This thesis explores the devastating economic consequences that a hypothetical World War III could have on the global economy. Unlike the previous world wars, this conflict would unfold in a highly globalized, digitally interconnected world—meaning the economic damage would be even more widespread and severe.Drawing from history, the paper analyzes past wars like World War I and II, highlighting how those events caused GDP contractions, hyperinflation, destruction of infrastructure, and long-term debt. It uses these precedents to build realistic scenarios for what could happen if WWIII breaks out today. The study models short-term disruptions like stock market crashes, currency collapse, and trade blockades; medium-term issues like mass unemployment and inflation; and long-term impacts such as technological regression and widespread economic stagnation.The thesis provides regional assessments as well—evaluating how countries like the U.S., China, and nations in Europe and the Global South would fare in different war scenarios, from limited conflicts to full-scale nuclear exchanges. It also discusses secondary effects like energy and food shortages, famine, and the collapse of consumer demand in non-essential sectors.Importantly, the paper doesn’t stop at doom and gloom. It outlines strategic policy responses such as emergency fiscal controls, global debt restructuring, a possible new Bretton Woods system, and a modern-day Marshall Plan to help rebuild economies post-war.In conclusion, the research emphasizes that preventing World War III is not just a matter of global peace, but an absolute economic necessity. Even the strongest economies could collapse, and recovery could take decades—if at all. The thesis serves as both a warning and a call for proactive international diplomacy, economic safeguards, and collective accountability.

This data package includes the underlying data to replicate the charts and calculations presented in Economic multilateralism 80 years after Bretton Woods, PIIE Working Paper 24-9.

If you use the data, please cite as: Obstfeld, Maurice. 2024. Economic multilateralism 80 years after Bretton Woods. PIIE Working Paper 24-9. Washington: Peterson Institute for International Economics.

InvaCost is the most up-to-date, comprehensive, standardized and robust data compilation and description of economic cost estimates associated with invasive species worldwide1. InvaCost has been constructed to provide a contemporary and freely available repository of monetary impacts that can be relevant for both research and evidence-based policy making. The ongoing work made by the InvaCost consortium2,3,4 leads to constantly improving the structure and content of the database (see sections below). The list of actual contributors to this data resource now largely exceeds the list of authors listed in this page. All details regarding the previous versions of InvaCost can be found by switching from one version to another using the “version” button above. IMPORTANT UPDATES: 1. All information, files, outcomes, updates and resources related to the InvaCost project are now available on a new website: http://invacost.fr/2. The names of the following columns have been changed between the previous and the current version: ‘Raw_cost_estimate_local_currency’ is now named ‘Raw_cost_estimate_original_currency’; ‘Min_Raw_cost_estimate_local_currency’ is now named ‘Min_Raw_cost_estimate_original_currency’; ‘Max_Raw_cost_estimate_local_currency’ is now named ‘Max_Raw_cost_estimate_original_currency’; ‘Cost_estimate_per_year_local_currency’ is now named ‘Cost_estimate_per_year_original_currency’3. The Frequently Asked Questions (FAQ) about the database and how to (1) understand it, (2) analyse it and (3) add new data are available at: https://farewe.github.io/invacost_FAQ/. There are over 60 questions (and responses), so there’s probably yours.4. Accordingly with the continuous development and updates of the database, a ‘living figure’ is now available online to display the evolving relative contributions of different taxonomic groups and regions to the overall cost estimates as the database is updated: https://borisleroy.com/invacost/invacost_livingfigure.html5. We have now added a new column called ‘InvaCost_ID’, which is now used to identify each cost entry in the current and future public versions of the database. As this new column only affects the identification of the cost entries and not their categorisation, this is not considered as a change of the structure of the whole database. Therefore, the first level of the version numbering remains ‘4’ (see VERSION NUMBERING section).

CONTENT: This page contains four files: (1) 'InvaCost_database_v4.1' which contains 13,553 cost entries depicted by 66 descriptive columns; (2) ‘Descriptors 4.1’ provides full definition and details about the descriptive columns used in the database; (3) ‘Update_Invacost_4.1’ has details about the all the changes made between previous and current versions of InvaCost; (4) ‘InvaCost_template_4.1’ (downloadable file) provides an easier way of entering data in the spreadsheet, standardizing all the terms used on it as much as possible to avoid mistakes and saving time at post-refining stages (this file should be used by any external contributor to propose new cost data).

METHODOLOGY: All the methodological details and tools used to build and populate this database are available in Diagne et al. 20201 and Angulo et al. 20215. Note that several papers used different approaches to investigate and analyse the database, and they are all available on our website http://invacost.fr/.

