The Contrarian Bias of Incentivizing Learning
研究了在委托代理关系中，激励专家获取不可观测信息如何内生地产生逆向或从众偏差，并解释了金融分析师中经验丰富者更倾向逆向推荐、新手更从众的矛盾现象。
Abstract Delegating high-stakes decisions creates a fundamental tension: incentivizing experts to acquire unobservable information inevitably distorts their final choices. In a principal-agent setting, we characterize the optimal compensation contract under hidden learning, showing it endogenously generates either contrarian or conformist bias. The direction of this bias depends on learning costs and the precision of public and private information. Our framework links information acquisition incentives to systematic biases in experts’ choices and offers a unifying explanation for conflicting empirical evidence in financial advice: why analysts issue excessive contrarian recommendations, and why inexperienced analysts follow the consensus more than their experienced peers.