Social Connections and Information Leakage: Evidence from Target Stock Price Run-up in Takeovers
Iftekhar Hasan, Lin Tong, An Yan
Journal of Financial Research,
forthcoming
Abstract
Does information leakage in a target's social networks increase its stock price prior to a merger announcement? Evidence reveals that a target with more social connections indeed experiences a higher pre-announcement price run-up. This effect does not exist during or after the merger announcement, or in windows ending two months before the announcement. It is more pronounced among targets with severe asymmetric information, and weaker when the information about the upcoming merger is publicly available prior to the announcement. It is also weaker in expedited deals such as tender offers.
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What’s the Melting Pot Worth? Multiculturalism and House Prices
Rachel Cho, Hisham Farag, Christoph Görtz, Danny McGowan, Huyen Nguyen, Max Schröder
IWH Discussion Papers,
No. 11,
2025
Abstract
Is there a multicultural neighborhood price premium? We exploit plausibly exogenous variation in British colonization patterns in Northern Ireland during the early 1600s which created neighborhoods of varying religious composition that persists until today. These religious groups are culturally distinct, but are observationally equivalent ethnically and socioeconomically. A standard deviation increase neighborhood-level multiculturalism raises house prices by 9.6%. Multiculturalism raises property prices by increasing asset liquidity and housing demand as a wider spectrum of society demand houses in these areas. The findings and mechanism contrast sharply with prior evidence showing negative relationships due to homophily, social networks, and identification challenges.
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Robots, Occupations, and Worker Age: A Production-unit Analysis of Employment
Liuchun Deng, Steffen Müller, Verena Plümpe, Jens Stegmaier
European Economic Review,
November
2024
Abstract
We analyse the impact of robot adoption on employment composition using novel micro data on robot use in German manufacturing plants linked with social security records and data on job tasks. Our task-based model predicts more favourable employment effects for the least routine-task intensive occupations and for young workers, with the latter being better at adapting to change. An event-study analysis of robot adoption confirms both predictions. We do not find adverse employment effects for any occupational or age group, but churning among low-skilled workers rises sharply. We conclude that the displacement effect of robots is occupation biased but age neutral, whereas the reinstatement effect is age biased and benefits young workers most.
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