The Ifo Institute for Economic Research is a Munich-based research institution. Ifo is an acronym from Information and Forschung (research). As one of Germany's largest economic think-tanks, it analyses economic policy and is widely known for its monthly Ifo Business Climate Index for Germany. Its research output is significant: about a quarter of the articles published by German research institutes in international journals in economics in 2006 were from Ifo researchers. The Frankfurter Allgemeine Zeitung ranks it as Germany's most influential economics research institute.
Gender gaps in labor-market outcomes often emerge with the arrival of the first child. We investigate a causal link between gender norms and labor-supply expectations within a survey experiment among 2,000 German adolescents. Using a hypothetical scenario, we document that the majority of girls expects to work 20 hours or less per week when having a young child, and expects from their partner to work 30 hours or more. Randomized treatments that highlight the existing traditional norm towards mothers significantly reduce girls’ self-expected labor supply and thereby increase the expected gender difference in labor supply between their partners and themselves (the expected within-family gender gap). Treatment effects persist in a follow-up survey two weeks later, and extend to incentivized outcomes. In a second experiment, we highlight another, more gender-egalitarian, norm towards shared household responsibilities and show that this attenuates the expected within-family gender gap. Our results suggest that social norms play an important role in shaping gender gaps in labor-market outcomes around child birth.
Multivalued treatments are commonplace in applications. We explore the use of discrete-valued instruments to control for selection bias in this setting. Our discussion revolves around the concept of targeting: which instruments target which treatments. It allows us to establish conditions under which counterfactual averages and treatment effects are point- or partially-identified for composite complier groups. We explore the additional identifying power of a positive selection assumption. We illustrate its usefulness by revisiting the findings of Kline and Walters (2016) on the Head Start Impact Study. We derive informative bounds that suggest less beneficial effects of Head Start expansions than their parametric estimates.
Abstract This paper introduces the Granular Trade and Production Activities (GRANTPA) database, which covers international trade flows for 3,124 products and 247 countries over the period 1995–2019 as well as domestic trade flows and production data for the same number of products and years for a subset of 35 European economies. The original data sources that we employ are Eurostat’s Comext and Prodcom databases. A gravity application delivers a large set of product-level ‘home bias’ estimates, which cannot be obtained without domestic trade flows. The average estimates on the standard gravity variables in our model (e.g., distance) are comparable to those from the related literature. However, our disaggregated estimates are very heterogeneous across products, thus highlighting the importance of our new database.
Zusammenfassung In diesem Beitrag beschreiben Christian Gréus, Philipp Heil, Niklas Potrafke, Ramona Schmid und Tuuli Tähtinen, wie Wirtschaftsfachleute geopolitisches Risiko und Verteidigungsausgaben sowie deren ökonomische Auswirkungen einschätzen. Die Daten hierfür wurden im Rahmen des Economic Experts Surveys (EES) des ifo Instituts im Jahr 2025 erhoben. Die Auswertung zeigt, dass das geopolitische Risiko im globalen Norden deutlich höher eingeschätzt wird als im globalen Süden. Die nationalen Verteidigungsausgaben sollten aus Sicht der Wirtschaftsfachleute in vielen Ländern höher sein, als sie es tatsächlich sind. Die von der NATO anvisierte Erhöhung der nationalen Verteidigungsausgaben auf 5 Prozent des jeweiligen Bruttoinlandsprodukts würde dessen Wachstumsrate aus Sicht der Expertinnen und Experten in der mittleren Frist um rund einen halben Prozentpunkt erhöhen.
In this paper, we use high-frequency transaction data to develop a weekly tracker for private consumption expenditures. Furthermore, we apply the transaction data in a nowcasting experiment and compare their performance with other, readily available indicators that are regularly linked to private consumption in Germany. The weekly tracker produces precise estimates and can thus be used in real time, especially in very turbulent times such as a pandemic or the high-inflation-phase in its aftermath. In terms of nowcast accuracy, the tracker outperforms all remaining indicators, making it a powerful tool for applied forecasting work. We intend to regularly publish the weekly consumption tracker in the future, thereby complementing the database for Germany.
