Stochastic Monotonicity and Stationary Distributions for Dynamic Economies
研究随机单调过程的平稳分布存在性与稳定性，利用Knaster-Tarski不动点定理和Topkis超模函数理论，为投资、增长和产业均衡等动态经济问题提供分析工具。
The existence and stability of invariant distributions for stochastically monotone processes is studied. The Knaster-Tarski fixed point theorem is applied to establish existence of fixed points of mappings on compact sets of measures that are increasing with respect to a stochastic ordering. Global convergence of a monotone Markov process to its unique invariant distribution is established under an easily verified assumption. Topkis' theory of supermodular functions is applied to stochastic dynamic optimization, providing conditions under which optimal stationary decisions are monotone functions of the state and induce a monotone Markov process. Applications of these results to investment theory, stochastic growth, and industry equilibrium dynamics are given.