The Gross Domestic Product (GDP) In the Euro Area was worth 16406.13 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Euro Area represents 14.74 percent of the world economy. This dataset provides the latest reported value for - Euro Area GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Gross Domestic Product per capita In the Euro Area was last recorded at 38145.12 US dollars in 2024. The GDP per Capita In the Euro Area is equivalent to 302 percent of the world's average. This dataset provides the latest reported value for - Euro Area GDP per capita - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The dataset contains GDP growth data for 15+ European Countries, spanning from 1960 to 2023. The indicator name is GDP (current US$), and the corresponding indicator code is NY.GDP.MKTP.CD.

This dataset is made possible with Collaboration of @Batros Jamali

The Gross Domestic Product per capita in European Union was last recorded at 54290.99 US dollars in 2024, when adjusted by purchasing power parity (PPP). The GDP per Capita, in European Union, when adjusted by Purchasing Power Parity is equivalent to 306 percent of the world's average. This dataset provides the latest reported value for - European Union GDP Per Capita Ppp - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The dataset used in this paper is a combination of monthly macroeconomic and weekly financial data.

TThe ERS International Macroeconomic Data Set provides historical and projected data for 181 countries that account for more than 99 percent of the world economy. These data and projections are assembled explicitly to serve as underlying assumptions for the annual USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term, 10-year scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks.

Explore the International Macroeconomic Data Set 2015 for annual growth rates, consumer price indices, real GDP per capita, exchange rates, and more. Get detailed projections and forecasts for countries worldwide.

Annual growth rates, Consumer price indices (CPI), Real GDP per capita, Real exchange rates, Population, GDP deflator, Real gross domestic product (GDP), Real GDP shares, GDP, projections, Forecast, Real Estate, Per capita, Deflator, share, Exchange Rates, CPI

Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe, WORLD Follow data.kapsarc.org for timely data to advance energy economics research. Notes:

Developed countries/1 Australia, New Zealand, Japan, Other Western Europe, European Union 27, North America

Developed countries less USA/2 Australia, New Zealand, Japan, Other Western Europe, European Union 27, Canada

Developing countries/3 Africa, Middle East, Other Oceania, Asia less Japan, Latin America;

Low-income developing countries/4 Haiti, Afghanistan, Nepal, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda, Zimbabwe;

Emerging markets/5 Mexico, Brazil, Chile, Czech Republic, Hungary, Poland, Slovakia, Russia, China, India, Korea, Taiwan, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Singapore

BRIICs/5 Brazil, Russia, India, Indonesia, China; Former Centrally Planned Economies

Former centrally planned economies/7 Cyprus, Malta, Recently acceded countries, Other Central Europe, Former Soviet Union

USMCA/8 Canada, Mexico, United States

Europe and Central Asia/9 Europe, Former Soviet Union

Middle East and North Africa/10 Middle East and North Africa

Other Southeast Asia outlook/11 Malaysia, Philippines, Thailand, Vietnam

Other South America outlook/12 Chile, Colombia, Peru, Bolivia, Paraguay, Uruguay

Indicator Source

Real gross domestic product (GDP) World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service all converted to a 2015 base year.

Real GDP per capita U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table and Population table.

GDP deflator World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Real GDP shares U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table.

Real exchange rates U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, CPI table, and Nominal XR and Trade Weights tables developed by the Economic Research Service.

Consumer price indices (CPI) International Financial Statistics International Monetary Fund, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Population Department of Commerce, Bureau of the Census, U.S. Department of Agriculture, Economic Research Service, International Data Base.

