| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP15092 |
| DP15092 Filtered and Unfiltered Treatment Effects with Targeting Instruments | |
| Sokbae Lee; Bernard Salanie | |
| 发表日期 | 2020-07-23 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | Multivalued treatments are commonplace in applications. We explore the use of discrete-valued instruments to control for selection bias in this setting. We establish conditions under which counterfactual averages and treatment effects are identified for heterogeneous complier groups. These conditions require a combination of assumptions that restrict both the unobserved heterogeneity in treatment assignment and how the instruments target the treatments. We introduce the concept of filtered treatment, which takes into account limitations in the analyst’s information. Finally, we illustrate the usefulness of our framework by applying it to data from the Student Achievement and Retention Project and the Head Start Impact Study. |
| 主题 | Labour Economics |
| 关键词 | Identification Selection Multivalued treatments Discrete instruments Unordered monotonicity Factorial design |
| URL | https://cepr.org/publications/dp15092 |
| 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/544048 |
| 推荐引用方式 GB/T 7714 | Sokbae Lee,Bernard Salanie. DP15092 Filtered and Unfiltered Treatment Effects with Targeting Instruments. 2020. |
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