors, including real industries such as forestry and fisheries, and the services such as hotels and restaurants.ConclusionThe overall negative macroeconomic impact of the epidemic on major economies has been significant. Strategic interventions encompassing initiatives like augmenting capital supply, diminishing corporate taxes and fees, offering individual subsidies, and nurturing international cooperation held the potential to mitigate the detrimental economic consequences and enhance the global-economic amid the pan-demic. Consequently, this study contributes to the advancement of global anti-epidemic policies targeting economic recovery. Moreover, using the CGE-COVID-19 model has enriched the exploration of general equilibrium models in PHEIC events.

As of June 9, 2020, the coronavirus outbreak posed a level ***** threat to businesses, meaning that severe and widespread economic impacts were likely. The composite index, which has level *** as its highest warning, was raised to level *** on March 12 and to level ***** on April 13.

Strong plans needed in response to coronavirus Countries are taking small steps on the road to economic recovery by gradually lifting lockdown measures. Manufacturing firms were among the first to return to work, and governments are now permitting shops, bars, and restaurants to reopen. However, there is no guarantee that consumers will return to their normal habits. In order to reduce the risks, businesses are being encouraged to activate contingency plans that include separating all essential operations from non-essential and focusing on high-priority areas and clients.

A focus on the U.S. economy COVID-19 has left the United States facing an economic crisis, and the country’s GDP fell by *** percent in the first quarter of 2020. Record numbers of Americans have lost their jobs during the pandemic, and the unemployment rate jumped to **** percent in April 2020. The Dow Jones, which monitors the stock prices of the ** largest companies in the United States, has rallied since the U.S. economy restarted but continues to feel the effects of a destructive period that wiped out years of gains in a matter of weeks.

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.

Across the EU, about half of respondents (51%) report being aware of a Recovery Plan for their country to support economic recovery from the COVID-19 pandemic. One third of respondents (33%) have seen, heard or read something about NextGenerationEU. Almost three-quarters of respondents (74%) think that the principle of solidarity is a good approach for the EU and seven in ten reply that this is a good approach for their country.

Processed data

Processed data files for the Eurobarometer surveys are published in .xlsx format.

• Volume A "Countries/EU" The file contains frequencies and means or other synthetic indicators including elementary bivariate statistics describing distribution patterns of (weighted) replies for each country or territory and for (weighted) EU results.
• Volume AP "Trends" The file compares to previous poll in (weighted) frequencies and means (or other synthetic indicators including elementary bivariate statistics describing distribution patterns of replies); shifts for each country or territory foreseen in Volume A and for (weighted) results.
• Volume AA "Groups of countries" The file contains (labelled) frequencies and means or other synthetic indicators including elementary bivariate statistics describing distribution patterns of (weighted) replies for groups of countries specified by the managing unit on the part of the EC.
• Volume AAP "Trends of groups of countries" The file contains shifts compared to the previous poll in (weighted) frequencies and means (or other synthetic indicators including elementary bivariate statistics describing distribution patterns of replies); shifts for each groups of countries foreseen in Volume AA and for (weighted) results.
• Volume B "EU/socio-demographics" The file contains (labelled) frequencies and means or other synthetic indicators including elementary bivariate statistics describing distribution patterns of replies for the EU as a whole (weighted) and cross-tabulated by some 20 sociodemographic, socio-political or other variables, depending on the request from the managing unit on the part of the EC or the managing department of the other contracting authorities.
• Volume BP "Trends of EU/socio-demographics" The file contains shifts compared to the previous poll in (weighted) frequencies and means (or other synthetic indicators including elementary bivariate statistics describing distribution patterns of replies); shifts for each country or territory foreseen in Volume B above)and for (weighted) results.
• Volume C "Country/socio-demographics" The file contains (labelled) weighted frequencies and means or other synthetic indicators including elementary bivariate statistics describing distribution patterns of replies for each country or territory surveyed separately and cross-tabulated by some 20 socio-demographic, socio-political or other variables (including a regional breakdown).

For SPSS files and questionnaires, please contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer

The United States has had the highest economic growth in the G7 since the start of the COVID-19 pandemic, with its economy *** percent larger in the first quarter of 2023, when compared with the fourth quarter of 2019. By contrast, the United Kingdom and Germany have both seen their economies shrink by *** percent in the same time period.