U.S. Public Debt vs. GDP

Trends and Comparisons

By Charlie Hutcheson [source]

About this dataset

This dataset contains quarterly data on the US Gross Domestic Product (GDP) and Total Public Debt from 1947 through 2020. It provides a comprehensive view into the development of debt versus GDP over the years, offering insights into how our economy has grown and changed since The Great Depression. Explore this valuable information to answer questions such as: How do debt and GDP relate to one another? Has US government spending been outpacing wealth throughout history? From what sources does our national debt originate? This dataset can be utilized by economists, governments, researchers, investors, financial institutions, journalists — anyone looking to gain a better understanding of where our economy stands today compared to past decades

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How to use the dataset

This dataset, U.S. GDP vs Debt Over Time, contains quarterly data on the Gross Domestic Product (GDP) and Total Public Debt of the United States between 1947 to 2020. This can be useful for conducting research into how the total public debt relates to economic growth in the US.

The dataset includes 4 columns: Quarter , Gross Domestic Product ($mil), Total Public Debt ($mil). The Quarter column consists of strings that represent each quarter from 1947-2020 with a corresponding number (e.g., “Q1-1947”). The Gross Domestic Product ($mil) and Total Public Debt ($mil) columns consist of numbers that indicate the respective amounts in millions for each quarter during this same time period.

By analyzing this dataset you can explore various trends over different periods as it relates to public debt versus economic growth in America and make informed decisions about how certain policies may affect future outcomes. Additionally, you could also compare these two values with other variables such as unemployment rate or inflation rate to gain deeper insights into America’s economy over time

Research Ideas

• Comparing the quarterly growth in GDP with public debt to show the correlation between economic growth and government spending.
• Creating a bar or line visualization that compares the US’s total public debt to comparable economic powers like China, Japan, and Europe over time.
• Examining how changes in government deficit have contributed towards an increase in public debt by analyzing which quarters saw significant leaps of growth from one year to the next

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: US GDP vs Debt.csv | Column name | Description | |:----------------------------------|:-------------------------------------------------------------------------------------------| | Quarter | The quarter of the year in which the data was collected. (String) | | Gross Domestic Product ($mil) | The total value of all goods and services produced by the US in a given quarter. (Integer) | | Total Public Debt ($mil) | The total amount owed by the federal government. (Integer) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Charlie Hutcheson.

Context

The European Union is a unique economic and political union between twenty-eight countries that together cover much of the continent. It was created in the aftermath of the Second World War to foster economic cooperation and thus avoid conflict. The result was the European Economic Community (EEC), established in 1958, with Belgium, Germany, France, Italy, Luxembourg and the Netherlands as its members. What began as an economic union has evolved into an organization spanning policy areas, from climate, environment and health to external relations and security, justice and migration. The 1993 name change from the European Economic Community (EEC) to the European Union (EU) reflected this.

The European Union has delivered more than half a century of peace, stability and prosperity, helped raise living standards and launched a single European currency: the Euro. In 2012, the EU was awarded the Nobel Peace Prize for advancing the causes of peace, reconciliation, democracy and human rights in Europe. The single market is the EU's main economic engine, enabling most goods, services, money and people to move freely.

Content

The European Union covers over 4 million square kilometers and has 508 million inhabitants — the world’s third largest population after China and India. This dataset includes information on each EU member state, candidate state, or European Free Trade Agreement (EFTA) signatory state.

Acknowledgements

The membership, population, and economic data was published by the European Commission's Eurostat. Gross domestic product and GDP per capita in US dollars was provided by the World Bank.

Inspiration

How has the European Union grown in the past fifty years? What is the largest country by population or surface area? Which country has the largest economy by gross domestic product? How many different languages are spoken across all the member states?

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in Gains from Harmonizing US and EU Auto Regulations under the Transatlantic Trade and Investment Partnership, PIIE Policy Brief 15-10. If you use the data, please cite as: Freund, Caroline, and Sarah Oliver. (2015). Gains from Harmonizing US and EU Auto Regulations under the Transatlantic Trade and Investment Partnership. PIIE Policy Brief 15-10. Peterson Institute for International Economics.

This collection provides users with data about R&D expenditure and R&D personnel broken down by the following institutional sectors: business enterprise (BES); government (GOV); higher education (HES); private non-profit (PNP), total of all sectors.