VERSION NUMBERING: InvaCost is regularly updated with contributions from both authors and future users in order to improve it both quantitatively (by new cost information) and qualitatively (if errors are identified). Any reader or user can propose to update InvaCost by filling the ‘InvaCost_updates_template’ file with new entries or corrections, and sending it to our email address (updates@invacost.fr). Each updated public version of InvaCost is stored in this figShare repository, with a unique version number. For this purpose, we consider the original version of InvaCost publicly released in September 2020 as ‘InvaCost_1.0’. The further updated versions are named using the subsequent numbering (e.g., ‘InvaCost_2.0’, InvaCost_2.1’) and all information on changes made are provided in a dedicated file called ‘Updates-InvaCost’ (named using the same numbering, e.g., ‘Updates-InvaCost_2.0’, ‘Updates-InvaCost_2.1’). We consider changing the first level of this numbering (e.g. ‘InvaCost_3.x’ ‘InvaCost_4.x’) only when the structure of the database changes. Every user wanting to have the most up-to-date version of the database should refer to the latest released version.

RECOMMENDATIONS: Every user should read the ‘Usage notes’ section of Diagne et al. 20201 before considering the database for analysis purposes or specific interpretation. InvaCost compiles cost data published in the literature, but does not aim to provide a ready-to-use dataset for specific analyses. While the cost data are described in a homogenized way in InvaCost, the intrinsic disparity, complexity, and heterogeneity of the cost data require specific data processing depending on the user objectives (see our FAQ). However, we provide necessary information and caveats about recorded costs, and we have now an open-source software designed to query and analyse this database6.

CAUTION: InvaCost is currently being analysed by a network of international collaborators in the frame of the InvaCost project2,3,4 (see https://invacost.fr/en/outcomes/). Interested users may contact the InvaCost team if they wish to learn more about or contribute to these current efforts. Users are in no way prevented from performing their own independent analyses and collaboration with this network is not required. Nonetheless, users and contributors are encouraged to contact the InvaCost team before using the database, as the information contained may not be directly implementable for specific analyses.

RELATED LINKS AND PUBLICATIONS:

1 Diagne, C., Leroy, B., Gozlan, R.E. et al. InvaCost, a public database of the economic costs of biological invasions worldwide. Sci Data 7, 277 (2020). https://doi.org/10.1038/s41597-020-00586-z

2 Diagne C, Catford JA, Essl F, Nuñez MA, Courchamp F (2020) What are the economic costs of biological invasions? A complex topic requiring international and interdisciplinary expertise. NeoBiota 63: 25–37. https://doi.org/10.3897/neobiota.63.55260

3 Researchgate page: https://www.researchgate.net/project/InvaCost-assessing-the-economic-costs-of-biological-invasions

4 InvaCost workshop: https://www.biodiversitydynamics.fr/invacost-workshop/

5 Angulo E, Diagne C, Ballesteros-Mejia L. et al. (2021) Non-English languages enrich scientific knowledge: the example of economic costs of biological invasions. Science of the Total Environment 775:144441. https://doi.org/10.1016/j.scitotenv.2020.144441

6Leroy B, Kramer A M, Vaissière A-C, Courchamp F and Diagne C (2020) Analysing global economic costs of invasive alien species with the invacost R package. BioRXiv. doi: https://doi.org/10.1101/2020.12.10.419432

United States US: Scientific and Technical Journal Articles data was reported at 408,985.300 Unit in 2016. This records a decrease from the previous number of 429,139.000 Unit for 2015. United States US: Scientific and Technical Journal Articles data is updated yearly, averaging 403,928.200 Unit from Dec 2003 (Median) to 2016, with 14 observations. The data reached an all-time high of 440,229.700 Unit in 2014 and a record low of 321,765.900 Unit in 2003. United States US: Scientific and Technical Journal Articles data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Technology. Scientific and technical journal articles refer to the number of scientific and engineering articles published in the following fields: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences.; ; National Science Foundation, Science and Engineering Indicators.; Gap-filled total;

The Gross Domestic Product (GDP) in the United States was worth 29184.89 billion US dollars in 2024, according to official data from the World Bank. The GDP value of the United States represents 27.49 percent of the world economy. This dataset provides - United States GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

presented in An analysis of pandemic-era inflation in 11 economies, PIIE Working Paper 24-11.

If you use the data, please cite as: Bernanke, Ben, and Olivier Blanchard. 2024. An analysis of pandemic-era inflation in 11 economies. PIIE Working Paper 24-11. Washington: Peterson Institute for International Economics.

