Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária

Detalhes bibliográficos
Autor(a) principal: Saúde, Arthur Moreira
Data de Publicação: 2017
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: http://hdl.handle.net/10438/18221
Resumo: This paper aims to create an econometric model capable of anticipating recessions in the United States economy, one year in advance, using not only monetary market variables that are already used by economists, but also capital market variables. Using a data span from 1959 to 2016, it was observed that the yield spread continues to be an explanatory variable with excellent predictive power over recessions. Evidence has also emerged of new variables that have very high statistical significance, and which offer valuable contributions to the regressions. Out-of-sample tests have been conducted which suggest that past recessions would have been predicted with substantially higher accuracy if the proposed Probit model had been used instead of the most widespread model in the economic literature. This accuracy is evident not only in the predictive quality, but also in the reduction of the number of false positives and false negatives in the regression, and in the robustness of the out-of-sample tests.
id FGV_ca569c2dfb704beecf16bd09da562e9c
oai_identifier_str oai:repositorio.fgv.br:10438/18221
network_acronym_str FGV
network_name_str Repositório Institucional do FGV (FGV Repositório Digital)
repository_id_str 3974
spelling Saúde, Arthur MoreiraEscolas::EPGEFGVGonçalves, Edson Daniel LopesSouza, Rafael Martins deCampos, Eduardo Lima2017-05-02T19:31:50Z2017-05-02T19:31:50Z2017-03-31SAÚDE, Arthur Moreira. Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária. Dissertação (Mestrado em Finanças e Economia Empresarial) - Escola de Pós-Graduação em Economia, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2017.http://hdl.handle.net/10438/18221This paper aims to create an econometric model capable of anticipating recessions in the United States economy, one year in advance, using not only monetary market variables that are already used by economists, but also capital market variables. Using a data span from 1959 to 2016, it was observed that the yield spread continues to be an explanatory variable with excellent predictive power over recessions. Evidence has also emerged of new variables that have very high statistical significance, and which offer valuable contributions to the regressions. Out-of-sample tests have been conducted which suggest that past recessions would have been predicted with substantially higher accuracy if the proposed Probit model had been used instead of the most widespread model in the economic literature. This accuracy is evident not only in the predictive quality, but also in the reduction of the number of false positives and false negatives in the regression, and in the robustness of the out-of-sample tests.Este trabalho visa desenvolver um modelo econométrico capaz de antecipar, com um ano de antecedência, recessões na economia dos Estados Unidos, utilizando não só variáveis dos mercados monetários, que já são indicadores antecedentes bastante utilizados por economistas, mas também dos mercados de capitais. Utilizando-se dados de 1959 a 2016, pode-se observar que o spread de juros de longo e curto prazo continua sendo uma variável explicativa com excelente poder preditivo sobre recessões. Também surgiram evidências de novas variáveis que possuem altíssimas significâncias estatísticas, e que oferecem valiosas contribuições para as regressões. Foram conduzidos testes fora da amostra que sugerem que as recessões passadas teriam sido previstas com acurácia substancialmente superior, caso o modelo Probit proposto tivesse sido utilizado no lugar do modelo mais difundido na literatura econômica. Essa acurácia é evidente não só na qualidade preditiva, mas também na redução do número de falsos positivos e falsos negativos da regressão, e na robustez dos testes fora da amostra.porRecessionsEconomic cyclesEconometricsBinary response modelsRecessõesCiclos econômicosEconometriaModelos de resposta bináriaProbitLogitEconomiaRecessão (Economia)Ciclos econômicosModelos econométricosProbitLogitMetodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta bináriainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVinfo:eu-repo/semantics/openAccessTEXTDissertacao Final.pdf.txtDissertacao Final.pdf.txtExtracted texttext/plain41237https://repositorio.fgv.br/bitstreams/8b782354-db48-4ab8-b456-4ff94775242d/download1a943bf7f469f6a9506aa75214528d24MD57ORIGINALDissertacao Final.pdfDissertacao Final.pdfDissertaçãoapplication/pdf947767https://repositorio.fgv.br/bitstreams/be1e3c38-eddf-4c74-967f-f64a1099da2e/downloadca50219ab757930a6d88422c06d48234MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-84707https://repositorio.fgv.br/bitstreams/b32502d1-dbf8-4d25-8397-9633c63236ba/downloaddfb340242cced38a6cca06c627998fa1MD52THUMBNAILDissertacao Final.pdf.jpgDissertacao Final.pdf.jpgGenerated Thumbnailimage/jpeg3184https://repositorio.fgv.br/bitstreams/d08d32cc-edca-4d3e-9d80-0c0e49d27bed/downloadc2b9336cd10cffe5af8c0ef1422f7ac7MD5810438/182212023-11-09 05:08:41.348open.accessoai:repositorio.fgv.br:10438/18221https://repositorio.fgv.brRepositório InstitucionalPRIhttp://bibliotecadigital.fgv.br/dspace-oai/requestopendoar:39742023-11-09T05:08:41Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV)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
