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Title: Henry Ford and Antisemitism (Johannes Buggle, Seyhun Sakalli, Alexandre Verlet, Ekaterina Zhuravskaya)
Abstract: We investigate whether economically powerful individuals leverage their business influence to advance political or ideological agendas. We study the impact of Henry Ford鈥檚 newspaper, The Dearborn Independent, which disseminated anti-Jewish conspiracy theories in the early 1920s, on the diffusion of antisemitism across the United States. To measure local antisemitic sentiment, we construct a novel granular index based on digitized data from discriminatory classified advertisements in local newspapers. Exploiting variation in exposure arising from the geographic distribution of Ford dealerships—since newspaper subscriptions were distributed with Ford car purchases—and the timing of the campaign鈥檚 onset, we employ a difference-in-differences design to estimate its effect. To isolate exogenous variation, we instrument for local exposure using market saturation with competing automobile brands, while controlling for detailed demographic characteristics. Our results indicate that the Ford campaign significantly increased antisemitic classified ads in counties with more Ford dealerships. Event-study estimates show no pre-trends and reveal that the effects persisted until World War II. These findings demonstrate how businesspeople can shape social and political attitudes over the long term without going into politics.

Title: Screening Information

Fields: Micro Theory

Title: The Role of Confidence Measures in European Unemployment Dynamics.

Abstract: This paper explores the role of confidence measures in macroeconomic dynamics, focusing on their impact on unemployment in Europe. Using a mixed-frequency Panel FAVAR model with data from 22 European countries, we find that confidence shocks, which have no immediate effect on productivity or unemployment, are strongly correlated with non-technological shocks driving long-term unemployment dynamics. By applying a simultaneous identification approach with short- and long-run restrictions, we show that confidence shocks account for approximately 50% of unemployment variance in the medium run. These results support the 鈥渘ews鈥� view of confidence and challenge both the traditional view that focuses solely on technological news and the conventional belief that technological news shocks are the primary drivers of business cycles, suggesting instead that confidence-related shocks linked to non-technological factors play a significant role. To validate our empirical findings, we develop a structural search and matching model, demonstrating that under adaptive learning, confidence shocks in the form of news can explain a substantial portion of unemployment fluctuations. This research shifts the focus from technological to confidence-related shocks, providing new insights into labor market dynamics. (Authors: Marta Garcia Rodriguez (BdE) and Clemente Pinilla Torremocha (BoE & ERUNI))