| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w24952 |
| 来源ID | Working Paper 24952 |
| Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change | |
| Edward L. Glaeser; Hyunjin Kim; Michael Luca | |
| 发表日期 | 2018-09-03 |
| 出版年 | 2018 |
| 语种 | 英语 |
| 摘要 | We demonstrate that data from digital platforms such as Yelp have the potential to improve our understanding of gentrification, both by providing data in close to real time (i.e. nowcasting and forecasting) and by providing additional context about how the local economy is changing. Combining Yelp and Census data, we find that gentrification, as measured by changes in the educational, age, and racial composition within a ZIP code, is strongly associated with increases in the numbers of grocery stores, cafes, restaurants, and bars, with little evidence of crowd-out of other categories of businesses. We also find that changes in the local business landscape is a leading indicator of housing price changes, and that the entry of Starbucks (and coffee shops more generally) into a neighborhood predicts gentrification. Each additional Starbucks that enters a zip code is associated with a 0.5% increase in housing prices. |
| 主题 | Microeconomics ; Households and Firms ; Development and Growth ; Development ; Innovation and R& ; D ; Regional and Urban Economics ; Regional Economics |
| URL | https://www.nber.org/papers/w24952 |
| 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/582626 |
| 推荐引用方式 GB/T 7714 | Edward L. Glaeser,Hyunjin Kim,Michael Luca. Measuring Gentrification: Using Yelp Data to Quantify Neighborhood Change. 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 | ||
| w24952.pdf（299KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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