| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w25574 |
| 来源ID | Working Paper 25574 |
| Are Sufficient Statistics Necessary? Nonparametric Measurement of Deadweight Loss from Unemployment Insurance | |
| David S. Lee; Pauline Leung; Christopher J. O'; Leary; Zhuan Pei; Simon Quach | |
| 发表日期 | 2019-02-25 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | Central to the welfare analysis of income transfer programs is the deadweight loss associated with possible reforms. To aid analytical tractability, its measurement typically requires specifying a simplified model of behavior. We employ a complementary “decomposition” approach that compares the behavioral and mechanical components of a policy’s total impact on the government budget to study the deadweight loss of two unemployment insurance policies. Experimental and quasi-experimental estimates using state administrative data show that increasing the weekly benefit is more efficient (with a fiscal externality of 53 cents per dollar of mechanical transferred income) than reducing the program’s implicit earnings tax. |
| 主题 | Econometrics ; Estimation Methods ; Public Economics ; Taxation ; Labor Economics ; Unemployment and Immigration |
| URL | https://www.nber.org/papers/w25574 |
| 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/583248 |
| 推荐引用方式 GB/T 7714 | David S. Lee,Pauline Leung,Christopher J. O',et al. Are Sufficient Statistics Necessary? Nonparametric Measurement of Deadweight Loss from Unemployment Insurance. 2019. |
| 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 | ||
| w25574.pdf（609KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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