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Publicação
(Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreak
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Autores
Orientador(es)
Resumo(s)
This paper aims to investigate and understand the drivers of unemployment rates in OECD Nations during the COVID-19 Outbreak and the associated measures and events. Previous research on unemployment models was consulted in order to consolidate a diverse list of possible explanatory variables for modelling unemployment rates. We further assess whether technology or healthcare availability impact said figures, particularly with lockdown measures imposed and a large amount of operations having shifted online. The model identified to best describe unemployment rates was the auto-regressive 2-factor model whilst a multiple linear regression was used to attain more interpretable insights. The proportion of a population in self employment as well as the availability of hospital beds appear to be the most influential factors as opposed to other more conventional factors during this pandemic environment.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
Palavras-chave
Unemployment Employment COVID-19 Technology