Real estate is a capstone connection between various economic agents and markets. It is the main store of household wealth, serves as collateral for mortgage loans in the banking system, aids the transmission of monetary policy, and can propagate financial crises when overvalued. Yet comparable house-price data across the European Union (EU) and the euro area is unavailable, which hinders the design and evaluation of common monetary and economic policy that operates across heterogeneous housing markets. We derive monthly subnational European Real Estate Indicators (EREI) from online residential property advertisements in 16 European countries. The release covers April 2024 to June 2026 and contains 48,168 region-month-segment observations for 1,154 NUTS 3 regions, aggregating more than 43 million listing observations across the monthly sale and rental cross-sections. Each region-month segment reports the number of advertisements and summary statistics for asking prices per square meter and listing durations. The release also includes sale-segment indices for Europe, the euro area, and individual countries. Thirteen covered countries are EU members, which represented 85% of EU-27 gross domestic product in 2024. EREI data support research on a wide range of socio-economic phenomena associated with real estate dynamics, such as the evaluation of monetary policy or macroprudential policy effects on financial stability.

Many countries and regions remain below the level of economic activity of the world’s most advanced economies. Some countries form growth clubs, some are stuck in the middle-income trap, and some stay on a very low level of economic activity. Although this situation is well documented on the country level, there is less evidence at the sub-national level within countries. We estimate county-level capital stocks and price indices and provide a comprehensive county-level data set for Germany. We find no evidence of convergence across all counties even if we condition on important drivers of long-term growth such as physical and human capital accumulation. Instead, we identify five convergence clubs, using endogenous clustering. We analyze differences in growth paths and describe the identified clusters based on variations in contributions of capital, labor, and total factor productivity to economic growth. Additionally, we examine the role of migration for regional development and find that net migration has in particular contributed to growth in richer regions.

This paper examines how firms adjust the number and types of workers they hire in response to increased biodiversity transition risk. Using the adoption of the Key Biodiversity Areas Standard of 2016 as a source of variation that increases the risk of future land-use restrictions, we find that firms reduce job postings in affected areas and reallocate labor to less exposed regions. This effect is concentrated among firms that make negative impacts on biodiversity. Cuts are stronger among production roles, while hiring in green and adaptive occupations increases. The effect is not driven by changes in capital investment or workers’ labor supply decisions. Our findings contribute to the ongoing debate on the costs and benefits of biodiversity conservation policies and their implications for labor market outcomes.

We study the effects of place-based policies on aggregate productivity using administrative data on projects co-financed by the EU in Italy linked to balance sheet data. We exploit quasi-experimental variation in funding for a large place-based policy stemming from measurement error in regional GDP estimates. Results show that the policy likely decreases productivity. Decompositions reveal that aggregate declines are driven by reallocation of labor to low-productivity firms. Mechanism analysis using firm-level event studies reveals that negative reallocation effects are caused by high-productivity firms taking up the funds and subsequently becoming more liquidity constrained, leading to slowdowns in employment growth.