| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w22627 |
| 来源ID | Working Paper 22627 |
| Using Big Data to Estimate Consumer Surplus: The Case of Uber | |
| Peter Cohen; Robert Hahn; Jonathan Hall; Steven Levitt; Robert Metcalfe | |
| 发表日期 | 2016-09-12 |
| 出版年 | 2016 |
| 语种 | 英语 |
| 摘要 | Estimating consumer surplus is challenging because it requires identification of the entire demand curve. We rely on Uber’s “surge” pricing algorithm and the richness of its individual level data to first estimate demand elasticities at several points along the demand curve. We then use these elasticity estimates to estimate consumer surplus. Using almost 50 million individual-level observations and a regression discontinuity design, we estimate that in 2015 the UberX service generated about $2.9 billion in consumer surplus in the four U.S. cities included in our analysis. For each dollar spent by consumers, about $1.60 of consumer surplus is generated. Back-of-the-envelope calculations suggest that the overall consumer surplus generated by the UberX service in the United States in 2015 was $6.8 billion. |
| 主题 | Public Economics ; Labor Economics ; Industrial Organization |
| URL | https://www.nber.org/papers/w22627 |
| 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/580300 |
| 推荐引用方式 GB/T 7714 | Peter Cohen,Robert Hahn,Jonathan Hall,et al. Using Big Data to Estimate Consumer Surplus: The Case of Uber. 2016. |
| 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 | ||
| w22627.pdf（2056KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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