Diferenciais demográficos em índices multidimensionais de vulnerabilidade: estudo de caso do impacto do desastre em Mariana nas famílias de trabalhadores em condição de pobreza

Detalhes bibliográficos
Ano de defesa: 2022
Autor(a) principal: Igor Coura de Mendonça
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
Brasil
FACE - FACULDADE DE CIENCIAS ECONOMICAS
Programa de Pós-Graduação em Demografia
UFMG
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/1843/50335
Resumo: The collapse of the Fundão dam in Mariana (MG) demonstrates how demography can be a crucial factor in the ability of families to recover or worsen their conditions. Starting from a de-identified database of the Cadastro Único of the Ministry of Citizenship , this dissertation main objective is to show the potential that multidimensional indicators of social vulnerability have in capturing the effects of a technological disaster on the affected families, including identifying aggravating or mitigating differences in the family composition in the face of sudden and adverse changes in the conditions of access to work and scarcity of resources over the years after the disaster. Based on the case study of the Mariana disaster, an impact evaluation based on the differences in differences methos was elaborated, taking as a reference its effects on the Family Vulnerability Index (IVF, in Portuguese): a multidimensional indicator of social vulnerability. An attempt was made to compare the annual results in the global indicator and in the dimensions of work and income, first by the total population of CadÚnico, and then by analyzing only the universe of families with certain demographic conditions: presence of a live-born child; presence of the elderly; absence of a spouse; and working-age minority households. The treatment group encompasses the 35 mining towns officially considered affected by the disaster. In order to list the municipalities in the control group, the K-Nearest Neighbor algorithm was used, taking 23 variables as a parameter to pair those most similar to the 35 affected, resulting in a total of 169 classified. The evaluation was divided into periods, considering each of them as a number of years from December 2014 (eleven months before the breakup), with the short-term period 2014-15; medium terms 2014-16 and 2014-17; and long term 2014-2018. This work presented apparently ambiguous results, but which manage to outline an interesting scenario to analyze and debate. Considering the entire population registered annually in CadÚnico of the two groups of municipalities, there was an apparent negative impact of the disaster in the first two years, which was reversed in the following years. But these variations were all in the third decimal place of an indicator that ranges from 0 to 1, that is, it is very risky to say that this is a real impact being observed. Likewise, access to work indicates small negative impacts in the first three years, while income scarcity shows positive impacts in all periods. When only populations with certain demographic characteristics are isolated, there are marked differences. Among the families that have newborn children, there were apparent negative impacts for all periods, both in the total IVF and in the dimensions of work and income. Families with the presence of elderly people seem to have suffered positive impacts on the IVF as a whole and on the work dimension, but negative effects on income scarcity. The lack of a spouse showed a great negative impact in the first years, which is reversed in the long term for the global IVF and scarcity of resources, but the dimension of access to work is impaired for all periods. Finally, the presence of a working-age minority in the household had more volatile results. This work does not intend to identify what this means, due to its limitations in the database and in the statistical analyses, and it is only possible to speculate hypotheses for future studies.