| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/t0273 |
| 来源ID | Technical Working Paper 0273 |
| A New Use of Importance Sampling to Reduce Computational Burden in Simulation Estimation | |
| Daniel A. Ackerberg | |
| 发表日期 | 2001-07-01 |
| 出版年 | 2001 |
| 语种 | 英语 |
| 摘要 | Method of Simulated Moments (MSM) estimators introduced by McFadden (1989)and Pakes and Pollard (1989) are of great use to applied economists. They are relatively easy to use even for estimating very complicated economic models. One simply needs to generate simulated data according to the model and choose parameters that make moments of this simulated data as close as possible to moments of the true data. This paper uses importance sampling techniques to address a significant computational caveat regarding these MSM estimators - that often one's economic model is hard to solve. Examples include complicated equilibrium models and dynamic programming problems. We show that importance sampling can reduce he number of times a particular model needs to be solved in an estimation procedure, significantly decreasing computational burden. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/t0273 |
| 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/565950 |
| 推荐引用方式 GB/T 7714 | Daniel A. Ackerberg. A New Use of Importance Sampling to Reduce Computational Burden in Simulation Estimation. 2001. |
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| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| t0273.pdf（242KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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