The GDP of Belgium, Luxembourg, and the Netherlands combined (Benelux) amounted to 1.44 trillion euros in 2021. As of 2021, the Netherlands had the highest GDP within the Benelux region at 861 billion euros, while Belgium's GDP was approximately 507 billion euros and Luxembourg's GDP roughly 73 billion.

The current health expenditure as a share of the GDP in Belgium was forecast to continuously increase between 2024 and 2029 by in total *** percentage points. After the eighth consecutive increasing year, the share is estimated to reach ***** percent and therefore a new peak in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. It is depicted here in relation to the total gross domestic product (GDP) of the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current health expenditure as a share of the GDP in countries like Netherlands and Luxembourg.

In 2021, real Gross Domestic Product (GDP) per capita in Belgium was around ****** U.S. dollars, whereas in the Netherlands it was ****** dollars. The highest GDP per capita in the Benelux was recorded in Luxembourg in that year, with a total of almost ******* U.S. dollars.

This dataset provides values for GDP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Nominal GDP in national currency at current prices (France, Germany, United Kingdom, Espagfne, Italy, United States, Netherlands and Belgium)Long series (1988 to 2010)

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.

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).

Explore annual GDP growth rates for various countries with this dataset. Analyze trends and patterns related to GDP growth to make informed decisions. Click here for more information!

GDP growth (annual %), GDP, Growth Rates

Kenya, Spain, Syrian Arab Republic, Bosnia and Herzegovina, El Salvador, Italy, Sint Maarten (Dutch part), Comoros, Kosovo, Argentina, Bulgaria, Guinea-Bissau, Slovenia, Guinea, Belize, Low income, Lower middle income, New Caledonia, St. Kitts and Nevis, Benin, World, Kyrgyz Republic, United Arab Emirates, Ethiopia, Burundi, Korea, Rep., Low & middle income, Euro area, Libya, Luxembourg, Namibia, Kiribati, India, Burkina Faso, East Asia & Pacific (excluding high income), Tajikistan, Lao PDR, Equatorial Guinea, Niger, Liechtenstein, Palau, Hong Kong SAR, China, Switzerland, Tonga, Qatar, Turkiye, Middle East & North Africa (excluding high income), Indonesia, Iraq, Fiji, Central Europe and the Baltics, Isle of Man, Costa Rica, Finland, Small states, Singapore, Slovak Republic, Netherlands, Turks and Caicos Islands, Europe & Central Asia (IDA & IBRD countries), Japan, Bhutan, Belgium, Australia, Denmark, Heavily indebted poor countries (HIPC), Middle East & North Africa (IDA & IBRD countries), Uzbekistan, Pacific island small states, Mongolia, Gabon, St. Vincent and the Grenadines, Ukraine, Venezuela, RB, Latvia, Macao SAR, China, Vietnam, Arab World, Myanmar, Latin America & Caribbean (excluding high income), Haiti, Micronesia, Fed. Sts., Nicaragua, Panama, San Marino, Gambia, The, Guatemala, IDA & IBRD total, Azerbaijan, Chad, Zimbabwe, Mali, Bolivia, Grenada, Mexico, East Asia & Pacific (IDA & IBRD countries), Timor-Leste, Dominica, Peru, Malawi, Trinidad and Tobago, Nauru, Monaco, Tuvalu, Egypt, Arab Rep., Virgin Islands (U.S.), Sao Tome and Principe, Cabo Verde, IDA only, Mozambique, Oman, Yemen, Rep., Albania, New Zealand, Latin America & Caribbean, Rwanda, Cameroon, Lesotho, Solomon Islands, Germany, Bangladesh, Papua New Guinea, Maldives, Moldova, Antigua and Barbuda, Congo, Dem. Rep., Romania, Portugal, Africa Western and Central, Mauritius, France, Uruguay, Tanzania, Colombia, South Asia (IDA & IBRD), Honduras, South Sudan, Sudan, Cuba, Least developed countries: UN classification, South Asia, Tunisia, Guyana, Nepal, Barbados, Brunei Darussalam, United States, Canada, Lebanon, Africa Eastern and Southern, Sub-Saharan Africa (excluding high income), Angola, Bahamas, The, Fragile and conflict affected situations, Malta, Middle East & North Africa, Turkmenistan, Cote d'Ivoire, Northern Mariana Islands, Thailand, Seychelles, North Macedonia, Afghanistan, Russian Federation, IBRD only, Iran, Islamic Rep., Malaysia, Djibouti, Europe & Central Asia (excluding high income), Norway, Dominican Republic, French Polynesia, Jordan, Nigeria, Lithuania, Estonia, Eswatini, Vanuatu, Late-demographic dividend, St. Lucia, Cambodia, Curacao, Kuwait, Belarus, American Samoa, Bahrain, Somalia, Pre-demographic dividend, Ghana, Sierra Leone, Jamaica, Ecuador, European Union, Post-demographic dividend, Brazil, Central African Republic, Chile, Puerto Rico, Pakistan, Uganda, United Kingdom, IDA total, Marshall Islands, Czechia, Channel Islands, Poland, Togo, Latin America & the Caribbean (IDA & IBRD countries), Sweden, Iceland, Armenia, Georgia, Montenegro, Europe & Central Asia, Hungary, IDA blend, Sub-Saharan Africa (IDA & IBRD countries), Paraguay, Zambia, Andorra, OECD members, Bermuda, Early-demographic dividend, Croatia, Upper middle income, Algeria, Samoa, Eritrea, Suriname, Mauritania, Guam, China, Sri Lanka, Congo, Rep., Liberia, Greece, Botswana, East Asia & Pacific, West Bank and Gaza, Philippines, Cayman Islands, Saudi Arabia, South Africa, High income, Serbia, Caribbean small states, Greenland, Cyprus, Aruba, Ireland, Israel, Kazakhstan, Morocco, Madagascar, Other small states, Sub-Saharan Africa, Senegal, Middle income, Austria, North America Follow data.kapsarc.org for timely data to advance energy economics research.