The R&D expenditure is broken down by source of funds; sector of performance; type of costs; type of R&D; fields of research and development (FORD); https://circabc.europa.eu/ui/group/c1b49c83-24a7-4ff2-951c-621ac0a89fd8/library/b4b841e5-d200-41bc-8f23-d0b1e034f689?p=1&n=10&sort=modified_DESC">socio-economic objectives (NABS 2007) and by regions (https://showvoc.op.europa.eu/#/datasets/ESTAT_Nomenclature_of_Territorial_Units_for_Statistics/data">NUTS 2 level). The business enterprise sector is further broken down by economic activity (https://showvoc.op.europa.eu/#/datasets/ESTAT_Statistical_Classification_of_Economic_Activities_in_the_European_Community_Rev._2/data">NACE Rev.2); size class; industry orientation.

R&D personnel data are broken down by professional position; sector of performance; educational attainment level; sex; field of research and development (https://www.oecd.org/innovation/frascati-manual-2015-9789264239012-en.htm">FORD); regions (https://showvoc.op.europa.eu/#/datasets/ESTAT_Nomenclature_of_Territorial_Units_for_Statistics/data">NUTS 2 level); for the business enterprise sector is further broken down in size class and economic activity (NACE Rev.2). Researchers are further broken down by age class and citizenship.

The periodicity of R&D data are every two years, except for the key R&D indicators (R&D expenditure, R&D personnel (in Full Time Equivalent - FTE) and Researchers (in FTE) by sectors of performance) which are transmitted annually by the EU Member States (from 2003 onwards based on a legal obligation). Some other breakdowns of the data may appear on an annual basis based on voluntary data provisions.

The data are collected through sample or census surveys, from administrative registers or through a combination of sources.

R&D data are available for following countries and country groups:

• All EU Member States; Candidate Countries; EFTA Countries; The Organisation for Economic Cooperation and Development (OECD) is data provider for the United States of America, Japan, South Korea and China.
• Country groups: EU Member States, Euro Area States.

R&D data are compiled in accordance to the guidelines laid down in OECD (2015), https://www.oecd.org/publications/frascati-manual-2015-9789264239012-en.htm">Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities and the European business statistics methodological manual for R&D statistics – 2023 edition - Manuals and guidelines - Eurostat

Laos LA: Net Bilateral Aid Flows from Development Assistance Committee Donors: European Commission data was reported at 27.330 USD mn in 2016. This records an increase from the previous number of 10.780 USD mn for 2015. Laos LA: Net Bilateral Aid Flows from Development Assistance Committee Donors: European Commission data is updated yearly, averaging 8.600 USD mn from Dec 1978 (Median) to 2016, with 37 observations. The data reached an all-time high of 27.330 USD mn in 2016 and a record low of 0.200 USD mn in 1982. Laos LA: Net Bilateral Aid Flows from Development Assistance Committee Donors: European Commission data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Laos – Table LA.World Bank: Defense and Official Development Assistance. Net bilateral aid flows from DAC donors are the net disbursements of official development assistance (ODA) or official aid from the members of the Development Assistance Committee (DAC). Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. DAC members are Australia, Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Japan, Republic of Korea, Luxembourg, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, United Kingdom, United States, and European Union Institutions. Regional aggregates include data for economies not specified elsewhere. World and income group totals include aid not allocated by country or region. Data are in current U.S. dollars.; ; Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: www.oecd.org/dac/stats/idsonline.; Sum;

Water and a Green Economy in Latin America and the Caribbean (LAC)

This dataset contains data about two ISEWs for the EU27, its individual Member States (MS), the UK and the US. Following Van der Slycken and Bleys (2023) (1), two variants of the ISEW are presented in this dataset: the ISEW_BCE accounts for the benefits and costs of the present and pasts activities experienced in the present and within a specific country (Benefits and Costs Experienced); the ISEW_BCPA accounts for the benefits and costs of present activities experienced in the present and in the future, both domestically and internationally (Benefits and Costs of Present economic Activities).

