IFS-STICERD Public Economics Seminar
Predicting Long-term Unemployment Risk
Johannes Spinnewijn (LSE & CEP), joint with Andreas Mueller
Wednesday 08 June 2022 12:30 - 13:30
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About this event
This paper uses rich administrative and survey data from Sweden to study the predictability and determinants of long-term unemployment (LTU) over the period 1992-2016. We use standard machine learning techniques to predict job seekers' LTU risk and find substantial predictable heterogeneity. Compared to a model using standard socio-demographic variables, a comprehensive model that uses data on income, employment, and benefit histories more than doubles the predictive power. The estimated heterogeneity in LTU risk implies that at least two thirds of the observed duration dependence in job finding is driven by dynamic selection. We apply our prediction algorithm over the business cycle and find significant heterogeneity underlying the cyclicality in average LTU risk, while the role of composition effects is limited. We evaluate the implied value of targeting unemployment policies and how this changes over the business cycle.
This seminar series is jointly organized by the IFS and STICERD.
IFS-STICERD Public Economics seminars are held on Wednesdays in term time at 16:30-17:30 ONLINE or at 12.30-12.45 IN PERSON at the IFS.
Seminar organisers: Stuart Adam (IFS), Monica Costa Dias (IFS), Xavier Jaravel (LSE), Camille Landais (LSE), Attila Lindner (UCL), Joana Naritomi (LSE), and Johannes Spinnewijn (LSE).
For further information please contact Lubala Chibwe, either by email: email@example.com.
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