This paper applies the explicit aggregation (XPA) algorithm to the standard heterogeneous agent model with aggregate uncertainty in continuous time. We find that the XPA algorithm is faster in solving the model than the Krusell–Smith algorithm, because the XPA algorithm does not rely on simulations within the algorithm to solve the model. The XPA algorithm is more accurate than the perturbation method when aggregate uncertainty is large.

中文翻译：

---

将显式聚合算法应用于连续时间的异构代理模型

本文将显式聚合（XPA）算法应用于具有连续时间聚合不确定性的标准异构代理模型。我们发现 XPA 算法在求解模型方面比 Krusell-Smith 算法更快，因为 XPA 算法不依赖于算法内部的模拟来求解模型。当聚合不确定性较大时，XPA 算法比扰动法更准确。