This document contains different datasets. Two datasets contain a summary of the values of the ISEWs and their components in ‘per capita’ terms. One summary presents the results for the EU27 (and MS) and the other one presents the results for the UK and the US (Non-EU countries). Additionally, each component is presented in some details in different pages, allowing to see the value of the different subcomponents included in each component (and even the value of some items with subcomponents for some components).

The period covered by this dataset is 1995-2020.

All the components are described in the accompanying table and in the report.

(1) Van der Slycken, J. and Bleys, B. (2023). Towards ISEW and GPI 2.0: Dealing with Cross-Time and Cross-Boundary Issues in a Case Study for Belgium. Social Indicators Research, 168(1):557-583.

Purchasing power parities (PPPs) are indicators of price level differences across countries. PPPs tell us how many currency units a given quantity of goods and services costs in different countries. PPPs can thus be used as currency conversion rates to convert expenditures expressed in national currencies into an artificial common currency (the Purchasing Power Standard, PPS), eliminating the effect of price level differences across countries.

The main use of PPPs is to convert national accounts aggregates, like the Gross Domestic Product (GDP) of different countries, into comparable volume aggregates. Applying nominal exchange rates in this process would overestimate the GDP of countries with high price levels relative to countries with low price levels. The use of PPPs ensures that the GDP of all countries is valued at a uniform price level and thus reflects only differences in the actual volume of the economy.

PPPs are also applied in analyses of relative price levels across countries. For this purpose, the PPPs are divided by the current nominal exchange rate to obtain a price level index (PLI) which expresses the price level of a given country relative to another, or relative to a group of countries like the EU Member States.

The production of PPPs is a multilateral exercise involving the National Statistical Institutes of the participating countries, Eurostat and the OECD.

Indicators in Eurostat's dissemination database

The indicators published in the price domain on Eurostat's website are the following:

• Purchasing power parities (PPPs) scaled to the sum of expenditures of the EU Member States expressed in euro. This means that the PPP of one particular country indicates how many units of national currency one would need in that country in order to maintain the purchasing power of one euro in the EU
• Price level indices (PLIs) as defined above
• Nominal expenditure in national currency, as extracted from each country's national accounts
• Nominal expenditure as percentage of GDP
• Nominal expenditure in euro
• Nominal expenditure per inhabitant in euro
• Real expenditure, defined as nominal expenditure divided by the PPP
• Real expenditure per inhabitant
• Volume indices of real expenditure per inhabitant
• The convergence indicators, defined as the coefficient of variation of the price level indices (PLIs) and per capita volume indices (VIs) of gross domestic product (GDP), actual individual consumption (AIC) and household final consumption expenditure (HFCE). It measures the price and volume convergence across countries.

In addition, PPPs and real expenditures are available from the national accounts domain of the database. For further details, cf. 17.1.

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from the Federal Reserve hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve using Kaggle and all of the data sources available through the Federal Reserve organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Francis Nie on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making.

Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013, amended by Council Regulation (EU) 2023/734 of 15 March 2023.

Gross domestic product (GDP) is one of the key aggregates in the European system of accounts (ESA). GDP is a measure of the total economic activity taking place on an economic territory which leads to output meeting the final demands of the economy.

There are three ways of measuring GDP at market prices:

1. the production approach, as the sum of the values added by all activities which produce goods and services, plus taxes less subsidies on products;
2. the expenditure approach, as the total of all final expenditures made in either consuming the final output of the economy, or in adding to wealth, plus exports less imports of goods and services;
3. the income approach, as the total of all incomes earned in the process of producing goods and services plus taxes on production and imports less subsidies.

Data published in the following tables reflect these 3 approaches.

Breakdowns provided are based on the ESA Transmission Programme, which list all tables requested from the countries.

