In September 2024, the global PMI amounted to 47.5 for new export orders and 48.8 for manufacturing. The manufacturing PMI was at its lowest point in August 2020. It decreased over the last months of 2022 after the effects of the Russia-Ukraine war and rising inflation hit the world economy, and remained around 50 since.

The COVID-19 pandemic had severe impacts on almost every aspect of life, from health via economy to education. School closures around the world caused disruptions in learning development of children and youth. Estimates from 2022 show that globally, the annual gross domestic product (GDP) loss could amount to nearly 1,600 billion U.S. dollars annually if no counter measures are taken. The economic damage was predicted to be highest in East Asia and the Pacific, and the lowest in Sub-Saharan Africa.

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.

The coronavirus (COVID-19) pandemic, has had a significant impact on the global economy. In 2020, global Gross Domestic Product (GDP) decreased by 3.4 percent, while the forecast initially was 2.9 percent GDP growth. As the world's governments are working towards a fast economic recovery, the GDP increased again in 2021 by 5.8 percent. Global GDP increased by over three 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.

Opinions about coronavirus' impact on the digital economy are mixed: 33 percent of surveyed international digital decision makers believed that the digital economy will benefit after the pandemic, whereas 24 percent thought that the digital economy will have to endure long-term revenue loss like the overall economy.

In a survey conducted in 2020, regarding the impact which the outbreak of the coronavirus had, 83 percent of respondents in Malaysia stated that the outbreak of COVID-19 had a major impact on the international economy. In comparison, 44 percent of respondents in Hong Kong thought the outbreak of the coronavirus had a major impact on the international economy in 2020.

Prior to the outbreak of the coronavirus (COVID-19), GlobalData had predicted that there would be an acceleration in the pace of growth in the global construction industry, to 3.1% from 2.6% in 2019. However, given the severe disruption in China and other leading economies worldwide following the outbreak, the forecast for growth in 2020 has now been revised down to 0.5%. The current forecast assumes that the outbreak is contained across all major markets by the end of the second quarter, following which, conditions would allow for a return to normalcy in terms of economic activity and freedom of movement in the second half of the year. However, there will be a lingering and potentially heavy impact on private investment owing to the financial toll that inflicted upon businesses and investors across a wide range of sectors. Read More

United States SBP: TW: COVID-19 Impact: Large Negative Effect data was reported at 34.100 % in 04 Oct 2020. This records an increase from the previous number of 33.500 % for 27 Sep 2020. United States SBP: TW: COVID-19 Impact: Large Negative Effect data is updated weekly, averaging 40.300 % from Apr 2020 (Median) to 04 Oct 2020, with 18 observations. The data reached an all-time high of 52.500 % in 26 Apr 2020 and a record low of 33.500 % in 27 Sep 2020. United States SBP: TW: COVID-19 Impact: Large Negative Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S036: Small Business Pulse Survey: by Sector: Weekly, Beg Sunday (Discontinued).

United States SBP: COVID-19 Impact: Large Positive Effect data was reported at 1.700 % in 04 Oct 2020. This records an increase from the previous number of 1.600 % for 27 Sep 2020. United States SBP: COVID-19 Impact: Large Positive Effect data is updated weekly, averaging 1.350 % from Apr 2020 (Median) to 04 Oct 2020, with 18 observations. The data reached an all-time high of 1.700 % in 04 Oct 2020 and a record low of 0.800 % in 10 May 2020. United States SBP: COVID-19 Impact: Large Positive Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S034: Small Business Pulse Survey: Weekly, Beg Sunday (Discontinued).

As of November 2021, the U.S. goverment dedicated 26.46 percent of the GDP to soften the effects of the coronavirus pandemic. This translates to stimulus packages worth 5.54 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 6.7 percent. The global unemployment rate rocketed to 6.47 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 53.69 percent (308 trillion Yen or 2.71 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.

United States SBP: RE: COVID-19 Impact: Moderate Negative Effect data was reported at 41.300 % in 04 Oct 2020. This records a decrease from the previous number of 45.100 % for 27 Sep 2020. United States SBP: RE: COVID-19 Impact: Moderate Negative Effect data is updated weekly, averaging 44.500 % from Apr 2020 (Median) to 04 Oct 2020, with 18 observations. The data reached an all-time high of 51.800 % in 24 May 2020 and a record low of 41.300 % in 04 Oct 2020. United States SBP: RE: COVID-19 Impact: Moderate Negative Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S035: Small Business Pulse Survey: by Sector: Weekly, Beg Sunday (Discontinued).

This data package includes the underlying data to replicate the charts presented in Lessons from China's fiscal policy during the COVID-19 pandemic, PIIE Working Paper 24-7.

If you use the data, please cite as: Huang, Tianlei. 2024. Lessons from China's fiscal policy during the COVID-19 pandemic. PIIE Working Paper 24-7. Washington: Peterson Institute for International Economics.

The SPIN covid19 RMRIO dataset is a time series of MRIO tables covering years from 2016-2026 on a yearly basis. The dataset covers 163 sectors in 155 countries.

This repository includes data for years from 2016 to 2019 (hist scenario) and the corresponding labels.