The current health expenditure as a share of the GDP in the Netherlands was forecast to continuously increase between 2024 and 2029 by in total *** percentage points. After the seventh consecutive increasing year, the share is estimated to reach ***** percent and therefore a new peak in 2029. According to Worldbank health spending includes expenditures with regards to healthcare services and goods. It is depicted here in relation to the total gross domestic product (GDP) of the country or region at hand.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the current health expenditure as a share of the GDP in countries like Belgium and Luxembourg.

This statistic shows the total value of assets of pension funds in Belgium, Luxembourg and the Netherlands from 2014 to 2018 (as share of GDP). According to OECD, pension fund assets in the Netherlands were amongst the highest in the world. In 2018, the size of pension funds compared to GDP reached *** percent in the Netherlands. By contrast, pension funds assets were below ***** percent of GDP in Belgium.

This statistic shows the Foreign Direct Investment (FDI) assets and liabilities as share of GDP in Belgium as of 2016. It shows that the ratio of the FDI liabilities outweighed the FDI assets. A Foreign Direct Investment is an investment made by a company or individual in one country in business interests in another country, in the form of either establishing business operations or acquiring business assets in the other country, such as ownership or controlling interest in a foreign company. The banking sector in Belgium has two important characteristics. First, banking is deemed an important part of Belgian culture with a relatively high number of bank offices in the country. In 2015, for example, the total number of offices of banks established in Belgium reached 4,519 in the Flemish region. Second, the Belgian banking landscape has the presence of several big non-Belgian banking concerns, notably Dutch bank ING and France-based BNP Paribas. In 2016, BNP Paribas Fortis, BNP Paribas' Belgian daughter, reached a phased-in Common Equity Tier 1 (CET 1) ratio of approximately 14 percent. In 2016, BNP Paribas Fortis was the leading Belgium-based bank when it comes to assets, with a total of approximately 298 billion euros.

This statistic shows the gross national savings in percent of GDP in the Benelux countries (Belgium, Luxembourg and the Netherlands) in 2017. Of the Benelux countries, the percentage of the Netherlands is the highest. The Global Competitiveness Index (GCI) combines 114 indicators that capture concepts that matter for productivity and long-term prosperity. These indicators are grouped into 12 pillars: institutions, infrastructure, macroeconomic environment, health and primary education, higher education and training, goods market efficiency, labor market efficiency, financial market development, technological readiness, market size, business sophistication, and innovation. These pillars are in turn organized into three subindexes: basic requirements, efficiency enhancers, and innovation and sophistication factors. The three subindexes are given different weights in the calculation of the overall Index, depending on each economy’s stage of development, as proxied by its GDP per capita and the share of exports represented by raw materials.

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.

While the tourism sector GDP share in Luxembourg was forecast to increase long-term between 2023 and 2028 by in total 1.6 percentage points, it is estimated to decrease in the years 2026, 2027 and 2028. The share is estimated to amount to 7.48 percent in 2028. While the share was forecast to increase significant in the next years, the increase will slow down in the future.Depited is the economic contribution of the tourism sector in relation to the gross domestic product of the country or region at hand.The forecast has been adjusted for the expected impact of COVID-19.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).Find more key insights for the tourism sector GDP share in countries like the Netherlands and Belgium.

