Luxembourg and Ireland stand far above the rest
In 2024, Luxembourg and Ireland remain clear outliers, with GDP per capita in PPS far above the EU average and well ahead of other EU and EFTA countries.
GDP per capita across Europe
GDP per capita relative to the EU average
GDP per capita is one of the most widely used indicators for comparing economic prosperity across Europe. This page uses GDP per capita in Purchasing Power Standards (PPS), where the EU average equals 100. Values above 100 indicate a level above the EU average, while values below 100 indicate a level below it.
The time series shows how countries moved relative to the EU average between 2014 and 2024. The latest map and table then provide a clear snapshot of the most recent year, making it easier to see which countries remain far above the EU average, which are catching up, and where gaps persist.
Explore the data
Key insights
Catch-up is visible, but uneven
Several Central and Eastern European countries moved closer to the EU average between 2014 and 2024, but the pace of convergence differs strongly by country.
PPS improves cross-country comparison
By adjusting for price-level differences, PPS makes cross-country comparisons more meaningful than nominal GDP per capita alone.
Key comparisons
Selected highlights from the Eurostat GDP per capita in PPS dataset, 2014–2024. The EU average equals 100.
Extended analysis
1) A simple benchmark: the EU average equals 100
GDP per capita in PPS is useful because it turns a complex economic comparison into a simple benchmark. A value of 100 represents the EU average. Countries above 100 are above the EU average, while countries below 100 are below it.
This makes the indicator easy to read visually. In 2024, countries such as Luxembourg (245), Ireland (221), Norway (160) and Switzerland (151) stand far above the average, while several countries in Central, Eastern and Southern Europe remain below it.
2) The 2024 snapshot shows very large gaps
The latest year shows that differences in GDP per capita adjusted for purchasing power remain substantial. At the top, Luxembourg reaches 245, followed by Ireland (221). At the bottom, Bulgaria records 66, followed by Latvia (68) and Greece (69).
This means that even after adjusting for price levels, the distance between the highest and lowest values is still very large. The map is therefore useful not only for identifying leaders and laggards, but also for seeing how wide the economic gap remains.
3) Catch-up is real, but it is not the same everywhere
Several countries moved closer to the EU average between 2014 and 2024. Among countries that started below the EU average, the strongest improvement was recorded in Romania (+22 index points), followed by Cyprus (+19) and Bulgaria and Croatia (+18 each).
These movements show that convergence is visible in the data, especially in parts of Central and Eastern Europe. However, the same decade also shows that catching up is gradual. Even after improving, many countries remain below the EU average in 2024.
4) Outliers matter when reading the ranking
Luxembourg and Ireland dominate the upper end of the ranking. Both countries are important outliers, and their high values can stretch the visual scale of a chart. This is especially visible in the time series, where most other countries are grouped much closer to the EU average.
For this reason, it is useful to read the chart in two ways: first, by noting the clear outliers at the top; and second, by comparing the large group of countries between roughly 70 and 130, where many of the most relevant convergence patterns take place.
How to read this indicator
GDP per capita in PPS is designed for comparing economic prosperity across countries after adjusting for differences in price levels. It is a useful indicator of relative economic output per person, but it should not be interpreted as household income or take-home purchasing power. It can be influenced by economic structure, multinational activity, commuting patterns and national accounting effects. Liechtenstein is not shown because comparable data were not available in the dataset used here.