In 2024, the total contribution of travel and tourism to the global gross domestic product (GDP) amounted to **** trillion U.S. dollars. This figure, which includes the direct, indirect, and induced impact of the global travel and tourism market, represented an increase in total contribution to GDP of *** percent over 2019. As forecast, the total contribution of the travel and tourism sector to the global GDP was expected to reach **** trillion U.S. dollars in 2025. Which countries record the highest travel and tourism contribution to GDP? GDP is the total value of all goods and services produced in a country in a year. It is considered an important indicator of a country's economic strength, and a positive change in GDP is a sign of economic growth. Both before and after the impact of COVID-19, the United States and China were by far the leading travel markets based on the total contribution of travel and tourism to GDP, followed by Germany, Japan, and the United Kingdom. What are the most visited countries in the world? In 2023, France was the country with the highest number of international tourist arrivals worldwide, welcoming 100 million international visitors. While the United States reported the third-highest number of inbound tourist arrivals that year, it was the destination with the highest international tourism receipts worldwide, ranking ahead of Spain and the United Kingdom.

files to replicate analyses reported in Ezrow and Hellwig, "Responding to Voters or Responding to Markets." Article abstract: Conventional wisdom has it that political parties have incentives to respond to public opinion. It is also conventional wisdom that in open economies, policymakers must also “respond” to markets. Research on representation has provided ample evidence in support of the first claim. Research on the political economy of globalization has not, however, provided evidence for the second. This article examines the effects of globalization on how parties respond to voters. We argue that while elections motivate parties to respond to public sentiment, economic interdependence distracts political elites from their electorates and toward market actors, reducing party responsiveness to the mean voter. Evidence from a pair of distinct data sources spanning elections in twenty advanced capitalist democracies from the 1970s to 2010 shows that while parties have incentives to respond to left-right shifts in the mean voter position, they only do so when the national economy is sufficiently sheltered from the world economy. These findings have implications for party strategies, for representation, and for the broader effects of market integration.

Scientific and technical journal articles in Lebanon was reported at 2091 in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Lebanon - Scientific and technical journal articles - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Georgia GE: Scientific and Technical Journal Articles data was reported at 579.400 Unit in 2016. This records an increase from the previous number of 492.000 Unit for 2015. Georgia GE: Scientific and Technical Journal Articles data is updated yearly, averaging 391.800 Unit from Dec 2003 (Median) to 2016, with 14 observations. The data reached an all-time high of 579.400 Unit in 2016 and a record low of 216.600 Unit in 2003. Georgia GE: Scientific and Technical Journal Articles data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank: Technology. Scientific and technical journal articles refer to the number of scientific and engineering articles published in the following fields: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences.; ; National Science Foundation, Science and Engineering Indicators.; Gap-filled total;

Saudi Arabia SA: Scientific and Technical Journal Articles data was reported at 9,231.900 Unit in 2016. This records an increase from the previous number of 8,885.000 Unit for 2015. Saudi Arabia SA: Scientific and Technical Journal Articles data is updated yearly, averaging 3,228.850 Unit from Dec 2003 (Median) to 2016, with 14 observations. The data reached an all-time high of 9,231.900 Unit in 2016 and a record low of 1,710.700 Unit in 2004. Saudi Arabia SA: Scientific and Technical Journal Articles data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Saudi Arabia – Table SA.World Bank: Technology. Scientific and technical journal articles refer to the number of scientific and engineering articles published in the following fields: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences.; ; National Science Foundation, Science and Engineering Indicators.; Gap-filled total;

This is the data used in the research "Complexity, Inequality, and Internet". Inequality is quantified using the Gini coefficient after taxes and transfers, sourced from the Standardized World Income Inequality Database, incorporating data from the OECD, World Bank, and ECLAC (Solt, 2020). Explanatory variables include the Economic Complexity Index (ECI) from the Atlas of Economic Complexity (The Growth Lab at Harvard University, 2019), normalized within a range of -3 to +3; real GDP per capita in 2017 US dollars from the Penn World Table (Feenstra, et al., 2015); and internet access, measured as the percentage of the population using this service (The World Bank, 2023). The dataset comprises 126 countries with data spanning from 1995 to 2020.

This data is presented in CSV and XLSX formats for further review.

This data package includes the underlying data files to replicate the calculations, charts, and tables presented in The International Financial System after COVID-19, PIIE Working Paper 22-2.

If you use the data, please cite as: Obstfeld, Maurice (2022). The International Financial System after COVID-19, PIIE Working Paper 22-2. Peterson Institute for International Economics.

Analysis of ‘Maddison Project Dataset 2020 Population by Region’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mathurinache/maddison-project-dataset-2020-population-by-region on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

The Maddison Project Database provides information on comparative economic growth and income levels over the very long run. The 2020 version of this database covers 169 countries and the period up to 2018. For questions not covered in the documentation, please contact maddison@rug.nl.

Content

We now offer a new 2020 update of the Maddison Project database, which uses a different methodology compared to the 2018 update. The approach of the 2018 update is identical to that of Penn World Tables, and consistent with recent economic and statistical research in this field. However, applying this approach systematically results in historical outcomes that are not consistent with current insights by economic historians, as explained in Bolt and Van Zanden (2020).