The European Union is comprised of 27 member states with economies of varying sizes. In 2024, Germany, France, and Italy made up over half of the European economy's output. Roughly another quarter of the union's GDP was made up by the next five largest economies, Spain, the Netherlands, Poland, Sweden, and Belgium. The remaining 19 member states make up the rest of the EU's GDP, with around 20 percent collectively.

The tourism sector GDP share in France was forecast to continuously increase between 2023 and 2028 by in total *** percentage points. The share is estimated to amount to **** percent in 2028.Depited is the economic contribution of the tourism sector in relation to the gross domestic product of the country or region at hand.The forecast has been adjusted for the expected impact of COVID-19.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than *** countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).Find more key insights for the tourism sector GDP share in countries like Belgium and the Netherlands.

The real total consumer spending on restaurants and hotels in Luxembourg was forecast to continuously increase between 2024 and 2029 by in total 215.2 million U.S. dollars (+13.47 percent). After the ninth consecutive increasing year, the real restaurants- and hotels-related spending is estimated to reach 1.8 billion U.S. dollars and therefore a new peak in 2029. Consumer spending, in this case concerning restaurants and hotels, refers to the domestic demand of private households and non-profit institutions serving households (NPISHs). Spending by corporations and the state is not included. The forecast has been adjusted for the expected impact of COVID-19.Consumer spending is the biggest component of the gross domestic product as computed on an expenditure basis in the context of national accounts. The other components in this approach are consumption expenditure of the state, gross domestic investment as well as the net exports of goods and services. Consumer spending is broken down according to the United Nations' Classification of Individual Consumption By Purpose (COICOP). The shown data adheres broadly to group 11. As not all countries and regions report data in a harmonized way, all data shown here has been processed by Statista to allow the greatest level of comparability possible. The underlying input data are usually household budget surveys conducted by government agencies that track spending of selected households over a given period.The data has been converted from local currencies to US$ using the average constant exchange rate of the base year 2017. The timelines therefore do not incorporate currency effects. The data is shown in real terms which means that monetary data is valued at constant prices of a given base year (in this case: 2017). To attain constant prices the nominal forecast has been deflated with the projected consumer price index for the respective category.Find more key insights for the real total consumer spending on restaurants and hotels in countries like Netherlands and Belgium.

COVID-19 led to a dramatic increase in the daily active users (DAU) of PayPal apps on iOS and Android among European users, but at varying degrees. This according to numbers calculated from Airnow PLC. Big surges can be observed, for example, in Turkey, France, and Belgium, whereas Poland barely showed an increase. In 2019, figures for the United Kingdom and Germany were already significantly higher than those of other European countries. Europe has many different digital payment methods or mobile wallets. Overall, debit cards rank as the most popular online payment method, with mobile fintech applications being slightly more popular than credit cards. PayPal is widely considered to be one of the few apps that sees use among multiple countries in the European continent. Payment options in Europe In theory, PayPal can be used in every country on the European continent except for Belarus. Note, however, that several countries offer domestic payment options that work both offline as well as online. Comparing the many payment brands within Europe shows how different each European country is in this. Visa and MasterCard, globally regarded as leading brands in payments, had varying market shares across Europe in 2018. Sometimes their market share was significantly lower than domestic payment card schemes. In Denmark, for example, domestic card scheme Dankort (a payment card as well as a mobile wallet) had a market share of ** percent (combining offline and online payments). In short, PayPal is available in Europe but might have domestic alternatives that very per country. Differences in European (cross-border) e-commerce PayPal use in Europe is very much connected to e-commerce. Like for payment methods, however, there are many differences in online shopping in Europe. In 2019, the United Kingdom was Europe's biggest B2C e-commerce market in absolute terms, followed by Germany. This picture changes somewhat when looking at the share of e-commerce within a country's GDP, however. Then, Denmark, Norway, the Netherlands, and Belgium join the UK and France as countries where online shopping made up more than ***** percent of GDP. Differences are even larger for cross-border e-commerce. Smaller European states, such as Malta, Cyprus, Montenegro, Luxembourg, and Iceland were most likely to buy something online from a foreign seller, either from within or outside the EU. Consumers from Turkey, the Netherlands, Poland, and Sweden, on the other hand, tended to buy more from domestic sellers.

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.