Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UCB |
Texto Completo: | https://bdtd.ucb.br:8443/jspui/handle/tede/2645 |
Resumo: | Forecasting is an important activity that can be developed in any space whose study is associated with the environment of predicting future behavior in relation to the events of interest. The objective of this work is to find through econometric modeling the best prediction model for the series of industrial production and residential electric energy demand in Brazil, using simpler individual models used as baseline (ARIMA), multivariate (ARDL) (VAR) and forecast combination. The best model was obtained through the statistics of the errors, through the performance of accuracy. |
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Gutierrez, Carlos Enrique Carrascohttp://lattes.cnpq.br/0881893862643600http://lattes.cnpq.br/3083097288481045Pontes, Luc??lia Pontes e2019-11-07T19:07:45Z2018-12-13PONTES, Luc??lia Pontes e. Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil. 2018. 104 f. Tese (Programa Stricto Sensu em Economia de Empresas) - Universidade Cat??lica de Bras??lia, Bras??lia, 2018.https://bdtd.ucb.br:8443/jspui/handle/tede/2645Forecasting is an important activity that can be developed in any space whose study is associated with the environment of predicting future behavior in relation to the events of interest. The objective of this work is to find through econometric modeling the best prediction model for the series of industrial production and residential electric energy demand in Brazil, using simpler individual models used as baseline (ARIMA), multivariate (ARDL) (VAR) and forecast combination. The best model was obtained through the statistics of the errors, through the performance of accuracy.Realizar previs??es ?? uma atividade importante que pode ser desenvolvida em qualquer espa??o, cujo estudo esteja associado ao ambiente de prever comportamentos futuros em rela????o aos acontecimentos de interesse. O objetivo deste trabalho ?? encontrar atrav??s de estudos econom??tricos o melhor modelo de previs??o para as s??ries da produ????o industrial e da demanda de energia el??trica residencial no Brasil, utilizando-se de modelos individuais mais simples como baseline (ARIMA), multivariados ARDL, VAR e com combina????o de previs??o. O melhor modelo foi obtido atrav??s das estat??sticas dos erros, utilizando o desempenho de acur??cia, destaque para o modelo combinado por m??nimos quadrados ordin??rios OLS.Submitted by Sara Ribeiro (sara.ribeiro@ucb.br) on 2019-11-07T19:03:08Z No. of bitstreams: 1 LuceliaPontesePontesTese2018.pdf: 2207609 bytes, checksum: 5b6a278bdbd0b01391897b1682761a35 (MD5)Approved for entry into archive by Sara Ribeiro (sara.ribeiro@ucb.br) on 2019-11-07T19:07:45Z (GMT) No. of bitstreams: 1 LuceliaPontesePontesTese2018.pdf: 2207609 bytes, checksum: 5b6a278bdbd0b01391897b1682761a35 (MD5)Made available in DSpace on 2019-11-07T19:07:45Z (GMT). No. of bitstreams: 1 LuceliaPontesePontesTese2018.pdf: 2207609 bytes, checksum: 5b6a278bdbd0b01391897b1682761a35 (MD5) Previous issue date: 2018-12-13application/pdfhttps://200.214.135.178:8443/jspui/retrieve/7050/LuceliaPontesePontesTese2018.pdf.jpgporUniversidade Cat??lica de Bras??liaPrograma Stricto Sensu em Economia de EmpresasUCBBrasilEscola de Humanidades, Neg??cios e DireitoEnergia el??tricaProdu????o industrialPrevis??o de s??ries temporaisTime series forecastingCNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIAPrevis??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UCBinstname:Universidade Católica de Brasília (UCB)instacron:UCBTHUMBNAILLuceliaPontesePontesTese2018.pdf.jpgLuceliaPontesePontesTese2018.pdf.jpgimage/jpeg5450https://200.214.135.178:8443/jspui/bitstream/tede/2645/4/LuceliaPontesePontesTese2018.pdf.jpgdab8cb9442dff00ff689d0eb57db1243MD54TEXTLuceliaPontesePontesTese2018.pdf.txtLuceliaPontesePontesTese2018.pdf.txttext/plain202454https://200.214.135.178:8443/jspui/bitstream/tede/2645/3/LuceliaPontesePontesTese2018.pdf.txte3071de09f7491d63bac56d4d84029e0MD53LICENSElicense.txtlicense.txttext/plain; charset=utf-81905https://200.214.135.178:8443/jspui/bitstream/tede/2645/1/license.txt75558dcf859532757239878b42f1c2c7MD51ORIGINALLuceliaPontesePontesTese2018.pdfLuceliaPontesePontesTese2018.pdfapplication/pdf2207609https://200.214.135.178:8443/jspui/bitstream/tede/2645/2/LuceliaPontesePontesTese2018.pdf5b6a278bdbd0b01391897b1682761a35MD52tede/26452020-07-07 15:58:49.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 Digital de Teses e Dissertaçõeshttps://bdtd.ucb.br:8443/jspui/ |
dc.title.por.fl_str_mv |
Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil |
title |
Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil |
spellingShingle |
Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil Pontes, Luc??lia Pontes e Energia el??trica Produ????o industrial Previs??o de s??ries temporais Time series forecasting CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA |
title_short |
Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil |
title_full |
Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil |
title_fullStr |
Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil |
title_full_unstemmed |
Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil |
title_sort |
Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil |
author |
Pontes, Luc??lia Pontes e |
author_facet |
Pontes, Luc??lia Pontes e |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Gutierrez, Carlos Enrique Carrasco |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/0881893862643600 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/3083097288481045 |
dc.contributor.author.fl_str_mv |
Pontes, Luc??lia Pontes e |
contributor_str_mv |
Gutierrez, Carlos Enrique Carrasco |
dc.subject.por.fl_str_mv |
Energia el??trica Produ????o industrial Previs??o de s??ries temporais |
topic |
Energia el??trica Produ????o industrial Previs??o de s??ries temporais Time series forecasting CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA |
dc.subject.eng.fl_str_mv |
Time series forecasting |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA |
dc.description.abstract.eng.fl_txt_mv |
Forecasting is an important activity that can be developed in any space whose study is associated with the environment of predicting future behavior in relation to the events of interest. The objective of this work is to find through econometric modeling the best prediction model for the series of industrial production and residential electric energy demand in Brazil, using simpler individual models used as baseline (ARIMA), multivariate (ARDL) (VAR) and forecast combination. The best model was obtained through the statistics of the errors, through the performance of accuracy. |
dc.description.abstract.por.fl_txt_mv |
Realizar previs??es ?? uma atividade importante que pode ser desenvolvida em qualquer espa??o, cujo estudo esteja associado ao ambiente de prever comportamentos futuros em rela????o aos acontecimentos de interesse. O objetivo deste trabalho ?? encontrar atrav??s de estudos econom??tricos o melhor modelo de previs??o para as s??ries da produ????o industrial e da demanda de energia el??trica residencial no Brasil, utilizando-se de modelos individuais mais simples como baseline (ARIMA), multivariados ARDL, VAR e com combina????o de previs??o. O melhor modelo foi obtido atrav??s das estat??sticas dos erros, utilizando o desempenho de acur??cia, destaque para o modelo combinado por m??nimos quadrados ordin??rios OLS. |
description |
Forecasting is an important activity that can be developed in any space whose study is associated with the environment of predicting future behavior in relation to the events of interest. The objective of this work is to find through econometric modeling the best prediction model for the series of industrial production and residential electric energy demand in Brazil, using simpler individual models used as baseline (ARIMA), multivariate (ARDL) (VAR) and forecast combination. The best model was obtained through the statistics of the errors, through the performance of accuracy. |
publishDate |
2018 |
dc.date.issued.fl_str_mv |
2018-12-13 |
dc.date.accessioned.fl_str_mv |
2019-11-07T19:07:45Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
status_str |
publishedVersion |
format |
doctoralThesis |
dc.identifier.citation.fl_str_mv |
PONTES, Luc??lia Pontes e. Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil. 2018. 104 f. Tese (Programa Stricto Sensu em Economia de Empresas) - Universidade Cat??lica de Bras??lia, Bras??lia, 2018. |
dc.identifier.uri.fl_str_mv |
https://bdtd.ucb.br:8443/jspui/handle/tede/2645 |
identifier_str_mv |
PONTES, Luc??lia Pontes e. Previs??o de s??ries temporais: produ????o industrial e demanda de energia el??trica no Brasil. 2018. 104 f. Tese (Programa Stricto Sensu em Economia de Empresas) - Universidade Cat??lica de Bras??lia, Bras??lia, 2018. |
url |
https://bdtd.ucb.br:8443/jspui/handle/tede/2645 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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.publisher.none.fl_str_mv |
Universidade Cat??lica de Bras??lia |
dc.publisher.program.fl_str_mv |
Programa Stricto Sensu em Economia de Empresas |
dc.publisher.initials.fl_str_mv |
UCB |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Escola de Humanidades, Neg??cios e Direito |
publisher.none.fl_str_mv |
Universidade Cat??lica de Bras??lia |
dc.source.none.fl_str_mv |
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Biblioteca Digital de Teses e Dissertações da UCB |
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