dc.title.por.fl_str_mv Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária
title Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária
spellingShingle Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária
Saúde, Arthur Moreira
Recessions
Economic cycles
Econometrics
Binary response models
Recessões
Ciclos econômicos
Econometria
Modelos de resposta binária
Probit
Logit
Economia
Recessão (Economia)
Ciclos econômicos
Modelos econométricos
Probit
Logit
title_short Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária
title_full Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária
title_fullStr Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária
title_full_unstemmed Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária
title_sort Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária
author Saúde, Arthur Moreira
author_facet Saúde, Arthur Moreira
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EPGE
dc.contributor.affiliation.none.fl_str_mv FGV
dc.contributor.member.none.fl_str_mv Gonçalves, Edson Daniel Lopes
Souza, Rafael Martins de
dc.contributor.author.fl_str_mv Saúde, Arthur Moreira
dc.contributor.advisor1.fl_str_mv Campos, Eduardo Lima
contributor_str_mv Campos, Eduardo Lima
dc.subject.eng.fl_str_mv Recessions
Economic cycles
Econometrics
Binary response models
topic Recessions
Economic cycles
Econometrics
Binary response models
Recessões
Ciclos econômicos
Econometria
Modelos de resposta binária
Probit
Logit
Economia
Recessão (Economia)
Ciclos econômicos
Modelos econométricos
Probit
Logit
dc.subject.por.fl_str_mv Recessões
Ciclos econômicos
Econometria
Modelos de resposta binária
Probit
Logit
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Recessão (Economia)
Ciclos econômicos
Modelos econométricos
Probit
Logit
description This paper aims to create an econometric model capable of anticipating recessions in the United States economy, one year in advance, using not only monetary market variables that are already used by economists, but also capital market variables. Using a data span from 1959 to 2016, it was observed that the yield spread continues to be an explanatory variable with excellent predictive power over recessions. Evidence has also emerged of new variables that have very high statistical significance, and which offer valuable contributions to the regressions. Out-of-sample tests have been conducted which suggest that past recessions would have been predicted with substantially higher accuracy if the proposed Probit model had been used instead of the most widespread model in the economic literature. This accuracy is evident not only in the predictive quality, but also in the reduction of the number of false positives and false negatives in the regression, and in the robustness of the out-of-sample tests.
publishDate 2017
dc.date.accessioned.fl_str_mv 2017-05-02T19:31:50Z
dc.date.available.fl_str_mv 2017-05-02T19:31:50Z
dc.date.issued.fl_str_mv 2017-03-31
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.citation.fl_str_mv SAÚDE, Arthur Moreira. Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária. Dissertação (Mestrado em Finanças e Economia Empresarial) - Escola de Pós-Graduação em Economia, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2017.
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10438/18221
identifier_str_mv SAÚDE, Arthur Moreira. Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária. Dissertação (Mestrado em Finanças e Economia Empresarial) - Escola de Pós-Graduação em Economia, Fundação Getúlio Vargas - FGV, Rio de Janeiro, 2017.
url http://hdl.handle.net/10438/18221
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.source.none.fl_str_mv reponame:Repositório Institucional do FGV (FGV Repositório Digital)
instname:Fundação Getulio Vargas (FGV)
instacron:FGV
instname_str Fundação Getulio Vargas (FGV)
instacron_str FGV
institution FGV
reponame_str Repositório Institucional do FGV (FGV Repositório Digital)
collection Repositório Institucional do FGV (FGV Repositório Digital)
bitstream.url.fl_str_mv https://repositorio.fgv.br/bitstreams/8b782354-db48-4ab8-b456-4ff94775242d/download
https://repositorio.fgv.br/bitstreams/be1e3c38-eddf-4c74-967f-f64a1099da2e/download
https://repositorio.fgv.br/bitstreams/b32502d1-dbf8-4d25-8397-9633c63236ba/download
https://repositorio.fgv.br/bitstreams/d08d32cc-edca-4d3e-9d80-0c0e49d27bed/download
bitstream.checksum.fl_str_mv 1a943bf7f469f6a9506aa75214528d24
ca50219ab757930a6d88422c06d48234
dfb340242cced38a6cca06c627998fa1
c2b9336cd10cffe5af8c0ef1422f7ac7
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositório Institucional do FGV (FGV Repositório Digital) - Fundação Getulio Vargas (FGV)
repository.mail.fl_str_mv
_version_ 1802749873611603968