Public finances sustainability by panel data models with cross-sectional dependence: analysis of Brazilian states
Autor(a) principal: | |
---|---|
Data de Publicação: | 2023 |
Outros Autores: | |
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 |