The global health crisis initiated by the COVID-19 pandemic triggered unparalleled economic upheavals. In this comprehensive study of 16 countries categorized by their infection rates, we scrutinize the impact of a range of variables on stock market indices and calculate four critical ratios derived from those variables. Our regression analyses reveal striking differences in how the variables influenced stock indices in countries with low and high infection rates. Notably, in countries with low infection rates, all variables exhibited significant effects on stock returns. An increase in infection numbers and fatalities correlated with greater stock market declines, underscoring the market’s sensitivity to the health and economic risks posed by the pandemic. Recovery and testing rates also displayed positive associations with stock returns, reflecting investor optimism concerning potential recovery scenarios. Conversely, nations grappling with high infection rates experienced notably weaker effects from these variables. Although fatalities had a negative impact on stock indices, other factors, including recoveries, infections, and testing rates, did not result in significant effects. This suggests the likelihood that markets in high-infection countries had likely factored pandemic conditions into their pricing, thereby reducing the immediate impact of these metrics on stock returns. Our findings underscore the intricacies of the COVID-19 pandemic’s impact on stock markets and highlight the importance of tailored strategies and policies for distinct country categories. This study offers valuable insights for policymakers and investors navigating financial markets during global health crises and preparing for future epidemics.

IntroductionThe COVID-19 pandemic emerged in a context that lacked adequate prevention, preparedness, and response (PPR) activities, and global, regional, and national leadership. South American countries were among world’s hardest hit by the pandemic, accounting for 10.1% of total cases and 20.1% of global deaths.MethodsThis study explores how pandemic PPR were affected by political, socioeconomic, and health system contexts as well as how PPR may have shaped pandemic outcomes in Argentina, Brazil, Colombia, and Peru. We then identify lessons learned and advance an agenda for improving PPR capacity at regional and national levels. We do this through a mixed-methods sequential explanatory study in four South American countries based on structured interviews and focus groups with elite policy makers.ResultsThe results of our study demonstrate that structural and contextual barriers limited PPR activities at political, social, and economic levels in each country, as well as through the structure of the health care system. Respondents believe that top-level government officials had insufficient political will for prioritizing pandemic PPR and post-COVID-19 recovery programs within their countries’ health agendas.DiscussionWe recommend a regional COVID-19 task force, post-pandemic recovery, social and economic protection for vulnerable groups, improved primary health care and surveillance systems, risk communication strategies, and community engagement to place pandemic PPR on Argentina, Brazil, Colombia, and Peru and other South American countries’ national public health agendas.

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.

Presentation of the plan France Relance Through the Recovery Plan, the Government mobilised to address and protect the country from the economic and social consequences of the COVID-19 crisis. In accordance with a commitment of the President of the Republic, the authorities are asked to publish data on the measures of the recovery plan on data.gouv.fr. The publication of these data should make it possible to enhance the commitment of the State to ensure the recovery of France, to facilitate the assessment of the implementation of the measures of the recovery plan, to allow the work of researchers and to contribute to enhancing the transparency of public action, while preserving business secrecy, fiscal secrecy and statistical secrecy in particular. ## Description of data In order to give more visibility to all French people on the implementation of the Recovery Plan, the Ministry of Economy, Finance and Relance publishes a scoreboard to monitor the progress of the main measures under the three strands of “France Relance” (ecology, competitiveness and cohesion). The published scoreboards present the main indicators by the end of December 2020. Number of industrial projects supported — Number of monuments belonging to local authorities or private actors selected for renovation — Number of young people entering the CIE (employment initiative contracts) and PEC (job pathway skills) — Number of MaPrimeRénov files accepted — Number of apprenticeship contracts receiving exceptional assistance — Number of export cheques and VIE cheques (international corporate volunteering) — Number of cathedrals and national monuments selected for renovation — Number of ecological bonuses and conversion bonuses paid — Number of State buildings selected for energy renovation — Number of aids paid for the hiring of young people The indicators are updated monthly and are broken down by region and department.

