(Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreak

Detalhes bibliográficos
Autor(a) principal: Demetriades, Manuel
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/142636
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
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spelling (Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreakUnemploymentEmploymentCOVID-19TechnologyDissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced AnalyticsThis 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.Pinheiro, Flávio Luís PortasRUNDemetriades, Manuel2022-07-29T10:56:21Z2022-05-092022-05-09T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/142636TID:203045262enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-05-22T18:04:06Zoai:run.unl.pt:10362/142636Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-22T18:04:06Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv (Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreak
title (Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreak
spellingShingle (Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreak
Demetriades, Manuel
Unemployment
Employment
COVID-19
Technology
title_short (Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreak
title_full (Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreak
title_fullStr (Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreak
title_full_unstemmed (Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreak
title_sort (Un)employment in unprecedented times: Understanding unemployment during the COVID-19 outbreak
author Demetriades, Manuel
author_facet Demetriades, Manuel
author_role author
dc.contributor.none.fl_str_mv Pinheiro, Flávio Luís Portas
RUN
dc.contributor.author.fl_str_mv Demetriades, Manuel
dc.subject.por.fl_str_mv Unemployment
Employment
COVID-19
Technology
topic Unemployment
Employment
COVID-19
Technology
description Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
publishDate 2022
dc.date.none.fl_str_mv 2022-07-29T10:56:21Z
2022-05-09
2022-05-09T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/142636
TID:203045262
url http://hdl.handle.net/10362/142636
identifier_str_mv TID:203045262
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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