Predicting the growth of industrial production: an analysis from the demand for electric energy in the state of Ceara

Detalhes bibliográficos
Autor(a) principal: Silvia Fernanda Oliveira
Data de Publicação: 2011
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações da UFC
Texto Completo: http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7387
Resumo: The timeliness with which economic agents make their decisions encourages the development of tools in order to anticipate changes in economic aggregates. Following this, the study analyses and develops models to forecast the industrial production from Cearà energy consumption measured by COELCE. Vector Autoregressive models (VAR) are estimated and scenarios are constructed for the period 2011-2012. The estimates were robust and the simulations indicated an increase of 3.9% in industrial production Cearà until 2012, comparing with the values observed in 2010, without seasonal effects.
id UFC_1d5f921624497e1eafc9bb7ae486380a
oai_identifier_str oai:www.teses.ufc.br:5295
network_acronym_str UFC
network_name_str Biblioteca Digital de Teses e Dissertações da UFC
spelling info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisPredicting the growth of industrial production: an analysis from the demand for electric energy in the state of CearaPrevendo o crescimento da produÃÃo industrial: uma anÃlise a partir da demanda de energia eletrica no Estado do CearÃ2011-02-28Andrei Gomes Simonassi00000060068http://lattes.cnpq.br/8542940399953204 FabrÃcio Carneiro Linhares45504849349http://lattes.cnpq.br/8577355400988841Paulo RogÃrio Faustino Matos00000000084http://lattes.cnpq.br/028852240010996225421436565http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4385777J4Silvia Fernanda OliveiraUniversidade Federal do CearÃPrograma de PÃs-GraduaÃÃo em Economia - CAENUFCBRPrevisÃo ProduÃÃo Industrial Consumo de Energia ElÃtricaForecasting Industrial Production Energy ConsumptionCIENCIAS SOCIAIS APLICADASThe timeliness with which economic agents make their decisions encourages the development of tools in order to anticipate changes in economic aggregates. Following this, the study analyses and develops models to forecast the industrial production from Cearà energy consumption measured by COELCE. Vector Autoregressive models (VAR) are estimated and scenarios are constructed for the period 2011-2012. The estimates were robust and the simulations indicated an increase of 3.9% in industrial production Cearà until 2012, comparing with the values observed in 2010, without seasonal effects.A tempestividade com a qual os agentes econÃmicos tomam suas decisÃes estimula o desenvolvimento de ferramentas que permitam antecipar as mudanÃas nos agregados econÃmicos. Deste modo, o estudo realiza uma anÃlise e previsÃo da produÃÃo industrial cearense a partir do consumo de energia elÃtrica mensurado pela COELCE. Modelos Vetoriais Auto-regressivos (VAR) sÃo estimados e cenÃrios sÃo construÃdos para o perÃodo 2011-2012. As estimativas se mostraram robustas com um elevado poder de explicaÃÃo do modelo e as simulaÃÃes indicaram um crescimento de 3,9% da produÃÃo industrial cearense atà 2012 com base no valor verificado em 2010, jà desconsiderando as influÃncias sazonais.http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7387application/pdfinfo:eu-repo/semantics/openAccessporreponame:Biblioteca Digital de Teses e Dissertações da UFCinstname:Universidade Federal do Cearáinstacron:UFC2019-01-21T11:20:25Zmail@mail.com -
dc.title.en.fl_str_mv Predicting the growth of industrial production: an analysis from the demand for electric energy in the state of Ceara
dc.title.alternative.pt.fl_str_mv Prevendo o crescimento da produÃÃo industrial: uma anÃlise a partir da demanda de energia eletrica no Estado do CearÃ
title Predicting the growth of industrial production: an analysis from the demand for electric energy in the state of Ceara
spellingShingle Predicting the growth of industrial production: an analysis from the demand for electric energy in the state of Ceara
Silvia Fernanda Oliveira
PrevisÃo
ProduÃÃo Industrial
Consumo de Energia ElÃtrica
Forecasting
Industrial Production
Energy Consumption
CIENCIAS SOCIAIS APLICADAS
title_short Predicting the growth of industrial production: an analysis from the demand for electric energy in the state of Ceara
title_full Predicting the growth of industrial production: an analysis from the demand for electric energy in the state of Ceara
title_fullStr Predicting the growth of industrial production: an analysis from the demand for electric energy in the state of Ceara