IntroductionThe long-term impact of COVID-19 on mental health, particularly in relation to socio-economic vulnerabilities, has received little attention. This study reports the prevalence of mental health-related symptoms among previously hospitalized patients after recovery from COVID-19, and its association with socio-economic status (SES).MethodsData collection of this cross-sectional study was conducted during February–April 2021, among previously hospitalized patients with COVID-19 like symptoms, on average six months after their discharge from the hospital. Using DASS-21, a validated scale to document symptoms of depression, anxiety, and stress, information on mental health-related symptoms were recorded from 481 respondents along with sociodemographic and economic information through telephone interviews. Chi-square tests were performed to identify significant group differences. Multinomial logistic regression analyzed the association between the changes in socioeconomic characteristics and mental health-related symptoms. Relative index of inequality (RII), slope index of inequality (SII), and concentration index (CIX) were applied to capture relevant inequalities in relation to mental health-related symptoms.ResultsEleven percent of the respondents reported changes in employment status, nearly half changes in income and expenditure. Forty-five percent reported symptoms of depression, anxiety and/or stress, and 12% reported coexistence of all three symptoms. Women [Adjusted Odds Ratio, AOR: 2.95; 95% Confidence Interval, CI: 1.39–5.68], and those who reported changes in occupation [AOR: 3.04; 95% CI: 1.01–9.08] and expenditure [AOR: 2.46; 95% CI: 1.12–5.37] were more likely to report all three mental health-related symptoms compared to men and those without changes in occupation and expenditure. The older age group was less likely [AOR: 0.96; 95%CI: 0.93–0.99] to report coexistence of all three symptoms compared to their younger counterparts. Negative values of concentration index (CIX) indicate that any one mental health-related symptom was significantly concentrated among those with lower expenditure and poor SES.ConclusionThis study will help in addressing mental health-related challenges after recovery from COVID-19 among the identified vulnerable groups through relevant community-based and clinical response, including counseling services, in Bangladesh and similar LMIC contexts.

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Building on chapter 2 on financial institutions, this chapter looks at the consumers of finance—households and firms—and especially at the insolvency systems countries can use in facilitating an equitable

recovery from the COVID-19 (coronavirus) economic crisis. Those systems—debt enforcement laws and

their institutional framework—are essential to achieving recovery. The reforms highlighted in this chapter, informed by the World Bank’s “Principles for Effective Insolvency and Creditor/Debtor Regimes” and

the “Legislative Guide on Insolvency Law” issued by the United Nations Commission on International

Trade Law (UNCITRAL),1

focus on mechanisms for restructuring or discharging debt.

Effective debt resolution, which these reforms facilitate, can contribute to economic growth and

contain the wider economic impact of business distress. In addition to establishing fairness for debtors

by providing a pathway out of perpetual indebtedness, well-functioning insolvency systems can spur

future innovation and economic growth by freeing up capital for lending to new and productive enterprises. To deliver on this potential, insolvency systems have to find an effective balance between the

need, on the one hand, to address individual instances of overindebtedness and, on the other, to discourage borrowers from engaging in unnecessary risk-taking.

According to data from McKinsey, ** percent of respondents from Italy said that their personal income reduced either slightly or reduced a lot as a result of the COVID-19 pandemic.

The coronavirus (COVID-19) pandemic, has had a significant impact on the global economy. In 2020, global Gross Domestic Product (GDP) decreased by *** percent, while the forecast initially was *** percent GDP growth. As the world's governments are working towards a fast economic recovery, the GDP increased again in 2021 by *** percent. Global GDP increased by over ***** percent in 2022, but it is still not clear to what extent Russia's war in Ukraine will impact the global economy. Global GDP growth is expected to slow somewhat in 2023.

The Government is fully mobilised to address and ** protect the country from the economic and social consequences** of the COVID-19 crisis. A support plan provided an immediate and strong response to cushion the first shock. In order to prepare the French economy for the challenges ahead in the coming years, the “France Relance” plan was presented on 3 September 2020, the result of a broad national consultation set up to draw lessons from the crisis. Three components are identified: ecology, competitiveness and cohesion. In order to give more visibility to all French people on the implementation of the Recovery Plan, the Ministry of Economy, Finance and Recovery publishes a scoreboard to monitor the progress of the main measures of the three strands of “France Relance”. The indicators are updated monthly. The public scoreboard presents the main indicators contained in these data. The dashboard is available at this address.

Abstract

Like the rest of the world, Sudan has been experiencing the unprecedented social and economic impact of the COVID-19 pandemic. From restrictions on movement to school closures and lockdowns, the economic situation worsened, and commodity prices soared across the country. Results from the first six rounds of the High-Frequency Phone survey indicated that household welfare was negatively affected. The situation led to the loss of employment and income, decreased access to essential commodities and services, and food insecurity, particularly among the poor and vulnerable Sudanese. Moreover, the inability to access food and medicine degraded in July/August 2021 despite a slight amelioration in February/April 2021.

