Analyzing Brazilian markets using the Global VAR & IIS Approach

Detalhes bibliográficos
Autor(a) principal: Barbosa, Bruno Tebaldi de Queiroz
Data de Publicação: 2022
Tipo de documento: Tese
Idioma: eng
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: https://hdl.handle.net/10438/32256
Resumo: This thesis consists of three chapters. The chapters can be read separately, ie there is no predetermined reading order. However, the suggested order follows a linear evolution of the theme. This work expands the work of Barbosa (2017), in his study the author establishes a model for the Brazilian market taking into account the interdependencies between regions using the Global VAR (GVAR) methodology, and uses this model to estimate the elasticity of regional employment in relation to the country’s economic activity. In this study we expand the Barbosa (2017) model on several fronts. First, the study addresses the use of different weight matrices. Traditionally, the weight matrix used in the literature is based on trade weights and bilateral trade between two countries. Barbosa (2017) proposes a weight matrix based on connections between regions, this study in its turn expands these weight matrix allowing the weight matrix to be based not only on connections between regions but also on macroeconomic variables of each region such as GDP, GDP per capita and population. A second innovation is made with the proposal of a new econometric model. This new econometric model is built from the Global VAR model, which is expanded through a saturation with impulse indicators (henceforth called GVAR-IIS). It is worth mentioning that the hypothesis of weak exogeneity remains a requirement for the validity of the GVAR-IIS. For validation of weak exogeneity, the study applies not only the classical tests of weak exogeneity proposed by Granger and Lin (1995) but expands the tests by applying the concept of separability proposed by Hecq et al. (2002). The first part of the study analyzes the original model proposed by Barbosa (2017) using a weight matrix based on connections between cities. The database is expanded to include the period of forecasts that took place between 2016 and 2018. In this chapter we assess how the forecasts behave in the face of the scenario, we also assess the resilience of the regions and the heterogeneity of the responses. In the second part, the GVAR model proposed by Barbosa (2017) is saturated with impulse indicators, this new model is referred as GVAR-IIS. The chapter proposes an estimation procedure for the GVARIIS. The Chapter also presents an empirical exercise in which the new GVAR-IIS model is evaluated together with other models to assess its predictive power. To validate the hypotheses of weak exogeneity, the classical tests proposed by Granger and Lin (1995) are carried out, in which an innovation is the use of the concept of separability proposed by Hecq et al. (2002) to validate the hypothesis of weak exogeneity. Finally, in the third part, the GVAR-IIS model developed in the previous chapter is used together with a weight.
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spelling Barbosa, Bruno Tebaldi de QueirozEscolas::EESPMarçal, EmersonMaciente, Aguinaldo NogueiraPrince, DiogoLaurini, Márcio PolettiPereira, Pedro L. Valls2022-07-19T15:09:24Z2022-07-19T15:09:24Z2022-07-08https://hdl.handle.net/10438/32256This thesis consists of three chapters. The chapters can be read separately, ie there is no predetermined reading order. However, the suggested order follows a linear evolution of the theme. This work expands the work of Barbosa (2017), in his study the author establishes a model for the Brazilian market taking into account the interdependencies between regions using the Global VAR (GVAR) methodology, and uses this model to estimate the elasticity of regional employment in relation to the country’s economic activity. In this study we expand the Barbosa (2017) model on several fronts. First, the study addresses the use of different weight matrices. Traditionally, the weight matrix used in the literature is based on trade weights and bilateral trade between two countries. Barbosa (2017) proposes a weight matrix based on connections between regions, this study in its turn expands these weight matrix allowing the weight matrix to be based not