Accessing the impact of COVID-19 on the Portuguese unemployment rate

Detalhes bibliográficos
Autor(a) principal: Miguel, Diogo Queiroz
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/152363
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
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spelling Accessing the impact of COVID-19 on the Portuguese unemployment rateCOVID-19unemploymentvector autoregressive modelsforecastingDissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceWe analyze the possibility of Vector Autoregressive models being good estimators for the unemployment rate in Portugal, by studying their ability to understand the impact the COVID-19 pandemic had on the unemployment rate. We make use of Bayesen Stochastic Search Variable Selection and bootstrapping techniques for forecasting, comparing the results of these models with two benchmark techniques, ARIMA and Artificial Neural Networks. The model performance is tested through the RMSE, MSE and MAE of the estimations, and we compare the forecasting quality through a Diebold-Mariano test. We conclude that the VAR methodology can provide better forecasts than the benchmark models when combined with the Bayesian approach, both for shorter and longer forecasting horizons. We also conclude that COVID-19 did not provide the expected shock to the Portuguese unemployment rate.Coelho, Pedro Miguel Pereira SimõesDamásio, Bruno Miguel PintoRUNMiguel, Diogo Queiroz2023-05-03T17:06:54Z2023-04-142023-04-14T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/152363TID:203275667enginfo: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:RCAAP2024-03-11T05:34:43Zoai:run.unl.pt:10362/152363Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:53.287542Repositório 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 Accessing the impact of COVID-19 on the Portuguese unemployment rate
title Accessing the impact of COVID-19 on the Portuguese unemployment rate
spellingShingle Accessing the impact of COVID-19 on the Portuguese unemployment rate
Miguel, Diogo Queiroz
COVID-19
unemployment
vector autoregressive models
forecasting
title_short Accessing the impact of COVID-19 on the Portuguese unemployment rate
title_full Accessing the impact of COVID-19 on the Portuguese unemployment rate
title_fullStr Accessing the impact of COVID-19 on the Portuguese unemployment rate
title_full_unstemmed Accessing the impact of COVID-19 on the Portuguese unemployment rate
title_sort Accessing the impact of COVID-19 on the Portuguese unemployment rate
author Miguel, Diogo Queiroz
author_facet Miguel, Diogo Queiroz
author_role author
dc.contributor.none.fl_str_mv Coelho, Pedro Miguel Pereira Simões
Damásio, Bruno Miguel Pinto
RUN
dc.contributor.author.fl_str_mv Miguel, Diogo Queiroz
dc.subject.por.fl_str_mv COVID-19
unemployment
vector autoregressive models
forecasting
topic COVID-19
unemployment
vector autoregressive models
forecasting
description Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
publishDate 2023
dc.date.none.fl_str_mv 2023-05-03T17:06:54Z
2023-04-14
2023-04-14T00:00:00Z
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/10362/152363
TID:203275667
url http://hdl.handle.net/10362/152363
identifier_str_mv TID:203275667
dc.language.iso.fl_str_mv eng
language eng
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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
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