In 2022, Denmark had the highest gross domestic product (GDP) per capita index of the Nordic countries. Denmark's GDP per capita index was at ***, with an index equaling 100 in 2015. The index of all five Nordic countries dropped in 2020 due to the COVID-19 pandemic, and it fell below 2015 levels in Iceland that year.

Denmark donated the most significant percentage of its 2021 gross domestic product (GDP) to help Ukraine over the period between January 2022, and June 2025. Denmark contributed 2.89 percent of its GDP in bilateral aid, followed by Estonia with 2.8 percent of GDP. Besides the Nordic and Baltic countries, the Netherlands donated the largest share of GDP. Western countries sent aid to Ukraine in view of the Russian invasion that began in February 2022. Who donated the most to Ukraine? In absolute terms, the largest bilateral aid allocations to Ukraine were made by the United States, at over 114 billion euros as of June 2025. European Union (EU) institutions, such as the European Commission and the European Council, allocated the second-largest amount of assistance, at almost 63.2 billion euros. The United Kingdom (UK) was the fourth-leading source of bilateral aid. EU aid to Ukraine The EU has supported Ukraine with over 69 billion euros in financial assistance as of January 2022. Of them, the largest share of aid has been provided as additional loans from the European Investment Bank (EIB) and the European Bank of Reconstruction and Development (EBRD). Among EU members, Germany allocated the largest amount of bilateral aid to Ukraine from January 24, 2022, at around 22 billion euros, while Estonia allocated the largest share of GDP.

Source: UNECE Statistical Database, compiled from national and international (CIS, EUROSTAT, IMF, OECD, World Bank) official sources.General note: The UNECE secretariat presents time series ready for immediate analysis. When appropriate, source segments with methodological differences have been linked and rescaled to build long consistent time series.The national accounts estimates are compiled according to 2008 SNA (System of National Accounts 2008) or 1993 SNA (System of National Accounts 1993).Constant price estimates are based on data compiled by the National Statistical Offices (NSOs), which reflect various national practices (different base years, fixed base, chain, etc.). To facilitate international comparisons, the data reported by the NSOs have been scaled to the current price value of of the common reference year. The resulting chain constant price data are not additive.Common currency (US$) estimates are computed by the secretariat using purchasing power parities (PPPs), which are the rates of currency conversion that equalise the purchasing power of different currencies. PPPs, and not exchange rates, should be used in international comparisons of GDP and its components.Growth rates (per cent) are over the preceding period, unless otherwise specified.Contributions to per cent growth in GDP (in percentage points) are over the preceding period, unless otherwise specified.Regional aggregates are computed by the secretariat. For national accounts all current price aggregates are sums of national series converted into US$ at current PPPs of GDP; all constant price aggregates are calculated by summing up national series scaled to the price level of the common reference year and then converted into US$ using PPPs of GDP of the common reference year. Due to conversion and rounding the resulting aggregates and components could be non-additive.Aggregates are computed for the following regions:UNECE-52:Albania; Armenia; Austria; Azerbaijan; Belarus; Belgium; Bosnia and Herzegovina; Bulgaria; Canada; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Georgia; Germany; Greece; Hungary; Iceland; Ireland; Israel; Italy; Kazakhstan; Kyrgyzstan; Latvia; Lithuania; Luxembourg; Malta; Montenegro; Netherlands; North Macedonia; Norway; Poland; Portugal; Republic of Moldova; Romania; Russian Federation; Serbia; Slovakia; Slovenia; Spain; Sweden; Switzerland; Tajikistan; Turkey; Turkmenistan; Ukraine; United Kingdom; United States; Uzbekistan.North America-2:Canada; United States.European Union-27 (31/12/2020):Austria; Belgium; Bulgaria; Cyprus; Croatia; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Hungary; Ireland; Italy; Latvia; Lithuania; Luxembourg; Malta; Netherlands; Poland; Portugal; Romania; Slovakia; Slovenia; Spain; Sweden.Euro area-20:Austria; Belgium; Croatia; Cyprus; Estonia; Finland; France; Germany; Greece; Ireland; Italy; Latvia; Lithuania; Luxembourg; Malta; Netherlands; Portugal; Slovakia; Slovenia; Spain.Eastern Europe, Caucasus and Central Asia (EECCA):Armenia; Azerbaijan; Belarus; Georgia; Kazakhstan; Kyrgyzstan; Republic of Moldova; Russian Federation; Tajikistan; Turkmenistan; Ukraine; Uzbekistan.CIS-11:Armenia; Azerbaijan; Belarus; Kazakhstan; Kyrgyzstan; Republic of Moldova; Russian Federation; Tajikistan; Turkmenistan; Ukraine; Uzbekistan.Western Balkans-6:Albania; Bosnia and Herzegovina; Croatia; Montenegro; North Macedonia; Serbia... - data not availableThe Coronavirus (COVID-19) pandemic impacts the production of statistics and may limit available resources and data sources. This may impact the quality of statistics for 2020, and could lead to later revisions.

In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.

