时间：2026年4月17日 上午10:00 – 11:30

地点：承泽园229

Abstract: We develop a bank-run theory in a data economy. We aim to examine how data helps banks mitigate information frictions in lending, and how data distribution across banks influences credit market competition and financial fragility. In our model, banks lend to firms with default risks and must infer firm quality to allocate credit efficiently. Data enables a bank to more precisely screen high-quality firms, thereby increasing the bank's credit profit and reducing the risks of runs. However, in an environment of bank competition, an asymmetric increase in data across banks can cause the one with less data to lose high-quality borrowers, thereby increasing its vulnerability to bank runs. We further characterize bank-run risk contagion by considering endogenous fire sales. When the large bank leverages data advantages to squeeze the smaller bank's profits and trigger runs, the resulting decline in fire-sale prices may backfire, increasing the large bank's own fragility. Finally, we analyze potential policy interventions that can mitigate systemic vulnerabilities arising from dispersed data distribution.

许志伟，复旦大学经济学院教授、博士生导师，主要研究领域为中国宏观经济、宏观金融与货币政策，长期致力于具有微观基础的中国宏观经济理论与定量研究。主持国家自然科学基金青B、面上、青年，以及教育部哲学社会科学研究重大专项等多项课题。研究成果获全国优秀财政理论研究成果一等奖、上海市哲学社会科学优秀成果论文类一等奖、浦山世界经济青年论文奖等，论文入选ESI高被引论文。代表性成果发表于American Economic Journal: Macroeconomics、Economic Journal、Journal of Development Economics、Journal of Economic Theory、Journal of Monetary Economics、Quantitative Economics、Review of Economic Dynamics等国际A类期刊，以及《经济研究》《管理世界》《经济学（季刊）》等国内权威期刊。目前担任China & World Economy、Economic Modelling、《经济学报》《金融学季刊》等学术期刊副主编，是“经济波动与增长”宏观学术会议的主要发起人和组织者。