The annual tables under this collection are the following:

• nama_10_gdp GDP and main components (output, expenditure and income)
• nama_10_pc Main GDP aggregates per capita
• nama_10_a10 Gross value added and income components by A*10 industry
• nama_10_a64 Gross value added and income components by A*64 industry

Geographical entities covered are the European Union, the euro area, EU Member States, EFTA countries and Candidate Countries. Data from other countries (e.g. US, Japan and other countries) are received via the OECD and IMF and published in Eurobase in the naid_10 collection.

Data sources: National Statistical Institutes, Eurostat (for European aggregates).

A cross-national data archive located in Luxembourg that contains two primary databases: the Luxembourg Income Study Database (LIS Database) includes income microdata from a large number of countries at multiple points in time. The newer Luxembourg Wealth Study Database(LWS Database) includes wealth microdata from a smaller selection of countries. Both databases include labor market and demographic data as well. Our mission is to enable, facilitate, promote, and conduct cross-national comparative research on socio-economic outcomes and on the institutional factors that shape those outcomes. Since its beginning in 1983, the LIS has grown into a cooperative research project with a membership that includes countries in Europe, North America, and Australia. The database now contains information for more than 30 countries with datasets that span up to three decades. The LIS databank has a total of over 140 datasets covering the period 1968 to 2005. The primary objectives of the LIS are as follows: * Test the feasibility for creating a database containing social and economic data collected in household surveys from different countries; * Provide a method which allows researchers to use the data under restrictions required by the countries providing the data; * Create a system that allows research requests to be received from and returned to users at remote locations; and * Promote comparative research on the social and economic status of various populations and subgroups in different countries. Data Availability: The dataset is accessed globally via electronic mail networks. Extensive documentation concerning technical aspects of the survey data, variables list, and the social institutions of income provision in member countries are also available to users through the project Website. * Dates of Study: 1968-present * Study Features: International * Sample Size: 30+ Countries Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00150

Foreign direct investment (FDI) is a category of investment that reflects the objective of establishing a lasting interest by a resident enterprise in one economy (direct investor) in an enterprise (direct investment enterprise) that is resident in an economy other than that of the direct investor. The lasting interest implies the existence of a long-term relationship between the direct investor and the direct investment enterprise and a significant degree of influence on the management of the enterprise. The lasting interest is deemed to exist if the investor acquires at least 10% of the voting power of the direct investment enterprise. Data are expressed as % of GDP to remove the effect of differences in the size of the economies of the reporting countries. FDI comprises: - Equity capital comprises equity in branches as well as all shares in subsidiaries and associates. - Reinvested earnings consist of the offsetting entry to the direct investor’s share of earnings not distributed as dividends by subsidiaries or associates, and earnings of branches not remitted to the direct investor and which are recorded under Investment income. - Debt instruments Direct investment is classified primarily on a directional basis: 1) Resident direct investment abroad (Outward direct investment) 2) Non-resident investment in the reporting economy (Inward direct investment). The Inward direct investment is investment by a non-resident direct investor in a direct investment enterprise resident in the host economy; the direction of the influence by the direct investor is inward for the reporting economy. Starting from October 2014 definitions are based on the IMF's Sixth Balance of Payments Manual (BPM6). Copyright notice and free re-use of data on: https://ec.europa.eu/eurostat/about-us/policies/copyright

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in Earmarked Revenues: How the European Union Can Learn from US Budgeting Experience, PIIE Policy Brief 18-2. If you use the data, please cite as: Kirkegaard, Jacob Funk. (2018). Earmarked Revenues: How the European Union Can Learn from US Budgeting Experience. PIIE Policy Brief 18-2. Peterson Institute for International Economics.

This data set contains annual and monthly data for exchange rates important to U.S. agriculture. It includes both nominal and real exchange rates for 79 countries, plus the European Union (EU), as well as real trade-weighted exchange rate indexes for many commodities and aggregations.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web page with links to Excel files For complete information, please visit https://data.gov.