π€ AI Summary
This study investigates Pareto optimal allocations in discrete-time, multi-period pure exchange economies under dynamic risk measures. By introducing the notion of dynamically Pareto optimal allocations, the authors establish a comonotonic improvement theorem and, under distribution-invariant preferences, recursively construct optimal allocations backward from the terminal period using strongly time-consistent dynamic risk measures and comonotonicity arguments. For distortion-based dynamic risk measures, they further derive closed-form solutions. In a two-period setting, the paper explicitly characterizes Pareto optimal allocations that align with agentsβ dynamic preferences, thereby demonstrating both the validity and practical tractability of the proposed approach.
π Abstract
We study a problem of optimal allocation in a discrete-time multi-period pure-exchange economy, where agents have preferences over stochastic endowment processes that are represented by strongly time-consistent dynamic risk measures. We introduce the notion of dynamic Pareto-optimal allocation processes and show that such processes can be constructed recursively starting with the allocation at the terminal time. We further derive a comonotone improvement theorem for allocation processes, and we provide a recursive approach to constructing comonotone dynamic Pareto optima when the agents' preferences are coherent and satisfy a property that we call equidistribution-preserving. In the special case where each agent's dynamic risk measure is of the distortion type, we provide a closed-form characterization of comonotone dynamic Pareto optima. We illustrate our results in a two-period setting.