The Principal-Agent Approach to Testing Experts
研究了在无法确定专家是否了解数据生成过程时，决策者如何通过设计合同实现最优收益，发现无限期无贴现模型中总能实现完全剩余提取，而贴现情况下则受预测技术约束。
Recent literature on testing experts shows that it is often impossible to determine whether an expert knows the stochastic process that generates data. Despite this negative result, we show that there often exist contracts that allow a decision maker to attain the first-best payoff without learning the expert's type. This kind of full-surplus extraction is always possible in infinite-horizon models in which future payoffs are not discounted. If future payoffs are discounted (but the discount factor tends to 1), the possibility of full-surplus extraction depends on a constraint involving the forecasting technology.