大数据计量经济学:现在的预测和早期的估计

Massimiliano Marcellino, Fotis Papailias, G. Mazzi, G. Kapetanios, Dario Buono
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引用次数: 11

摘要

本文旨在介绍大数据在宏观经济临近预测和早期估计中的应用。我们将讨论:(i)与宏观经济临近预报和早期估计相关的大数据特征类型,(ii)从非结构化大数据提取可用时间序列特征的方法,(iii)可用于大数据临近预报的计量经济学方法,(iv)四个欧盟国家关键目标变量的一些经验临近预报结果,以及(v)评估临近预报和灰估计的方法。最后,我们提供了一组建议,以评估在特定的经验临近预报背景下使用大数据的利弊。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data Econometrics: Now Casting and Early Estimates
This paper aims at providing a primer on the use of big data in macroeconomic nowcasting and early estimation. We discuss: (i) a typology of big data characteristics relevant for macroeconomic nowcasting and early estimates, (ii) methods for features extraction from unstructured big data to usable time series, (iii) econometric methods that could be used for nowcasting with big data, (iv) some empirical nowcasting results for key target variables for four EU countries, and (v) ways to evaluate nowcasts and ash estimates. We conclude by providing a set of recommendations to assess the pros and cons of the use of big data in a specific empirical nowcasting context.
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