How CORRECTIV investigated the EU housing crisis
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Europe has become painfully expensive to live in. Renting is harder. Buying is worse. Surprising? Not really. According to Eurostat data, between 2015 and 2025, rents across the European Union, Norway, Iceland, and Switzerland increased by 21.1 per cent. Home prices rose even faster, jumping as much as 63.6 per cent.
A new analysis by CORRECTIV.Europe offers one of the first continent-wide views of local housing costs. The project features interactive maps of rent and home prices at the municipal level across the European Union, using data from the ESPON House4All dataset, an EU-funded research project that tracked average rents and home prices – as scraped from 100 million online property listings – across nearly 100,000 cities and municipalities in Europe between March 2024 and March 2025. It goes, however, a step further by comparing housing costs to the salaries of a single profession – nurses – revealing which cities are truly affordable to them.
The visualisation and dataset are open to journalists who sign up through CORRECTIV.Europe’s website, providing a powerful tool to explore housing pressures across Europe.
A dataset across 100,000 European cities
CORRECTIV.Europe is a cross-border investigative journalism network linking more than 450 European media and journalists across Europe. It has long focused on stories that are both local and pan-European in scope, often pairing reporting with cross-border data.
By 2024, the housing crisis stood out as an obvious topic to the team, said Frida Thurm, senior reporter at CORRECTIV.Europe, speaking to iMEdD from Berlin. "We always aim at topics that connect to almost everybody in Europe," she added, explaining that housing is usually the biggest expense for European households.
While digging into the issue, Thurm discovered the ESPON House4All dataset. The ESPON researchers collected the data weekly for a year across all EU and EFTA countries. The dataset has limitations, though. Especially for countries in the Balkans where the data was not available.
There have been similar datasets in the past, created by data........
