I study a principal-agent model in which a principal hires an agent to collect information about an unknown continuous state. The agent acquires a signal whose distribution is centered around the state, controlling the signal's precision at a cost. The principal observes neither the precision nor the signal, but rather, using transfers that can depend on the state, incentivizes the agent to choose high precision and report the signal truthfully. I identify a sufficient and necessary condition on the agent's information structure which ensures that there exists an optimal transfer with a simple cutoff structure: the agent receives a fixed prize when his prediction is close enough to the state and receives nothing otherwise. This condition is mild and applies to all signal distributions commonly used in the literature.

翻译：本文研究一个委托-代理模型，其中委托人雇佣代理人收集关于未知连续状态的信息。代理人获取一个以状态为中心分布的信号，并以成本控制信号的精度。委托人既无法观测精度也无法观测信号，而是通过可依赖于状态的转移支付，激励代理人选择高精度并真实报告信号。本文识别出代理人信息结构的一个充分必要条件，该条件确保存在具有简单截断结构的最优转移支付：当代理人的预测足够接近状态时获得固定奖励，否则一无所获。该条件较为温和，适用于文献中常用的所有信号分布。