Author: Hurwitz, Evan; Cevora, George
Title: Forecasting performance of workforce reskilling programmes Cord-id: 44662bxq Document date: 2021_7_21
ID: 44662bxq
Snippet: Estimating success rates for programmes aiming to reintegrate theunemployed into the workforce is essential for good stewardship of publicfinances. At the current moment, the methods used for this task arebased on the historical performance of comparable programmes. In lightof Brexit and Covid-19 simultaneously causing a shock to the labourmarket in the UK we developed an estimation method that is basedon fundamental factors involved - workforce demand and supply - asopposed to the historical va
Document: Estimating success rates for programmes aiming to reintegrate theunemployed into the workforce is essential for good stewardship of publicfinances. At the current moment, the methods used for this task arebased on the historical performance of comparable programmes. In lightof Brexit and Covid-19 simultaneously causing a shock to the labourmarket in the UK we developed an estimation method that is basedon fundamental factors involved - workforce demand and supply - asopposed to the historical values which are quickly becoming irrelevant.With an average error of 3.9% of the re-integration success rate, ourmodel outperforms the best benchmark known to us by 53%
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