文章基本信息

标题：Using machine learning and big data to analyse the business cycle
本地全文：下载
作者：Dominik Hirschbühl ; Luca Onorante ; Lorena Saiz 等
期刊名称：Euro Area Balance of Payments and International Investment Position Statistics
印刷版ISSN：1830-3420
电子版ISSN：1830-3439
出版年度：2021
卷号：2021
语种：English
出版社：European Central Bank
摘要：Policymakers take decisions in real time based on incomplete information about current economic conditions. Central banks and economic analysts largely rely on official statistics together with soft data and surveys, to assess the state of the economy. Although a wide range of high-quality conventional data is available, the datasets are released with lags ranging from a few days or weeks to several months after the reference period. For these reasons, central banks have been looking at ways to exploit timelier data and employ more sophisticated methods to enhance accuracy when forecasting metrics that are relevant for policymaking.