Investigating the 'Bolsonaro effect' on the spread of the Covid-19 pandemic: An empirical analysis of observational data in Brazil.

Brazil counts among the countries the hardest hit by the Covid-19 pandemic. A great deal has been said about the negative role played by President Bolsonaro's denialism, but relatively few studies have attempted to measure precisely what impact it actually had on the pandemic. Our paper conducts econometric estimates based on observational data at municipal level to quantitatively assess the 'Bolsonaro effect' over time from March 2020 to December 2022. To our knowledge, this paper presents the most comprehensive investigation of Bolsonaro's influence in the spread of the pandemic from two angles: considering Covid-19 mortality and two key transmission mitigation channels (social distancing and vaccination); and exploring the full pandemic cycle (2020-2022) and its dynamics over time. Controlling for a rich set of relevant variables, our results find a strong and persistent 'Bolsonaro effect' on the death rate: municipalities that were more pro-Bolsonaro recorded significantly more fatalities. Furthermore, evidence suggests that the president's attitude and decisions negatively influenced the population's behaviour. Firstly, pro-Bolsonaro municipalities presented a lower level of compliance with social distancing measures. Secondly, vaccination was relatively less widespread in places more in favour of the former president. Finally, our analysis points to longer-lasting and damaging repercussions. Regression results are consistent with the hypothesis that the 'Bolsonaro effect' impacted not only on Covid-19 vaccination, but has affected vaccination campaigns in general thereby jeopardizing the historical success of the National Immunization Program in Brazil.

Municípios in the Time of Covid-19 in Brazil: Socioeconomic Vulnerabilities, Transmission Factors and Public Policies.

This paper aims at identifying the Covid-19 infection and mortality risk factors in Brazil during the pandemic's first wave. Three groups of variables are considered: socioeconomic and health vulnerabilities, factors related to the virus transmission channels (mobility and density) and the effects of the policy responses. The analysis at the level of all 5,570 municipalities, drawing on a matching of different statistical and administrative databases, returns three main results. First, structurally vulnerable populations are hardest hit-non-white, poor, in poor health, favela residents and informal workers-showing the impact of socioeconomic inequalities. Second, we highlight some policy repercussions. The Auxilio Emergencial (emergency cash transfer) has had a mitigating effect in communities with relatively more informal workers. Finally, Covid-19 has hit hardest in municipalities that are more pro-Bolsonaro. The president's rhetoric and attitudes may have prompted his supporters to adopt more risky behaviour, suffer the consequences and infect others. Supplementary Information: The online version contains supplementary material available at 10.1057/s41287-021-00487-w.

Cet article cherche à identifier les facteurs de risque de contracter le COVID-19 et d'en mourir durant la première vague de la pandémie au Brésil. Trois groupes de variables sont considérés : les facteurs socio-économiques et sanitaires, ceux liés aux canaux de transmission du virus (la mobilité et la densité) et les effets des réponses politiques. Réalisée sur l'ensemble des 5 570 municipalités et basée sur l'appariement de différentes bases de données statistiques et administratives, l'analyse fait ressortir trois principaux résultats. En premier lieu, les populations structurellement vulnérables sont les plus touchées ­ non-blancs, pauvres, de santé précaire, habitants des favelas, informels - renforçant l'effet des inégalités socioéconomiques. En deuxième lieu, nous mettons en évidence l'influence des politiques. L'Auxilio emergencial (transfert monétaire d'urgence) a un effet atténuateur dans les localités ayant relativement plus de travailleurs informels. Enfin, le CoVid-19 fait plus de ravages dans les municipalités plus favorables à Bolsonaro. Le discours du président induit ses partisans à adopter plus souvent des comportements à risque et à en subir les conséquences.

Programas de renda mínima: linhas gerais de uma metodologia de avaliaçäo a partir da experiência pioneira do Paranoá, no Distrito Federal / Minimal revenue programs: general lines of a valuation methodology from pioneer experience of Paranoá, in Federal District

Avalia o programa de renda mínima implantado no Distrito Federal em maio de 1995 a partir da experiência do Paranoá em três aspectos. O primeiro, consiste no exame do sistema de pontuaçäo, responsável pela seleçäo das famílias beneficiárias. O segundo, concerne ao resultado do processo de seleçäo, comparando-se as características das famílias selecionadas e näo-selecionadas no conjunto das famílias inscritas. O terceiro aspecto refere-se à comparaçäo entre as famílias selecionadas pelo Programa e o subconjunto de famílias pobres definidas segundo os mesmos critérios na PNAD para o Distrito Federal.

Trabalho infanto-juvenil no Brasil dos anos 90 / Child labor in Brazil at 70'

Faz uma breve caracterizaçäo do trabalho de crianças e adolescentes no Brasil a partir de sua evoluçäo no passado recente, com ênfase à situaçäo observada na primeira metade dos anos novente, apresentando os principais movimentos do mercado

Distribuiçäo de renda e pobreza metropolitana / Per capita income and the metropolitan poverty

A evoluçäo da distribuiçäo de renda e da pobreza nas regioes metropolitanas do país durante a década de 80. Utiliza a Pesquisa Nacional por Amostra de Domicílios (PNAD) entre 1981 e 1989 como fonte de dados e para estudos da distribuiçäo de renda utiliza os dados de rendimento. Para a populaçäo ocupada com rendimento do trabalho, apresenta um indicador de desigualdade - o índice de Gipi. Para análise da pobreza utiliza a renda familiar (ou domiciliar) per capita. Conclui constatando o agravamento da pobreza e da miséria. (RGG)