Matlab code for "Numerically stable and accurate stochastic simulation approaches for solving dynamic economic models"
Matlab code for "Numerically stable and accurate stochastic simulation approaches for solving dynamic economic models"
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“求解动态经济模型的数值稳定且准确的随机模拟方法”的 Matlab 代码
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Serguei Maliar
中科院分区：
文献类型：
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作者：
K. Judd;L. Maliar;Serguei Maliar
我们开发了数值稳定和精确的随机模拟方法来求解动态经济模型。首先，我们研究了各种替代方法，包括使用奇异值分解和Tikhonov正则化的最小二乘法、最小绝对偏差方法和主成分回归方法，这些方法在数值上是稳定的，可以处理病态问题。其次，我们使用精确的正交和单次积分来代替传统的蒙特卡罗积分。本文在典型代理新古典增长模型、罕见灾害模型和具有数百个状态变量的多国模型三种应用中对广义随机模拟算法（GSSA）进行了测试。GSSA编程简单，并提供了MATLAB代码。
We develop numerically stable and accurate stochastic simulation approaches for solving dynamic economic models. First, instead of standard least-squares methods, we examine a variety of alternatives, including least-squares methods using singular value decomposition and Tikhonov regularization, least-absolute deviations methods, and principal component regression method, all of which are numerically stable and can handle ill-conditioned problems. Second, instead of conventional Monte Carlo integration, we use accurate quadrature and monomial integration. We test our generalized stochastic simulation algorithm (GSSA) in three applications: the standard representative agent neoclassical growth model, a model with rare disasters and a multi-country models with hundreds of state variables. GSSA is simple to program, and MATLAB codes are provided.