Political institutions and economic development: a local spatial analysis for Brazil

Detalhes bibliográficos
Autor(a) principal: Suzuki, William Yasuhiko Nagai
Data de Publicação: 2020
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Biblioteca Digital de Teses e Dissertações da USP
Texto Completo: https://www.teses.usp.br/teses/disponiveis/96/96131/tde-02072020-080257/
Resumo: Political institutions, characterized by North and Thomas (1973) and Acemoglu et al. (2001), are an essential component to explain economic development. The objective of this study is to measure the spatial heterogeneity of the relationship between political institutions and development. For this, we use a spatial moving window method applied to weighted regressions, called Geographically Weighted Regression (GWR), proposed in Fotheringham et al. (2002). In spatial econometrics and global statistical analysis, the common assumption is that the DGP (Data Generating Process) is homogeneous for the whole map or sample. On the other hand, the advantage of the local statistical analysis is that we can estimate the spatially non-stationary DGP underlying the map. Overall we find evidence that political institutions increase economic development. However, local statistical analysis shows that for many parts of Brazil the effect is null or even negative. We present maps indicating where the relationship is positive, negative, and non-significant. The dataset is a spatial cross-section on the municipalities of Brazil for the year 2000.
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spelling Political institutions and economic development: a local spatial analysis for BrazilInstituições políticas e desenvolvimento econômico: uma análise espacial local para o BrasilDesenvolvimento econômicoEconomic developmentEstatística espacial localInstituições políticasLocal spatial statisticsPolitical institutionsPolitical institutions, characterized by North and Thomas (1973) and Acemoglu et al. (2001), are an essential component to explain economic development. The objective of this study is to measure the spatial heterogeneity of the relationship between political institutions and development. For this, we use a spatial moving window method applied to weighted regressions, called Geographically Weighted Regression (GWR), proposed in Fotheringham et al. (2002). In spatial econometrics and global statistical analysis, the common assumption is that the DGP (Data Generating Process) is homogeneous for the whole map or sample. On the other hand, the advantage of the local statistical analysis is that we can estimate the spatially non-stationary DGP underlying the map. Overall we find evidence that political institutions increase economic development. However, local statistical analysis shows that for many parts of Brazil the effect is null or even negative. We present maps indicating where the relationship is positive, negative, and non-significant. The dataset is a spatial cross-section on the municipalities of Brazil for the year 2000.Instituições políticas, caracterizadas por North and Thomas (1973) e Acemoglu et al. (2001), são um componente importante para explicar desenvolvimento econômico. O objetivo deste trabalho é o de mensurar a heterogeneidade espacial da relação entre instituições políticas e desenvolvimento. Para isso é utilizado o método de janela espacial móvel aplicada a regressões com pesos, chamado de Geographically Weighted Regression (GWR), proposto em Fotheringham et al. (2002). Em econometria espacial e análises estatísticas globais, é comum assumir um DGP (Data Generating Process) homogêneo para todo mapa ou amostra. Por outro lado, a vantagem de análises estatísticas locais é que é possível estimar o DGP não estacionário que subsiste no mapa. De forma geral, é concluído que instituições políticas têm um impacto positivo no desenvolvimento econômico. Mas análises estatísticas locais mostram que para muitas partes do Brasil o efeito é nulo ou negativo. São apresentados mapas indicando onde a relação é positiva, negativa e não significativa. A análise é feita com uma base de dados cross-section espacial dos municípios do Brasil para o ano de 2000.Biblioteca Digitais de Teses e Dissertações da USPLaurini, Marcio PolettiSuzuki, William Yasuhiko Nagai2020-03-31info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/96/96131/tde-02072020-080257/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2021-03-24T20:40:01Zoai:teses.usp.br:tde-02072020-080257Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212021-03-24T20:40:01Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Political institutions and economic development: a local spatial analysis for Brazil
Instituições políticas e desenvolvimento econômico: uma análise espacial local para o Brasil
title Political institutions and economic development: a local spatial analysis for Brazil
spellingShingle Political institutions and economic development: a local spatial analysis for Brazil
Suzuki, William Yasuhiko Nagai
Desenvolvimento econômico
Economic development
Estatística espacial local
Instituições políticas
Local spatial statistics
Political institutions
title_short Political institutions and economic development: a local spatial analysis for Brazil
title_full Political institutions and economic development: a local spatial analysis for Brazil
title_fullStr Political institutions and economic development: a local spatial analysis for Brazil
title_full_unstemmed Political institutions and economic development: a local spatial analysis for Brazil
title_sort Political institutions and economic development: a local spatial analysis for Brazil
author Suzuki, William Yasuhiko Nagai
author_facet Suzuki, William Yasuhiko Nagai
author_role author
dc.contributor.none.fl_str_mv Laurini, Marcio Poletti
dc.contributor.author.fl_str_mv Suzuki, William Yasuhiko Nagai
dc.subject.por.fl_str_mv Desenvolvimento econômico
Economic development
Estatística espacial local
Instituições políticas
Local spatial statistics
Political institutions
topic Desenvolvimento econômico
Economic development
Estatística espacial local
Instituições políticas
Local spatial statistics
Political institutions
description Political institutions, characterized by North and Thomas (1973) and Acemoglu et al. (2001), are an essential component to explain economic development. The objective of this study is to measure the spatial heterogeneity of the relationship between political institutions and development. For this, we use a spatial moving window method applied to weighted regressions, called Geographically Weighted Regression (GWR), proposed in Fotheringham et al. (2002). In spatial econometrics and global statistical analysis, the common assumption is that the DGP (Data Generating Process) is homogeneous for the whole map or sample. On the other hand, the advantage of the local statistical analysis is that we can estimate the spatially non-stationary DGP underlying the map. Overall we find evidence that political institutions increase economic development. However, local statistical analysis shows that for many parts of Brazil the effect is null or even negative. We present maps indicating where the relationship is positive, negative, and non-significant. The dataset is a spatial cross-section on the municipalities of Brazil for the year 2000.
publishDate 2020
dc.date.none.fl_str_mv 2020-03-31
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dc.identifier.uri.fl_str_mv https://www.teses.usp.br/teses/disponiveis/96/96131/tde-02072020-080257/
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dc.language.iso.fl_str_mv eng
language eng
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dc.rights.driver.fl_str_mv Liberar o conteúdo para acesso público.
info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Biblioteca Digitais de Teses e Dissertações da USP
publisher.none.fl_str_mv Biblioteca Digitais de Teses e Dissertações da USP
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reponame_str Biblioteca Digital de Teses e Dissertações da USP
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