| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP15308 |
| DP15308 Urban economics in a historical perspective: Recovering data with machine learning | |
| Pierre-Philippe Combes; Laurent Gobillon; Yanos Zylberberg | |
| 发表日期 | 2020-09-18 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | A recent literature has used a historical perspective to better understand fundamental questions of urban economics. However, a wide range of historical documents of exceptional quality remain underutilised: their use has been hampered by their original format or by the massive amount of information to be recovered. In this paper, we describe how and when the flexibility and predictive power of machine learning can help researchers exploit the potential of these historical documents. We first discuss how important questions of urban economics rely on the analysis of historical data sources and the challenges associated with transcription and harmonisation of such data. We then explain how machine learning approaches may address some of these challenges and we discuss possible applications. |
| 主题 | International Trade and Regional Economics |
| 关键词 | Urban economics History Machine learning |
| URL | https://cepr.org/publications/dp15308-0 |
| 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/544285 |
| 推荐引用方式 GB/T 7714 | Pierre-Philippe Combes,Laurent Gobillon,Yanos Zylberberg. DP15308 Urban economics in a historical perspective: Recovering data with machine learning. 2020. |
| 条目包含的文件 | 条目无相关文件。 | |||||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
