Beyond Econometrics: Using Google Trends and Social Media Data to Forecast Unemployment - OECD analysis of accuracy gains and robustness of predictions

Detalhes bibliográficos
Autor(a) principal: Castro, Pedro Sancho Vivas de
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/10362/152357
Resumo: Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
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spelling Beyond Econometrics: Using Google Trends and Social Media Data to Forecast Unemployment - OECD analysis of accuracy gains and robustness of predictionsGoogle TrendsUnemploymentTime series forecastingInformation gapsDissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsGoogle Trends has been used for less than two decades in academia to forecast outcomes, using various techniques. While most research has focused on developed countries, there are clear information gaps that have not been fully addressed. Previous studies in this field indicate that non-linear algorithms with feature set selection while using a large set of queries can yield better results across more countries. However, it is unlikely that these methods will be widely and rapidly adopted given the skills required. Therefore, the objective of this research is to explore whether the abundance of digital data sources, specifically Google searches, can aid agents as institutions and policy makers in their modeling efforts. The aim is to fill the gap in analysis for less influential countries and explore whether the use of Google searches data can be extended to multiple countries using a simple and agile methodology based on a widely used statistics-based modeling approach (ARIMAX). For this use we selected unemployment rate as the variable of interest. However, our findings show that only 30% of countries had promising results using Google-augmented ARIMAs. Thus, more computationally intensive empirical strategies would be needed to extract more predictive power out of Google queries information pool for unemployment rate modelling.Damásio, Bruno Miguel PintoRUNCastro, Pedro Sancho Vivas de2023-05-03T15:04:49Z2023-04-142023-04-14T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/152357TID:203275055enginfo: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:RCAAP2024-03-11T05:34:42Zoai:run.unl.pt:10362/152357Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:53.012589Repositório 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 Beyond Econometrics: Using Google Trends and Social Media Data to Forecast Unemployment - OECD analysis of accuracy gains and robustness of predictions
title Beyond Econometrics: Using Google Trends and Social Media Data to Forecast Unemployment - OECD analysis of accuracy gains and robustness of predictions
spellingShingle Beyond Econometrics: Using Google Trends and Social Media Data to Forecast Unemployment - OECD analysis of accuracy gains and robustness of predictions
Castro, Pedro Sancho Vivas de
Google Trends
Unemployment
Time series forecasting
Information gaps
title_short Beyond Econometrics: Using Google Trends and Social Media Data to Forecast Unemployment - OECD analysis of accuracy gains and robustness of predictions
title_full Beyond Econometrics: Using Google Trends and Social Media Data to Forecast Unemployment - OECD analysis of accuracy gains and robustness of predictions
title_fullStr Beyond Econometrics: Using Google Trends and Social Media Data to Forecast Unemployment - OECD analysis of accuracy gains and robustness of predictions
title_full_unstemmed Beyond Econometrics: Using Google Trends and Social Media Data to Forecast Unemployment - OECD analysis of accuracy gains and robustness of predictions
title_sort Beyond Econometrics: Using Google Trends and Social Media Data to Forecast Unemployment - OECD analysis of accuracy gains and robustness of predictions
author Castro, Pedro Sancho Vivas de
author_facet Castro, Pedro Sancho Vivas de
author_role author
dc.contributor.none.fl_str_mv Damásio, Bruno Miguel Pinto
RUN
dc.contributor.author.fl_str_mv Castro, Pedro Sancho Vivas de
dc.subject.por.fl_str_mv Google Trends
Unemployment
Time series forecasting
Information gaps
topic Google Trends
Unemployment
Time series forecasting
Information gaps
description Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
publishDate 2023
dc.date.none.fl_str_mv 2023-05-03T15:04:49Z
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/10362/152357
TID:203275055
url http://hdl.handle.net/10362/152357
identifier_str_mv TID:203275055
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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institution RCAAP
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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
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