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来源类型 | Working Paper |
规范类型 | 报告 |
DOI | 10.3386/w20673 |
来源ID | Working Paper 20673 |
Measuring the Sensitivity of Parameter Estimates to Estimation Moments | |
Isaiah Andrews; Matthew Gentzkow; Jesse M. Shapiro | |
发表日期 | 2014-11-17 |
出版年 | 2014 |
语种 | 英语 |
摘要 | We propose a local measure of the relationship between parameter estimates and the moments of the data they depend on. Our measure can be computed at negligible cost even for complex structural models. We argue that reporting this measure can increase the transparency of structural estimates, making it easier for readers to predict the way violations of identifying assumptions would affect the results. When the key assumptions are orthogonality between error terms and excluded instruments, we show that our measure provides a natural extension of the omitted variables bias formula for nonlinear models. We illustrate with applications to published articles in several fields of economics. |
主题 | Econometrics ; Estimation Methods |
URL | https://www.nber.org/papers/w20673 |
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/578347 |
推荐引用方式 GB/T 7714 | Isaiah Andrews,Matthew Gentzkow,Jesse M. Shapiro. Measuring the Sensitivity of Parameter Estimates to Estimation Moments. 2014. |
条目包含的文件 | 条目无相关文件。 |
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