This development is in line with a broader expectation among governments to conduct evidence-based policy making, to prevent prolonged spells of joblessness, and to tailor services to individuals. One example is the Flemish Employment and Vocational Training Office which has had the opportunity to develop statistical profiling models using modern, data-hungry, and computationally expensive machine learning techniques. These machine learning techniques are better at predicting which jobseekers are at risk of becoming long-term unemployed or of exhausting their benefits than standard regression models.
Understanding job search is crucial to forming a complete picture of this extraordinary economic event and could provide valuable insights for economic policy making in future pandemic-induced recessions.
The consequences of the global coronavirus for mental health have been dire, particularly for adolescents and young adults, who have faced large disruptions to their education and living situations and may suffer lifelong economic impacts.
The Covid-19 crisis had important impacts on people’s income-inequality preferences and health-inequality preferences, but the effects differ depending on the characteristics and experiences of risk in the household.
The jobless benefit claim numbers began climbing rapidly during the week of March 14, 2020 and, according to data from the Labor Department, more than 24 million people ended up applying over the next month, with millions more the following weeks.