Hybrideseminar: Predicting Firm Exits with Machine Learning: Implications for Selection into COVID-19 Support and Productivity Growth
Dinsdag 6 december 2022 geeft Benedikt Vogt (CPB) een online presentatie getiteld: "Predicting Firm Exits with Machine Learning: Implications for Selection into COVID-19 Support and Productivity Growth" Indien u wilt deelnemen stuurt u een e-mail naar Simone Pailer (S.Pailer@cpb.nl). U wordt aangemeld bij de receptie of ontvangt een Webex-uitnodiging via Outlook. Journalisten dienen zich tevens te melden bij woordvoerder Jeannette Duin: J.E.C.Duin@cpb.nl
Evaluations of business support programs often face the problem of accurately predicting which firms leave the market. We address this problem, by first showing that a machine learning model better predicts firm exits than conventional methods. This improvement is mostly due to the use of high-dimensional firm data. Second, we provide new insights on the short-term selection effects into COVID-19 support in 2020 in the Netherlands. We find that firms with a lower predicted exit probability are more likely to use support. But because the benefits of support - as measured by prevented exits - are increasing in the probability to leave the market, we conclude that COVID-19 support also reduced the cleansing mechanism of economic crises but less than previously thought.
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