only on connections between regions but also on macroeconomic variables of each region such as GDP, GDP per capita and population. A second innovation is made with the proposal of a new econometric model. This new econometric model is built from the Global VAR model, which is expanded through a saturation with impulse indicators (henceforth called GVAR-IIS). It is worth mentioning that the hypothesis of weak exogeneity remains a requirement for the validity of the GVAR-IIS. For validation of weak exogeneity, the study applies not only the classical tests of weak exogeneity proposed by Granger and Lin (1995) but expands the tests by applying the concept of separability proposed by Hecq et al. (2002). The first part of the study analyzes the original model proposed by Barbosa (2017) using a weight matrix based on connections between cities. The database is expanded to include the period of forecasts that took place between 2016 and 2018. In this chapter we assess how the forecasts behave in the face of the scenario, we also assess the resilience of the regions and the heterogeneity of the responses. In the second part, the GVAR model proposed by Barbosa (2017) is saturated with impulse indicators, this new model is referred as GVAR-IIS. The chapter proposes an estimation procedure for the GVARIIS. The Chapter also presents an empirical exercise in which the new GVAR-IIS model is evaluated together with other models to assess its predictive power. To validate the hypotheses of weak exogeneity, the classical tests proposed by Granger and Lin (1995) are carried out, in which an innovation is the use of the concept of separability proposed by Hecq et al. (2002) to validate the hypothesis of weak exogeneity. Finally, in the third part, the GVAR-IIS model developed in the previous chapter is used together with a weight.Este trabalho utiliza um modelo para o mercado Brasileiro levando em conta as interdependências entre as regiões utilizando a metodologia do Global VAR (GVAR), o estudo é dividido em 3 partes. A primeira parte do estudo analisa o modelo original proposto por (Barbosa, 2017) utilizando uma matriz de peso baseada nas conexões entre cidades. A base de dados é expandida para contemplar o período de previsões ocorridas entre 2016 e 2018. Neste capitulo avaliamos como as previsões se comportam frente ao cenário ocorrido bem como avaliamos a resiliência das regiões e a heterogeneidade das respostas. Na segunda parte, o modelo GVAR é saturado com a indicadoras de impulso, sendo este novo modelo referenciado como GVAR-IIS. O capitulo propõe um procedimento de estimação para o GVAR-IIS. O Capitulo apresenta também um exercício empírico no qual o novo modelo GVAR-IIS é avaliado juntamente com outros modelos para avaliação do seu poder preditivo. Para validação das hipóteses de exogeneidade fraca é realizado os testes clássicos propostos por Granger (1995), em sendo que uma inovação é a utilização do conceito de separabilidade proposto por Hecq (2002) para validação da hipóteses de exogeneidade fraca. Por fim, na terceira parte, o modelo GVAR-IIS desenvolvido no capitulo anterior é utilizado juntamente com uma matriz de pesos baseado na conexões entre cidades ponderada com informações do PIB per-capta. O capitulo avalia a performance de previsão do modelo GVAR-IIS, juntamente com a matriz de conexões, em um cenário de especificação incorreta.engMacroeconomicGlobal VARGVARMacroeconomiaEconomiaEconomia - BrasilModelos econométricosMacroeconomiaMercado de trabalho - BrasilAnalyzing Brazilian markets using the Global VAR & IIS Approachinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVLICENSElicense.txtlicense.txttext/plain; charset=utf-84707https://repositorio.fgv.br/bitstreams/20d793d7-3283-4e51-b56f-33dbc09bf8ed/downloaddfb340242cced38a6cca06c627998fa1MD54ORIGINALTese___All_Caps_vf.pdfTese___All_Caps_vf.pdfPDFapplication/pdf8106327https://repositorio.fgv.br/bitstreams/fc02219b-593b-4938-9b3a-cc9629164b81/download15dd35e98a95bbb009ce5c10892259c6MD53TEXTTese___All_Caps_vf.pdf.txtTese___All_Caps_vf.pdf.txtExtracted 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dc.title.eng.fl_str_mv Analyzing Brazilian markets using the Global VAR & IIS Approach
title Analyzing Brazilian markets using the Global VAR & IIS Approach
spellingShingle Analyzing Brazilian markets using the Global VAR & IIS Approach
