Inequality Constraints and Euler Equation-based Solution Methods
研究如何用基于欧拉方程的迭代方法（时间迭代）求解带有不等式约束的动态模型，证明该方法在多种条件下收敛到真实解，对需要快速可靠求解这类模型的经济学者有用。
Solving dynamic models with inequality constraints poses a challenging problem for two major reasons: dynamic programming techniques are reliable but often slow, whereas Euler equation‐based methods are faster but have problematic or unknown convergence properties. This study attempts to bridge this gap. I show that a common iterative procedure on the first‐order conditions – usually referred to as time iteration – delivers a sequence of approximate policy functions that converges to the true solution under a wide range of circumstances. These circumstances extend to a large set of endogenous and exogenous state variables as well as a very broad spectrum of occasionally binding constraints.