| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w15296 |
| 来源ID | Working Paper 15296 |
| Numerically Stable Stochastic Simulation Approaches for Solving Dynamic Economic Models | |
| Kenneth Judd; Lilia Maliar; Serguei Maliar | |
| 发表日期 | 2009-08-27 |
| 出版年 | 2009 |
| 语种 | 英语 |
| 摘要 | We develop numerically stable stochastic simulation approaches for solving dynamic economic models. We rely on standard simulation procedures to simultaneously compute an ergodic distribution of state variables, its support and the associated decision rules. We differ from existing methods, however, in how we use simulation data to approximate decision rules. Instead of the usual least-squares approximation methods, we examine a variety of alternatives, including the least-squares method using SVD, Tikhonov regularization, least-absolute deviation methods, principal components regression method, all of which are numerically stable and can handle ill-conditioned problems. These new methods enable us to compute high-order polynomial approximations without encountering numerical problems. Our approaches are especially well suitable for high-dimensional applications in which other methods are infeasible. |
| 主题 | Microeconomics ; Mathematical Tools |
| URL | https://www.nber.org/papers/w15296 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/572971 |
| 推荐引用方式 GB/T 7714 | Kenneth Judd,Lilia Maliar,Serguei Maliar. Numerically Stable Stochastic Simulation Approaches for Solving Dynamic Economic Models. 2009. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w15296.pdf（448KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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