Using Models to Persuade

• 成果类型: Article
• 署名作者: Schwartzstein, Joshua; Sunderam, Adi
• 署名单位: Harvard University
• 刊物名称: AMERICAN ECONOMIC REVIEW
• ISSN/ISSBN: 0002-8282
• DOI: 10.1257/aer20191074
• 发表日期: 2021
• 页码: 276-323
• 关键词: technical analysis; media bias; INFORMATION; COMPETITION; paradigm; benefits; ADVISERS; MARKET; tests; news

摘要

We present a framework where model persuaders inf hence receivers' beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers' prior beliefs. Model persuaders face a trade-gTh better-fitting models induce less movement in receivers' beliefs. Consequently, a receiver exposed to the true model can be most misled by persuasion when that model fits poorly, competition between persuaders tends to neutralize the data by pushing toward better-fitting models, and a persuader facing multiple receivers is more effective when he can send tailored, private messages.