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The importance of principal components in studying mineral prices using vector autoregressive models: evidence from the Brazilian economy

2019-08Journal article Restricted access
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dc.contributor.authorRamser, Claudia Aline de Souza
dc.contributor.authorSouza, Adriano Mendonça
dc.contributor.authorSouza, F. M.
dc.contributor.authorda Veiga, Claudimar Pereira
dc.contributor.authorda Silva, Wesley Vieira
dc.date.accessioned2024-01-09T12:02:55Z
dc.date.available2024-01-09T12:02:55Z
dc.date.issued2019-08
dc.date.updated2024-01-08T19:45:05Z
dc.description.abstracthis study examines the impact of the main Brazilian mineral commodity prices negotiated in trade balance using vector autoregressive models (VAR) in the Brazilian economy in a short-term period. VAR models were applied to the full original data and then to the data dimensionality reduced by principal components denoted by PC-VAR (principal component - vector autoregressive). In the study cases, Cholesky decomposition impulse response and variance decomposition were performed and compared in terms of short run co-movements to identify the most effective model. The applied PC-VAR methodology led to a significant reduction of variables, and similar co-movements were obtained in the short-term period when an impulse response was applied and compared to an unrestricted vector autoregressive. The proposed method also identified the most important variables that affect the other variables in the Brazilian economy and have the same co-movements.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationRamser, C. A., Souza, A. M., Souza, F. M., Veiga, C. P. & Silva, W. V. (2019). The importance of principal components in studying mineral prices using vector autoregressive models: Evidence from the Brazilian economy. Resources Policy, 62, 9-21pt_PT
dc.identifier.doi10.1016/j.resourpol.2019.03.001pt_PT
dc.identifier.issn0301-4207
dc.identifier.slugcv-prod-486210
dc.identifier.urihttp://hdl.handle.net/10400.26/48758
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/abs/pii/S0301420718305397pt_PT
dc.subjectMultivariate statisticspt_PT
dc.subjectBrazilian economypt_PT
dc.subjectPrice analysispt_PT
dc.subjectMineral economicspt_PT
dc.subjectMineral resourcespt_PT
dc.titleThe importance of principal components in studying mineral prices using vector autoregressive models: evidence from the Brazilian economypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage21pt_PT
oaire.citation.startPage9pt_PT
oaire.citation.titleResources Policypt_PT
oaire.citation.volume62pt_PT
person.familyNameMendonça Souza
person.givenNameFrancisca
person.identifier.ciencia-idDD15-B860-0C26
person.identifier.orcid0000-0003-3011-0086
rcaap.cv.cienciaidDD15-B860-0C26 | Francisca Mendonça Souza
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationc21c2cb7-fd5c-4e64-b44b-8be82785102e
relation.isAuthorOfPublication.latestForDiscoveryc21c2cb7-fd5c-4e64-b44b-8be82785102e

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