The statistic shows the growth of the real gross domestic product (GDP) in the European Union and the Euro area from 2020 to 2024, with projections up until 2030. GDP refers to the total market value of all goods and services that are produced within a country per year. It is an important indicator of the economic strength of a country. Real GDP is adjusted for price changes and is therefore regarded as a key indicator for economic growth. In 2024, the GDP in the European Union increased by about 1.12 percent compared to the previous year. Growth trends in the EU compared to the euro area The euro area, which is also called the eurozone, is an economic and monetary union (EMU) which includes 19 of the 27 European Union member states which have formally adopted the euro. Those countries include Austria, Belgium, Cyprus, Estonia, Finland, France, Germany, Greece, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Portugal, Slovakia, Slovenia, and Spain. Member states which have not yet adopted the euro include Bulgaria, Croatia, Czechia, Denmark, Hungary, Poland, Romania, Sweden and the United Kingdom. Additionally, there is the so-called Schengen Area, which is composed of EU and non-EU states, and has been established mainly to facilitate travelling in Europe. While some countries, such as Kosovo and Montenegro have adopted the euro unilaterally, they are not formally part of the eurozone. Others have established a monetary agreement with the EU to use the euro, such as Andorra, Monaco, San Marino and the Vatican, but they do not form part of the official euro area. As can be seen in the chart, annual GDP growth slumped in 2012 and 2013, presumably as a result of the global financial crisis, in both the EU and the euro area. In 2013, growth began increasing ever so slightly and in 2014 the EU regained a bit of stability. However, overall recovery in the EU has been relatively moderate and gradual; growth throughout the EU has been slightly better than in the euro area and is projected to remain slightly better for the foreseeable future. Relatively new member states such as Romania and Czechia, which have not yet adopted the euro, reported the highest annual growth rates in the EU in 2015, and generally, new member states show slightly better growth rates. Also, unemployment has been slightly higher in the euro area compared to the EU for the last ten years (267906). The unemployment rate also remains relatively high for both the EU and the euro area. As for public spending as a share of GDP, these figures are slightly higher in the euro area than in the EU as a whole. The member states with the highest national debt include the United Kingdom, Italy, France and Germany - some of the oldest members of the euro area. The national debt of the euro area is slightly higher than the national debt of the EU as a whole, underlining the economic situation of both areas.

This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).

For a more detailed description of the dataset and the coding process, see the codebook available in the .zip-file.

Purpose:

This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).

Gross domestic product (GDP) per capita is a measure of economic production, which takes the entire output of a national economy during a year and divides it by the population of that country. In the European Union, Luxembourg, Ireland, Denmark, the Netherlands, and Austria come out on top as the countries which produced the most per capita in 2024. Europe's richest countries benefit from multinational companies Many criticisms have been made of using GDP per capita as away to judge a country's economic wealth in recent years, as global capital flows have come to distort the statistics and to give a warped impression of different countries' wealth. This is most notably the case for Ireland and for Luxembourg, which while certainly high-income countries, have experienced dramatic booms in their GDP over the past two decades due to the accounting practices of the large multinational corporations which have their European headquarters in these member states, such as Facebook and Apple in Dublin, and Amazon in Luxembourg. Will the poorest countries converge towards the EU average? At the bottom of the list, two of the most recent member states of the EU, Romania and Bulgaria, come last in terms of GDP per capita. Whether these countries will be able to capitalize on their relatively low-wages to spur economic growth and experience the convergence towards the older member states of the union shown by countries such as Estonia, Czechia, and Lithuania, remains a pressing issue for these poorer member states.

At **** U.S. dollars, Switzerland has the most expensive Big Macs in the world, according to the January 2025 Big Mac index. Concurrently, the cost of a Big Mac was **** dollars in the U.S., and **** U.S. dollars in the Euro area. What is the Big Mac index? The Big Mac index, published by The Economist, is a novel way of measuring whether the market exchange rates for different countries’ currencies are overvalued or undervalued. It does this by measuring each currency against a common standard – the Big Mac hamburger sold by McDonald’s restaurants all over the world. Twice a year the Economist converts the average national price of a Big Mac into U.S. dollars using the exchange rate at that point in time. As a Big Mac is a completely standardized product across the world, the argument goes that it should have the same relative cost in every country. Differences in the cost of a Big Mac expressed as U.S. dollars therefore reflect differences in the purchasing power of each currency. Is the Big Mac index a good measure of purchasing power parity? Purchasing power parity (PPP) is the idea that items should cost the same in different countries, based on the exchange rate at that time. This relationship does not hold in practice. Factors like tax rates, wage regulations, whether components need to be imported, and the level of market competition all contribute to price variations between countries. The Big Mac index does measure this basic point – that one U.S. dollar can buy more in some countries than others. There are more accurate ways to measure differences in PPP though, which convert a larger range of products into their dollar price. Adjusting for PPP can have a massive effect on how we understand a country’s economy. The country with the largest GDP adjusted for PPP is China, but when looking at the unadjusted GDP of different countries, the U.S. has the largest economy.