This field experiment investigates the causal impact of mothers’ perceptions of gender norms on their employment attitudes and labor-supply expectations. We provide mothers of young children in Germany with information about the prevailing gender norm regarding maternal employment in their city. At baseline, over 70% of mothers incorrectly perceive this gender norm as too conservative. Our randomized treatment improves the accuracy of these perceptions, significantly reducing the share of mothers who misperceive gender norms as overly conservative. The treatment also shifts mothers’ own labor-market attitudes towards being more liberal – and we show that specifically the shifted attitude is a strong predictor of mothers’ future labor-market participation. Consistently, treated mothers are significantly more likely to plan an increase in their working hours one year ahead.

Based on the sufficient statistics approach developed by Huang and Ottaviano (2024), we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation.

Based on the sufficient statistics approach developed by Huang and Ottaviano (2024), we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation.

Zur Jahreswende dürfte die weltweite Produktion weiterhin in etwa so schnell wie in der Dekade vor der Pandemie expandieren. Die Konjunktur im Euroraum ist nur verhalten, und die Stagnation der deutschen Wirtschaft setzt sich fort. Die Industrie verliert an internationaler Wettbewerbsfähigkeit. Unternehmen und Verbraucher halten sich aufgrund unklarer wirtschaftspolitischer Aussichten mit ihren Ausgaben zurück. Das Bruttoinlandsprodukt dürfte im Jahr 2024 um 0,2% sinken und im Jahr 2025 um 0,4% expandieren.

Our results reveal that higher lending spreads between foreign and home markets redirect real estate backed lending towards foreign markets offering a higher interest rate, which provides evidence for "search for yield" behavior. This re-allocation is found especially for banks with more expertise on the foreign market due to a higher local activity and holds for commercial and residential real estate backed loans. Furthermore, "search for yield" behavior and a resulting increase in foreign real estate backed lending is found when macroprudential regulation is missing or misaligned between a bank’s country of residence and the destination country. When turning to the question of whether the detected search for yield behavior results in more risk, we find that especially better capitalized banks report higher forbearance ratios as they might face less stigma effects compared to low capitalized banks.

This field experiment investigates the causal impact of mothers’ perceptions of gender norms on their employment attitudes and labor-supply expectations. We provide mothers of young children in Germany with information about the prevailing gender norm regarding maternal employment in their city. At baseline, over 70% of mothers incorrectly perceive this gender norm as too conservative. Our randomized treatment improves the accuracy of these perceptions, significantly reducing the share of mothers who misperceive gender norms as overly conservative. The treatment also shifts mothers’ own labor-market attitudes towards being more liberal – and we show that specifically the shifted attitude is a strong predictor of mothers’ future labor-market participation. Consistently, treated mothers are significantly more likely to plan an increase in their working hours one year ahead.

The Transition Report 2024-25 focuses on industrial policies in the EBRD regions and beyond. Such policies have seen a resurgence, seeking to address market failures such as environmental degradation. However, their track record is mixed. Their growing popularity is shaped primarily by domestic political economy considerations and rising geopolitical tensions. While industrial policies are typically employed by higher-income economies, they are also now used more frequently in economies with less administrative and fiscal capacity to implement them.

This paper provides a comprehensive analysis of the forecastability of the real price of natural gas in the United States at the monthly frequency considering a universe of models that differ in their complexity and economic content. Our key finding is that considerable reductions in mean-squared prediction error relative to a random walk benchmark can be achieved in real time for forecast horizons of up to two years. A particularly promising model is a six-variable Bayesian vector autoregressive model that includes the fundamental determinants of the supply and demand for natural gas. To capture real-time data constraints of these and other predictor variables, we assemble a rich database of historical vintages from multiple sources. We also compare our model-based forecasts to readily available model-free forecasts provided by experts and futures markets. Given that no single forecasting method dominates all others, we explore the usefulness of pooling forecasts and find that combining forecasts from individual models selected in real time based on their most recent performance delivers the most accurate forecasts.