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来源类型 | Working Paper |
规范类型 | 报告 |
DOI | 10.3386/w26872 |
来源ID | Working Paper 26872 |
FRED-QD: A Quarterly Database for Macroeconomic Research | |
Michael McCracken; Serena Ng | |
发表日期 | 2020-03-23 |
出版年 | 2020 |
语种 | 英语 |
摘要 | In this paper we present and describe a large quarterly frequency, macroeconomic database. The data provided are closely modeled to that used in Stock and Watson (2012a). As in our previous work on FRED-MD, our goal is simply to provide a publicly available source of macroeconomic “big data” that is updated in real time using the FRED database. We show that factors extracted from this data set exhibit similar behavior to those extracted from the original Stock and Watson data set. The dominant factors are shown to be insensitive to outliers, but outliers do affect the relative influence of the series as indicated by leverage scores. We then investigate the role unit root tests play in the choice of transformation codes with an emphasis on identifying instances in which the unit root-based codes differ from those already used in the literature. Finally, we show that factors extracted from our data set are useful for forecasting a range of macroeconomic series and that the choice of transformation codes can contribute substantially to the accuracy of these forecasts. |
主题 | Econometrics ; Estimation Methods ; Macroeconomics |
URL | https://www.nber.org/papers/w26872 |
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/584545 |
推荐引用方式 GB/T 7714 | Michael McCracken,Serena Ng. FRED-QD: A Quarterly Database for Macroeconomic Research. 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 | ||
w26872.pdf(346KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 |
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