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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.

New yorkUnited statesJulian ashwinEleni kalamaraVasco botelhoAgostino consoloDominik hirschbLorena saizLuca onoranteGerman institute for employment researchFederal reserve bankEuropean commissionFinancial affairsSpanish ministry of inclusionDeutsche bundesbankItalian national institute for social security