title_full_unstemmed Predicting the growth of industrial production: an analysis from the demand for electric energy in the state of Ceara
title_sort Predicting the growth of industrial production: an analysis from the demand for electric energy in the state of Ceara
author Silvia Fernanda Oliveira
author_facet Silvia Fernanda Oliveira
author_role author
dc.contributor.advisor1.fl_str_mv Andrei Gomes Simonassi
dc.contributor.advisor1ID.fl_str_mv 00000060068
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/8542940399953204
dc.contributor.referee1.fl_str_mv FabrÃcio Carneiro Linhares
dc.contributor.referee1ID.fl_str_mv 45504849349
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/8577355400988841
dc.contributor.referee2.fl_str_mv Paulo RogÃrio Faustino Matos
dc.contributor.referee2ID.fl_str_mv 00000000084
dc.contributor.referee2Lattes.fl_str_mv http://lattes.cnpq.br/0288522400109962
dc.contributor.authorID.fl_str_mv 25421436565
dc.contributor.authorLattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4385777J4
dc.contributor.author.fl_str_mv Silvia Fernanda Oliveira
contributor_str_mv Andrei Gomes Simonassi
FabrÃcio Carneiro Linhares
Paulo RogÃrio Faustino Matos
dc.subject.por.fl_str_mv PrevisÃo
ProduÃÃo Industrial
Consumo de Energia ElÃtrica
topic PrevisÃo
ProduÃÃo Industrial
Consumo de Energia ElÃtrica
Forecasting
Industrial Production
Energy Consumption
CIENCIAS SOCIAIS APLICADAS
dc.subject.eng.fl_str_mv Forecasting
Industrial Production
Energy Consumption
dc.subject.cnpq.fl_str_mv CIENCIAS SOCIAIS APLICADAS
dc.description.abstract.por.fl_txt_mv The timeliness with which economic agents make their decisions encourages the development of tools in order to anticipate changes in economic aggregates. Following this, the study analyses and develops models to forecast the industrial production from Cearà energy consumption measured by COELCE. Vector Autoregressive models (VAR) are estimated and scenarios are constructed for the period 2011-2012. The estimates were robust and the simulations indicated an increase of 3.9% in industrial production Cearà until 2012, comparing with the values observed in 2010, without seasonal effects.
A tempestividade com a qual os agentes econÃmicos tomam suas decisÃes estimula o desenvolvimento de ferramentas que permitam antecipar as mudanÃas nos agregados econÃmicos. Deste modo, o estudo realiza uma anÃlise e previsÃo da produÃÃo industrial cearense a partir do consumo de energia elÃtrica mensurado pela COELCE. Modelos Vetoriais Auto-regressivos (VAR) sÃo estimados e cenÃrios sÃo construÃdos para o perÃodo 2011-2012. As estimativas se mostraram robustas com um elevado poder de explicaÃÃo do modelo e as simulaÃÃes indicaram um crescimento de 3,9% da produÃÃo industrial cearense atà 2012 com base no valor verificado em 2010, jà desconsiderando as influÃncias sazonais.
description The timeliness with which economic agents make their decisions encourages the development of tools in order to anticipate changes in economic aggregates. Following this, the study analyses and develops models to forecast the industrial production from Cearà energy consumption measured by COELCE. Vector Autoregressive models (VAR) are estimated and scenarios are constructed for the period 2011-2012. The estimates were robust and the simulations indicated an increase of 3.9% in industrial production Cearà until 2012, comparing with the values observed in 2010, without seasonal effects.
publishDate 2011
dc.date.issued.fl_str_mv 2011-02-28
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
status_str publishedVersion
format masterThesis
dc.identifier.uri.fl_str_mv http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7387
url http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7387
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 Federal do CearÃ
dc.publisher.program.fl_str_mv Programa de PÃs-GraduaÃÃo em Economia - CAEN
dc.publisher.initials.fl_str_mv UFC
dc.publisher.country.fl_str_mv BR
publisher.none.fl_str_mv Universidade Federal do CearÃ
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações da UFC
instname:Universidade Federal do Ceará
instacron:UFC
reponame_str Biblioteca Digital de Teses e Dissertações da UFC
collection Biblioteca Digital de Teses e Dissertações da UFC
instname_str Universidade Federal do Ceará
instacron_str UFC
institution UFC
repository.name.fl_str_mv -
repository.mail.fl_str_mv mail@mail.com
_version_ 1643295156875558912

Registros relacionados