| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP14100 |
| DP14100 Cheating with (recursive) models | |
| Kfir Eliaz; Ran Spiegler; Yair Weiss | |
| 发表日期 | 2019-11-05 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | To what extent can misspecified models generate false estimated correlations? We focus on models that take the form of a recursive system of linear regression equations. Each equation is fitted to minimize the sum of squared errors against an arbitrarily large sample. We characterize the maximal pairwise correlation that this procedure can predict given a generic objective covariance matrix, subject to the constraint that the estimated model does not distort the mean and variance of individual variables. We show that as the number of variables in the model grows, the false pairwise correlation can become arbitrarily close to one, regardless of the true correlation. |
| 主题 | Industrial Organization |
| URL | https://cepr.org/publications/dp14100 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/542987 |
| 推荐引用方式 GB/T 7714 | Kfir Eliaz,Ran Spiegler,Yair Weiss. DP14100 Cheating with (recursive) models. 2019. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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