After COVID-19 in 2020, Sudan experienced situations that are more likely to compromise the recovery process. Political instability, unrest, and protests occurred before and after the military takeover in October 2021. Meanwhile, Sudan Central Bank devalued the currency, which may increase the already high commodities price. Besides, Sudan encountered historic flooding since the onset of the rainy season between May and June 2022. To monitor and assess the dynamics of the impacts of the country's economic and political situation (high inflation, social unrest, food shortages, asset loss, displacement, etc.) on households' welfare, another round of the Sudan High-Frequency Phone survey took place in June to August 2022.

Similar to the six previous rounds, the survey was conducted using mobile phones and covered all 18 states of Sudan. Round 7 sample is composed of 2816 Households from both urban and rural areas of Sudan. This sample allows us to draw statistical inferences about the Sudanese population at the national and rural/urban levels. The risk of nonresponse was a concern, so efforts were made to minimize this risk, including follow-up with respondents who failed to respond and keep the interviews short (15–20 minutes) to reduce respondent fatigue.

The questions are similar to the previous six rounds of the High-Frequency Phone survey but with added context. Households are asked about the key channels through which individuals and households are expected to be affected by the exchange rate distortions, country political instability, or flooding that occurred in May/June 2022, as well as how they have recovered from the COVID-19 pandemic impacts. Furthermore, questions cover a range of topics/themes including, but not limited to, health conditions, access to health facilities, access to other social services, availability of common food and non-food items (including medicines), nutrition and food security, employment/labor, income, assets, coping strategies, remittances, subjective welfare, climate/weather events, and the safety nets assistance.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Sampling procedure

The sampling methodology adopted for the implementation of this survey is probabilistic. Each of the units in the targeted population of the study must have a nonzero and known probability of selection. The sample was stratified by rural/urban for all 18 states. The distribution of the sub-sample between states and rural/urban is proportional to the size of the individuals owning mobile phones, i.e., not equal allocation. The selection of the individual phones (the households) is random, i.e., with equal probability, using a systematic sample procedure in the list (frame) of phones. This allows for extrapolating the results of the sample to the target population and estimating the precision of the results obtained. However, the implementation of this approach requires the availability of an adequate sampling frame containing all the units of the population without omissions or duplications.

In this survey, the sampling frame is provided by the phone lists. Considerable efforts were made to compile the frame using multiple lists of phone numbers collected during the implementation of various projects/surveys during the last few years at the household level across the country. This reduces the chances of having more than one phone number per household. Moreover, the interviewers double-checked during data collection that only one number was called for each selected surveyed household. Therefore, selecting individual phone numbers is the same as selecting households. It is worth noting that for West Kordofan and Central Darfur, the proportionality of rural/urban cannot be done according to the size of phones since there are no details for rural/urban. So, the size of the rural and urban populations (projection 2020) was used instead.

In Sudan, under the present federal system, the state is considered a semiautonomous entity mandated to take care of the affairs of the citizen, provide governance, and be responsible for planning, policy formulation, and implementation of the annual program. Consequently, the sample needed to cover all 18 states of the country. The sample is conceived to provide reliable estimates for the country (urban and rural) and to give statistically meaningful results at the national level.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

BASELINE (ROUND 1): One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on: - Demographics - Knowledge regarding the spread of COVID-19 - Behavior and social distancing - Access to basic goods and services (medicines, staple food, health, education, financial services) - Employment - Income loss - Food insecurity experience - Welfare - Shocks and Coping strategies - Social safety nets

ROUND 2: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on: - Demographics - Knowledge regarding the spread of COVID-19 - Behavior and social distancing - Access to basic goods and services (medicines, staple food, health, education, financial services, water, transportation, housing, internet, energy) - Employment - Income loss - Food insecurity experience - Welfare - Shocks and Coping strategies - Social safety nets ROUND 3: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on: - Demographics - Behavior and social distancing - Access to basic goods and services (medicines, staple food, health, education, financial services) - Employment - Income loss - Food insecurity experience - Welfare - Shocks and Coping strategies - Social safety nets ROUND 4: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on: - Demographics - Youth module screening - Behavior and social distancing - Access to basic goods and services (medicines, staple food, health, education, transportation, fuel) - Employment - Income loss - Food insecurity experience - Welfare - Shocks and Coping strategies - Social safety nets ROUND 5: One questionnaire, the Household Questionnaire, was administered to all households in the sample. Respondent were asked to think about each child in their household for the education question. The Household Questionnaire provides information on: - Demographics - Mental health of the respondent - Children education.