Data for years 2020 to 2026 are stored in the corresponding repositories:

• covid: 10.5281/zenodo.5713825
• counterfactual: 10.5281/zenodo.5713839

Tables are generated using the SPIN method, based on the RMRIO tables for the year 2015, GDP, imports and exports data from the International Financial Statistics (IFS) and the World Economic Outlooks (WEO) of October 2019 and April 2021.

From 2020 to 2026, the dataset includes two diverging scenarios. The covid scenario is in line with April 2021 WEO's data and includes the macroeconomic effects of Covid 19. The counterfactual scenario is in line with October 2019 WEO's data and simulates the global economy without Covid 19. Tables from 2016 to 2019 are labelled as hist.

The Projections folder includes the generated tables for years from 2016 to 2019 (hist scenario) and the corresponding labels.

The Sources folder contains the data records from the IFS and WEO databases. The Method data contains the data files used to generate the tables with the SPIN method and the following Python scripts:

• SPIN_covid19_MRIO_files_preparation.py generates the data files from the source data.
• SPIN_covid19_RMRIO runs.py is the command to run the SPIN method and generate the dataset.
• figures.py is a script to produce figures reflecting the consistency of the projected tables and the evolution of macroeconomic figures in the 2016-2026 period for a selection of countries.

All tables are labelled in 2015 US$ and valued in basic prices.

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.

BackgroundThe spread of COVID-19 has been characterized by unprecedented global lock-downs. Although, the extent of containment policies cannot be explained only through epidemic data. Previous studies already focused on the relationship between the economy and healthcare, focusing on the impact of diseases in countries with a precarious economic situation. However, the pandemic caused by SARS-CoV-2 drew most countries of the world into a precarious economic situation mostly caused by the global and local lock-downs policies.MethodsA discriminant analysis performed via partial least squares procedure was applied to evaluate the impact of economic and healthcare variables on the containment measures adopted by 39 countries. To collect the input variables (macroeconomic, healthcare, and medical services), we relied on official databases of international organizations, such as The World Bank and WHO.ResultsThe stringency lock-down policies could not only be influenced by the epidemical data, but also by previous features of the selected countries, such as economic and healthcare conditions.ConclusionsIndeed, economic and healthcare variables also contributed to shaping the implemented lock-down policies.

United States COVID-19 Impact: Upcoming Travel Plans: From Fly to Drive data was reported at 33.000 % in 23 Sep 2020. This stayed constant from the previous number of 33.000 % for 09 Sep 2020. United States COVID-19 Impact: Upcoming Travel Plans: From Fly to Drive data is updated weekly, averaging 26.000 % from Mar 2020 (Median) to 23 Sep 2020, with 21 observations. The data reached an all-time high of 33.000 % in 23 Sep 2020 and a record low of 17.000 % in 25 Mar 2020. United States COVID-19 Impact: Upcoming Travel Plans: From Fly to Drive data remains active status in CEIC and is reported by Longwoods International. The data is categorized under Global Database’s United States – Table US.Q008: Travel Sentiment.

The global pandemic caused by coronavirus COVID-19 could have a prolonged impact on China's economy. Manufacturing sector was estimated to drop by 3.61 percentage points form the baseline of no global coronavirus crisis. The overall impact was projected to be a decline by 3.54 percentage point.

United States SB: COVID-19 Impact: Little or Number Effect data was reported at 28.500 % in 11 Apr 2022. This records a decrease from the previous number of 34.500 % for 04 Apr 2022. United States SB: COVID-19 Impact: Little or Number Effect data is updated weekly, averaging 30.350 % from Nov 2021 (Median) to 11 Apr 2022, with 18 observations. The data reached an all-time high of 34.500 % in 04 Apr 2022 and a record low of 24.300 % in 15 Nov 2021. United States SB: COVID-19 Impact: Little or Number Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S042: Small Business Pulse Survey: by State: West Region: Weekly, Beg Monday (Discontinued).

The year-end closing values of the Dow Jones Transportation Index increased more than twofold since 2012. The value of Dow Jones Transportation Index amounted to 15,895.75 points in 2024. Even with the economic effects of the global coronavirus (COVID-19) pandemic, 2021 had the highest point of the index in the past two decades.

In 2022, global container throughput reached approximately 866 million twenty-foot equivalent units (TEUs). This represented a slight increase of some four million TEUs compared with the previous year.

Container shipping in the context of global seaborne trade The global economy is becoming more and more interconnected every year, driving the staggering demand for transportation of goods across regions and value chains. Since its development in the mid-20th century, container shipping enabled a standardized method of freight transportation that made it safe and efficient to transport goods overseas. To facilitate this process, industrialized nations developed container ports across export-oriented regions. In 2021, the biggest container port worldwide based on throughput was Shanghai. In the same year, most of the largest container ports globally were located around Asia.

Impact of COVID-19 on global container shipping The coronavirus (COVID-19) outbreak inflicted a deep shock on the global economy. As many countries imposed lock-downs, industrial production slowed down, causing major cancellations in supply chain routes and affecting seaborne logistics as well. Port congestions have become commonplace and container ships have been arriving in their destinations with significant delays. As a result, in February 2022, some 11.6 percent of the global container ship capacity was not utilized.