| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP12589 |
| DP12589 Macroeconomic Nowcasting and Forecasting with Big Data | |
| Domenico Giannone; Andrea Tambalotti | |
| 发表日期 | 2018-01-13 |
| 出版年 | 2018 |
| 语种 | 英语 |
| 摘要 | Data, data, data ... Economists know their importance well, especially when it comes to monitoring macroeconomic conditions -- the basis for making informed economic and policy decisions. Handling large and complex data sets was a challenge that macroeconomists engaged in real-time analysis faced long before "big data" became pervasive in other disciplines. We review how methods for tracking economic conditions using big data have evolved over time and explain how econometric techniques have advanced to mimic and automate best practices of forecasters on trading desks, at central banks, and in other market-monitoring roles. We present in detail the methodology underlying the New York Fed Staff Nowcast, which employs these innovative techniques to produce early estimates of GDP growth, synthesizing a wide range of macroeconomic data as they become available. |
| 主题 | Monetary Economics and Fluctuations |
| 关键词 | Monitoring economic conditions Business cycle analysis High-dimensional data Real-time data flow |
| URL | https://cepr.org/publications/dp12589 |
| 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/541400 |
| 推荐引用方式 GB/T 7714 | Domenico Giannone,Andrea Tambalotti. DP12589 Macroeconomic Nowcasting and Forecasting with Big Data. 2018. |
| 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。