ROUND 6: One questionnaire, the Household Questionnaire, was administered to all households in the sample. One youth per household is interviewed in the youth section of the questionnaire. The Questionnaire provides information on: - Demographics - Access to basic goods (medicines, staple food) - Youth employment - Youth job search - Youth aspirations and expectations - Youth skills and mental health.

ROUND 7: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on: - Geography - Access to basic goods and services (medicines, staple food, health, education, water, housing, electricity) - Employment - Income loss - Food insecurity experience - Welfare - Experience of Climate/Weather events - Shocks and Coping strategies

Response rate

BASELINE (ROUND 1): A total of 4,032 households were successfully interviewed during the first round of data collection (conducted during June 16–July 5, 2020). Selected households from each state include both rural and urban households, with the representation of each state in the final sample being proportional to the state’s population relative to the overall population. Households who refused to tell their location (mode of living and state) were dropped to minimize bias. The final sample size accounts 4,027 households.

ROUND 2: Interviewers attempted to contact and interview all 4,032 households that were successfully interviewed in the baseline of the Sudan HFS on COVID-19. 2,989 households were successfully interviewed in the second round. However, households who refused to tell their location (mode of living and state) were dropped to minimize bias. The final sample size accounts 2,987 households.

ROUND 3: Interviewers attempted to contact and interview all 4,032 households that were successfully interviewed in the Baseline of the Sudan HFS on COVID-19. 2,990 households were successfully interviewed in the third round. Households who refused to tell their location (mode of living and state) were dropped to minimize bias. The final sample size accounts 2,987 households.

ROUND 4: Interviewers attempted to contact and interview all 4,032 households that were successfully interviewed in the Baseline of the Sudan

This Country Private Sector Diagnostic (CPSD) is a joint International Finance Corporation–World Bank effort to highlight the constraints, as well as the opportunities, facing the private sector in Ecuador. A review is particularly timely because the policy dialogue in the country has shifted, with the government paying greater attention to the needs of the private sector, including by committing to create space for private activity to expand its role in the economy. The decline in oil prices in recent years has ushered in more challenging economic times for the country, underscoring the need for economic diversification, crowding in private investment, and creating a more hospitable business climate. Ultimately, Ecuador’s growth prospects and its ability to create high-quality jobs depend on the extent to which its private sector leads the way in increasing productivity. This report reflects the early impacts of the COVID-19 pandemic, and the current understanding regarding the potential fallout of the crisis on the country and on the private sector. The CPSD’s analysis and recommendations remain valid in the context of the pandemic and of an eventual recovery. A dynamic and resilient private sector is necessary if Ecuador is to break the low-growth trajectory it finds itself in today. The CPSD argues that tackling some of the major obstacles facing the private sector is essential to job creation, firm performance, investment, and productivity. These actions are as critical in times of crisis and especially afterwards to pave the way for a vigorous and sustainable recovery. Similarly, the sectors assessed by the CPSD - mining and perishable agricultural exports - continue to hold promise for the country. And while tourism is one of the sectors hardest hit across the globe by the COVID-19 crisis, crafting a strategy that effectively addresses the obstacles that prevent the tourism sector from attaining its potential is a necessary investment for a strong recovery. This is especially the case for regulations that carry a low fiscal cost and that have the potential to open up the sector over the medium-term.

The Coronavirus State and Local Fiscal Recovery Funds program, as part of the American Rescue Plan Act delivers financial assistance to state, local, and Tribal governments across the country to support their response to and recovery from the COVID-19 public health emergency. The American Rescue Plan Act, or ARPA, was one of the largest recovery responses taken by the federal government and passed by Congress on March 11, 2021. The City of Phoenix received an allocation of $396 million and funds were delivered in two tranches over two years. On June 8, 2021, the Phoenix City Council approved the first tranche strategic plan and on June 7, 2022, Phoenix City Council approved the second tranche strategic plan. This dataset provides the funding types and amounts invested in the community and city operations.

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.