Rules of Thumb versus Dynamic Programming
研究动态决策问题中经验法则与动态规划的对比，指出仅基于过去经验比较规则会导致偏好仅适用于好状态的规则，纠正这种偏差需要求解动态规划，并应用于解释消费对暂时收入的敏感性。
This paper studies decision-making with rules of thumb in the context of dynamic decision problems and compares it to dynamic programming. A rule is a fixed mapping from a subset of states into actions. Rules are compared by averaging over past experiences. This can lead to favoring rules which are only applicable in good states. Correcting this good state bias requires solving the dynamic program. We provide a general framework and characterize the asymptotic properties. We apply it to provide a candidate explanation for the sensitivity of consumption to transitory income.