| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w25217 |
| 来源ID | Working Paper 25217 |
| On the Informativeness of Descriptive Statistics for Structural Estimates | |
| Isaiah Andrews; Matthew Gentzkow; Jesse M. Shapiro | |
| 发表日期 | 2018-11-05 |
| 出版年 | 2018 |
| 语种 | 英语 |
| 摘要 | We propose a way to formalize the relationship between descriptive analysis and structural estimation. A researcher reports an estimate ĉ of a structural quantity of interest c that is exactly or asymptotically unbiased under some base model. The researcher also reports descriptive statistics γ̂ that estimate features γ of the distribution of the data that are related to c under the base model. A reader entertains a less restrictive model that is local to the base model, under which the estimate ĉ may be biased. We study the reduction in worst-case bias from a restriction that requires the reader's model to respect the relationship between c and γ specified by the base model. Our main result shows that the proportional reduction in worst-case bias depends only on a quantity we call the informativeness of γ̂ for ĉ. Informativeness can be easily estimated even for complex models. We recommend that researchers report estimated informativeness alongside their descriptive analyses, and we illustrate with applications to three recent papers. |
| 主题 | Econometrics ; Estimation Methods ; Microeconomics ; Households and Firms ; Health, Education, and Welfare ; Health ; Education |
| URL | https://www.nber.org/papers/w25217 |
| 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/582891 |
| 推荐引用方式 GB/T 7714 | Isaiah Andrews,Matthew Gentzkow,Jesse M. Shapiro. On the Informativeness of Descriptive Statistics for Structural Estimates. 2018. |
| 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 | ||
| w25217.pdf（1230KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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