O impacto socioeconômico da pandemia da Covid-19 no Brasil sob a ótica da governança pública

• Ano de defesa: 2023
• Autor(a) principal: Maciel, Ana Maria Heinrichs
• Orientador(a): Pinto, Nelson Guilherme Machado
• Banca de defesa: Coronel, Daniel Arruda, Lopes, Mygre
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Centro de Ciências Sociais e Humanas
• Programa de Pós-Graduação: Programa de Pós-Graduação em Administração Pública
• Departamento: Administração Pública
• País: Brasil
• Palavras-chave em Português: Pandemia; Covid-19; Governança pública; Impacto socioeconômico
• Palavras-chave em Inglês: Pandemic; Public governance; Socioeconomic impact
• Área do conhecimento CNPq: CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO::ADMINISTRACAO PUBLICA
• Link de acesso: http://repositorio.ufsm.br/handle/1/28869

The global crisis caused by the Covid-19 Pandemic has led countries around the world to face challenges in defining strategies to mitigate the impacts caused by the disease. Governance structures influence the decision making process of each country and bring different results and impacts. The objective of this paper is to analyze the socioeconomic impact caused by the Covid-19 Pandemic in Brazil in light of the governance model adopted by the country. The study is developed based on suggestions and evidence from the literature, dividing the variables into two lines: (i) social; which encompasses the magnitude of the disease, deaths and vaccination, and (ii) economic-financial; which covers employment and income indicators and public spending on social benefits during the Pandemic. The research is exploratory and descriptive, with the intention of investigating and describing the phenomenon, taking ownership of the theme and the impacts caused on the country's socioeconomic set. The approach of the study is quantitative, aiming to measure the impacts, using secondary data from documentary analysis of portals and public data sources. For data analysis, the techniques used are descriptive statistics and panel data regression. The random-effects test used 756 observations in 27 cross-section units, which represent the Brazilian states in the 28-month time series, from March 2020 to June 2022. The dependent variable considered is the magnitude/cases of the disease. The evidence from the study describes the pandemic scenario in the different states. From the application of the econometric model, it was found that the variables used have significance and represent the study hypothesis. Therefore, the relationship between the magnitude of the disease, the number of deaths, the number of vaccines applied, the emergency aid, and the high/low formal jobs gives support to what was proposed in the hypothesis of the study. The most indicative coefficient of the study was mortality. The directly proportional relationship indicates that states that had more cases of Covid-19 had more deaths. In addition, the vaccines variable, evidences that immunization saved more lives, as places with higher vaccination numbers had fewer cases and deaths. The emergency aid variable indicated that places where there were higher amounts of benefits paid had a decrease in cases. Considering the hiring in the labor market, where there were more people working, there were more cases of contamination. On the other hand, the more people that quit their jobs, the lower the proportion of cases of the disease. With the lockdown and the decrease in people circulating there was a reduction in the number of cases. The adjusted R² of the panel regression model presented the value of 0.405234. The value is satisfactory, as it shows that the ability to explain the issue with the variables was 40.52%. It is admitted that the six variables inserted in the study capture the relationship of the impacts of the Pandemic in the Brazilian regions. Thus, the consequences identified in each region stem from the decisions of the governance models adopted in each state, whose regionalization brought different socioeconomic impacts in the Brazilian regions.