Abordagem das Capacitações: aplicação do método GoM na construção de indicadores de bem estar

• Ano de defesa: 2014
• Autor(a) principal: Augusto Carvalho Souza
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Grade of Membership; Medida de bem estar; Desenvolvimento; Abordagem das capacitações; Economia
• Link de acesso: http://hdl.handle.net/1843/AMSA-9JGQRC

The current doctoral dissertation aims to advance knowledge about methods of measurement of individual capacity and functioning according to the Capability Approach. We discuss this huge and complex area of knowledge from the perspective of socio-economic development, seeking to understand the possibilities and limitations of the GoM (Grade of Membership) method as a possible way of measuring Development as Freedom. Passing through the critique of utilitarianism and the definition of the place occupied by the Capability Approach in the economic theory of social welfare and development, we highlight the complex theoretical framework inherent in this approach, and its multidimensionality, proposing a theoretical framework to guide the definition of the object of measurement: capability or functioning. We agree with other authors that secondary data are limited in the assessment of capabilities and functioning, and to observe such phenomena we must start from data obtained for this purpose. In this sense, we studied the suitability of the GoM method to the conceptual structure of the Capability Approach as a possible structure for generating capability and functioning indicators. We conclude that this method can be useful in several ways: to generate one-dimensional indicators of well-being from multidimensional data, identifying latent capabilities and functioning related to groups of indicators, and measure capability and functioning whenever possible. We tested the first usage of this method to investigate the welfare of social arrangements. We use two samples from Brazil's censuses of 2000 and 2010.