Barbosa, Bruno Tebaldi de Queiroz
Macroeconomic
Global VAR
GVAR
Macroeconomia
Economia
Economia - Brasil
Modelos econométricos
Macroeconomia
Mercado de trabalho - Brasil
title_short Analyzing Brazilian markets using the Global VAR & IIS Approach
title_full Analyzing Brazilian markets using the Global VAR & IIS Approach
title_fullStr Analyzing Brazilian markets using the Global VAR & IIS Approach
title_full_unstemmed Analyzing Brazilian markets using the Global VAR & IIS Approach
title_sort Analyzing Brazilian markets using the Global VAR & IIS Approach
author Barbosa, Bruno Tebaldi de Queiroz
author_facet Barbosa, Bruno Tebaldi de Queiroz
author_role author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EESP
dc.contributor.member.none.fl_str_mv Marçal, Emerson
Maciente, Aguinaldo Nogueira
Prince, Diogo
Laurini, Márcio Poletti
dc.contributor.author.fl_str_mv Barbosa, Bruno Tebaldi de Queiroz
dc.contributor.advisor1.fl_str_mv Pereira, Pedro L. Valls
contributor_str_mv Pereira, Pedro L. Valls
dc.subject.eng.fl_str_mv Macroeconomic
topic Macroeconomic
Global VAR
GVAR
Macroeconomia
Economia
Economia - Brasil
Modelos econométricos
Macroeconomia
Mercado de trabalho - Brasil
dc.subject.por.fl_str_mv Global VAR
GVAR
Macroeconomia
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Economia - Brasil
Modelos econométricos
Macroeconomia
Mercado de trabalho - Brasil
description This thesis consists of three chapters. The chapters can be read separately, ie there is no predetermined reading order. However, the suggested order follows a linear evolution of the theme. This work expands the work of Barbosa (2017), in his study the author establishes a model for the Brazilian market taking into account the interdependencies between regions using the Global VAR (GVAR) methodology, and uses this model to estimate the elasticity of regional employment in relation to the country’s economic activity. In this study we expand the Barbosa (2017) model on several fronts. First, the study addresses the use of different weight matrices. Traditionally, the weight matrix used in the literature is based on trade weights and bilateral trade between two countries. Barbosa (2017) proposes a weight matrix based on connections between regions, this study in its turn expands these weight matrix allowing the weight matrix to be based not only on connections between regions but also on macroeconomic variables of each region such as GDP, GDP per capita and population. A second innovation is made with the proposal of a new econometric model. This new econometric model is built from the Global VAR model, which is expanded through a saturation with impulse indicators (henceforth called GVAR-IIS). It is worth mentioning that the hypothesis of weak exogeneity remains a requirement for the validity of the GVAR-IIS. For validation of weak exogeneity, the study applies not only the classical tests of weak exogeneity proposed by Granger and Lin (1995) but expands the tests by applying the concept of separability proposed by Hecq et al. (2002). The first part of the study analyzes the original model proposed by Barbosa (2017) using a weight matrix based on connections between cities. The database is expanded to include the period of forecasts that took place between 2016 and 2018. In this chapter we assess how the forecasts behave in the face of the scenario, we also assess the resilience of the regions and the heterogeneity of the responses. In the second part, the GVAR model proposed by Barbosa (2017) is saturated with impulse indicators, this new model is referred as GVAR-IIS. The chapter proposes an estimation procedure for the GVARIIS. The Chapter also presents an empirical exercise in which the new GVAR-IIS model is evaluated together with other models to assess its predictive power. To validate the hypotheses of weak exogeneity, the classical tests proposed by Granger and Lin (1995) are carried out, in which an innovation is the use of the concept of separability proposed by Hecq et al. (2002) to validate the hypothesis of weak exogeneity. Finally, in the third part, the GVAR-IIS model developed in the previous chapter is used together with a weight.
publishDate 2022
dc.date.accessioned.fl_str_mv 2022-07-19T15:09:24Z
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