Rationalizing Policy Functions by Dynamic Optimization
推导了凸约束和凹目标泛函下动态最大化问题中最优政策函数和最优值函数的充要条件，证明每个Lipschitz连续函数都可作为解，并在自由处置和单调性假设下给出完整刻画，适用于标准加总最优增长模型。
We derive necessary and sufficient conditions for a pair of functions to be the optimal policy function and the optimal value function of a dynamic maximization problem with convex constraints and concave objective functional. It is shown that every Lipschitz continuous function can be the solution of such a problem. If the maintained assumptions include free disposal and monotonicity, then we obtain a complete characterization of all optimal policy and optimal value functions. This is the case, e.g., in the standard aggregative optimal growth model.