| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w27406 |
| 来源ID | Working Paper 27406 |
| Belief Distortions and Macroeconomic Fluctuations | |
| Francesco Bianchi; Sydney C. Ludvigson; Sai Ma | |
| 发表日期 | 2020-06-22 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | This paper combines a data rich environment with a machine learning algorithm to provide new estimates of time-varying systematic expectational errors ("belief distortions") embedded in survey responses. We find that distortions are large even for professional forecasters, with all respondent-types over-weighting their own beliefs relative to publicly available information. Forecasts of inflation and GDP growth oscillate between optimism and pessimism by large margins, with biases in expectations evolving dynamically in response to cyclical shocks. The results suggest that artificial intelligence algorithms can be productively deployed to correct errors in human judgement and improve predictive accuracy. |
| 主题 | Macroeconomics ; Macroeconomic Models |
| URL | https://www.nber.org/papers/w27406 |
| 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/585079 |
| 推荐引用方式 GB/T 7714 | Francesco Bianchi,Sydney C. Ludvigson,Sai Ma. Belief Distortions and Macroeconomic Fluctuations. 2020. |
| 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 | ||
| w27406.pdf（975KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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