The effects of corruption on healthcare outcomes of Brazilian municipalities

Detalhes bibliográficos
Ano de defesa: 2024
Autor(a) principal: Oldani, Frederico de Aguiar
Orientador(a): Nakaguma, Marcos Yamada
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Palavras-chave em Inglês:
Link de acesso: https://hdl.handle.net/10438/34876
Resumo: This paper investigates the impact of the Controladoria Geral da União (CGU) anti-corruption audit program on healthcare outcomes in Brazilian municipalities. Employing a Poisson QMLE staggered difference-in-differences (Diff-in-Diff) approach, the study analyzes CGU audit data from 2006 to 2018 to establish a causal relationship between the audits and healthcare indicators. The results reveal that CGU audits significantly reduce fetal deaths in municipalities with higher poverty rates, illustrating the vulnerability of poorer populations to compromised public services due to corruption. Conversely, in areas with lower poverty, CGU audits are associated with lower birth rates. Both effects are more pronounced in municipalities with serious corruption findings, indicating a link between higher corruption levels and more adverse health outcomes. While acknowledging some of the critiques regarding the program's high costs and limited effectiveness, this work highlights the potential positive impacts on health outcomes associated with anti-corruption programs. It contributes to the literature by establishing a causal link between corruption and health outcomes and proposing an alternative Diff-in-Diff methodology that combines a quasiPoisson regression with the Sun & Abraham interaction, which is more appropriate than traditional OLS regression in the presence of count data and heterogeneous treatment effects.