The 2020 update has to some extent gone back to the original Maddison approach to remedy for this (see documentation). Both the 2018 and the 2020 datasets incorporate the available recent work by economic historians on long term economic growth, the 2020 is most complete in this respect.

Acknowledgements

Attribution requirement -

All original papers must be cited when:

the data is shown in any graphical form subsets of the full dataset that include less than a dozen (12) countries are used for statistical analysis or any other purposes

A list of original papers can be found in the source sheet of the database. When neither a) or b) apply, then the MPD as a whole should be cited.

Maddison Project Database, version 2020. Bolt, Jutta and Jan Luiten van Zanden (2020), “Maddison style estimates of the evolution of the world economy. A new 2020 update ”.

Inspiration

You can find some inspiration here : https://ourworldindata.org/global-economic-inequality-introduction

--- Original source retains full ownership of the source dataset ---

Main explanatory variables.

The Open Economics project provides open content, data and code related to Economics. This site itself provides interfaces to some (though not all) of the Open Economics datasets and models.

Current datasets (all available as csv):

• Bank of England Interest Rate
• CIA World Factbook Data (Various Years)
• Copyright Registrations in the United States 1790-2000
• Country and Regional Analyses (CRA) - UK Government Finances
• Daily Wages of Thatchers in the Middle Ages
• Distribution of Estimated Patent Values in Various European Countries
• Gold Prices 1950-2008 (Monthly)
• Government revenue (for 17 Countries in the period 1880-1913)
• Gross value added at basic prices: Output Index: CVM SA
• Hard Drive Capacities and Costs (1955-2000)
• Income Distribution in Hamburg for Occupied Persons in 1890
• Millenium Development Goals Dataset
• Monthly stock price, dividends, and earnings data and the consumer price index from January 1871
• Number of Published Articles in Economics (1970-2006)
• Patents Enrolled in England 1660-1799
• Penn World Table of PPP and National Income Accounts
• Population, Landscape and Climate Estimates
• Recorded Music Sales 1969-2004 Worldwide (in millions)
• UK Government Finances - Public Expenditure Statistical Analyses
• UK House Price Data
• UK Population Estimates 1520 to 1851
• UK Price Index 1850-2002 (Annual)
• US Population Estimates (mid year) 1790 to 2005
• US Wheat Production and Prices
• USA Employment status of the civilian noninstitutional population, 1940 to date
• W3Schools Browser Statistics (Monthly)
• Wheat, barley, oat, mutton and wool prices, and agricultural wages, 1500-1849 (10 year averages 1700-49 = 100)
• World Population Historical

We are in the process of merging this data catalog in CKAN (so each dataset will become a package on CKAN).

Openness

All Open Economics datasets are openly licensed though not always possible to gauge status of underlying data used. Individual datasets have more information about their license status.

Globalisation critics are concerned that increased trade openness and foreign direct investment exacerbate existing economic disadvantages of women and foster conditions for forced labour. Defenders of globalisation argue instead that as countries become more open and competition intensifies, discrimination against any group, including women, becomes more difficult to sustain and is therefore likely to recede. The same is argued with respect to forced labour. This article puts these competing claims to an empirical test. We find that countries that are more open to trade provide better economic rights to women and have a lower incidence of forced labour. This effect holds in a global sample as well as in a developing country sub-sample and holds also when potential feedback effects are controlled via instrumental variable regression. The extent of an economy's ‘penetration’ by foreign direct investment by and large has no statistically significant impact. Globalisation might weaken the general bargaining position of labour such that outcome-related labour standards might suffer. However, being more open toward trade is likely to promote rather than hinder the realisation of two labour rights considered as core or fundamental by the International Labour Organisation, namely the elimination of economic discrimination and of forced labour.

This data product provides agricultural output, input and total factor productivity (TFP) growth rates, but not levels, across the countries and regions of the world in a consistent, comparable way, for 1961-2010.

A listing of Science and Technology Agreements (STAs) signed by China with other countries of the world, gathered 2021.

Vanuatu VU: Scientific and Technical Journal Articles data was reported at 13.500 Unit in 2016. This records an increase from the previous number of 10.900 Unit for 2015. Vanuatu VU: Scientific and Technical Journal Articles data is updated yearly, averaging 6.650 Unit from Dec 2003 (Median) to 2016, with 14 observations. The data reached an all-time high of 13.500 Unit in 2016 and a record low of 2.600 Unit in 2007. Vanuatu VU: Scientific and Technical Journal Articles data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vanuatu – Table VU.World Bank: Technology. Scientific and technical journal articles refer to the number of scientific and engineering articles published in the following fields: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences.; ; National Science Foundation, Science and Engineering Indicators.; Gap-filled total;