Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian states

Detalhes bibliográficos
Autor(a) principal: Campos, Eduardo Lima
Data de Publicação: 2023
Outros Autores: Cysne, Rubens Penha
Tipo de documento: preprint
Idioma: eng
Título da fonte: SciELO Preprints
Texto Completo: https://preprints.scielo.org/index.php/scielo/preprint/view/6349
Resumo: This study investigates the sustainability of Brazilian states’ public finances with quarterly revenue and expenses data from 2006 to 2020, aimed at the identification of groups of states that share similar patterns. The technique adopted is a panel data model that avoids mistaken inferences by controlling for cross-dependence among states. We find two clear patterns, from which we identify a fiscally sustainable group of only 9 states and an unsustainable group, comprising the remaining ones.
id SCI-1_f7235e0ece8f4f5e9e743bd5ff001ed6
oai_identifier_str oai:ops.preprints.scielo.org:preprint/6349
network_acronym_str SCI-1
network_name_str SciELO Preprints
repository_id_str
spelling Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian statesSustentabilidade das finanças públicas via modelos para dados em painel com dependência cruzada: análise dos estados brasileirosMétodos de painel de dependência cruzadasustentabilidade fiscaldívida pública dos estados brasileirosCross-dependencepanel methodsfiscal sustainabilityBrazilian states public debtThis study investigates the sustainability of Brazilian states’ public finances with quarterly revenue and expenses data from 2006 to 2020, aimed at the identification of groups of states that share similar patterns. The technique adopted is a panel data model that avoids mistaken inferences by controlling for cross-dependence among states. We find two clear patterns, from which we identify a fiscally sustainable group of only 9 states and an unsustainable group, comprising the remaining ones.Este estudo investiga a sustentabilidade das finanças públicas dos estados brasileiros a partir de dados trimestrais de receitas e despesas entre 2006 e 2020, com o objetivo de identificar grupos de estados que apresentem características semelhantes. É utilizado um modelo para dados em painel que permite controlar a dependência cruzada entre os estados, cuja omissão poderia levar a conclusões equivocadas. Encontramos dois padrões claros, a partir dos quais identificamos um grupo fiscalmente sustentável de 9 estados e um grupo insustentável, composto pelos demais.SciELO PreprintsSciELO PreprintsSciELO Preprints2023-06-30info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/634910.1590/0103-6351/7588enghttps://preprints.scielo.org/index.php/scielo/article/view/6349/12118Copyright (c) 2023 Eduardo Lima Campos, Rubens Penha Cysnehttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessCampos, Eduardo LimaCysne, Rubens Penhareponame:SciELO Preprintsinstname:Scientific Electronic Library Online (SCIELO)instacron:SCI2023-06-29T23:48:41Zoai:ops.preprints.scielo.org:preprint/6349Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2023-06-29T23:48:41SciELO Preprints - Scientific Electronic Library Online (SCIELO)false
dc.title.none.fl_str_mv Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian states
Sustentabilidade das finanças públicas via modelos para dados em painel com dependência cruzada: análise dos estados brasileiros
title Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian states
spellingShingle Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian states
Campos, Eduardo Lima
Métodos de painel de dependência cruzada
sustentabilidade fiscal
dívida pública dos estados brasileiros
Cross-dependence
panel methods
fiscal sustainability
Brazilian states public debt
title_short Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian states
title_full Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian states
title_fullStr Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian states
title_full_unstemmed Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian states
title_sort Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian states
author Campos, Eduardo Lima
author_facet Campos, Eduardo Lima
Cysne, Rubens Penha
author_role author
author2 Cysne, Rubens Penha
author2_role author
dc.contributor.author.fl_str_mv Campos, Eduardo Lima
Cysne, Rubens Penha
dc.subject.por.fl_str_mv Métodos de painel de dependência cruzada
sustentabilidade fiscal
dívida pública dos estados brasileiros
Cross-dependence
panel methods
fiscal sustainability
Brazilian states public debt
topic Métodos de painel de dependência cruzada
sustentabilidade fiscal
dívida pública dos estados brasileiros
Cross-dependence
panel methods
fiscal sustainability
Brazilian states public debt
description This study investigates the sustainability of Brazilian states’ public finances with quarterly revenue and expenses data from 2006 to 2020, aimed at the identification of groups of states that share similar patterns. The technique adopted is a panel data model that avoids mistaken inferences by controlling for cross-dependence among states. We find two clear patterns, from which we identify a fiscally sustainable group of only 9 states and an unsustainable group, comprising the remaining ones.
publishDate 2023
dc.date.none.fl_str_mv 2023-06-30
dc.type.driver.fl_str_mv info:eu-repo/semantics/preprint
info:eu-repo/semantics/publishedVersion
format preprint
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://preprints.scielo.org/index.php/scielo/preprint/view/6349
10.1590/0103-6351/7588
url https://preprints.scielo.org/index.php/scielo/preprint/view/6349
identifier_str_mv 10.1590/0103-6351/7588
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://preprints.scielo.org/index.php/scielo/article/view/6349/12118
dc.rights.driver.fl_str_mv Copyright (c) 2023 Eduardo Lima Campos, Rubens Penha Cysne
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Eduardo Lima Campos, Rubens Penha Cysne
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv SciELO Preprints
SciELO Preprints
SciELO Preprints
publisher.none.fl_str_mv SciELO Preprints
SciELO Preprints
SciELO Preprints
dc.source.none.fl_str_mv reponame:SciELO Preprints
instname:Scientific Electronic Library Online (SCIELO)
instacron:SCI
instname_str Scientific Electronic Library Online (SCIELO)
instacron_str SCI
institution SCI
reponame_str SciELO Preprints
collection SciELO Preprints
repository.name.fl_str_mv SciELO Preprints - Scientific Electronic Library Online (SCIELO)
repository.mail.fl_str_mv scielo.submission@scielo.org
_version_ 1797047812221829120

Registros relacionados