Strong policy actions have dampened the impact of Covid-19 on workers and businesses. Amid a rapid recovery, dents to potential output are set to remain limited and transitory. But many uncertainties persist and some economic scarring from the pandemic may only emerge over the coming years. This column summarises the insights from a recent conference on the implications of
Economic Bulletin Issue 5, 2021 ecb.europa.eu - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from ecb.europa.eu Daily Mail and Mail on Sunday newspapers.
Using machine learning and big data to analyse the business cycle
Prepared by Dominik Hirschbühl, Luca Onorante and Lorena Saiz
1 Introduction
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.