Comparative Statics by Adaptive Dynamics and the Correspondence Principle
形式化了比较静态分析与系统在参数变化后如何演化的非均衡解释之间的关系，证明外生参数增加会引发内生变量增大的学习动态，且非单调的均衡选择必然预测不稳定均衡。
This paper formalizes the relation between comparative statics and the out-of-equilibrium explanation for how a system evolves after a change in parameters. The paper has two main results. First, an increase in an exogenous parameter sets o# learning dynamics that involve larger values of the endogenous variables. Second, equilibrium selections that are not monotone increasing in the exogenous variables must be predicting unstable equilibria. Moreover, under some conditions monotone comparative statics and stability are equivalent.