Eficiência administrativa em cooperativas de crédito: uma análise por meio do sistema Pearls

• Ano de defesa: 2017
• Autor(a) principal: Heverton Freire Almeida
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Sistema PEALRS; Cooperativa de Crédito; Índice de Eficiência Administrativa (IEA); Cooperativas de crédito Contabilidade; Controladoria
• Link de acesso: http://hdl.handle.net/1843/BUOS-BADJ8B

In this research, we sought to analyze the relationship between the Administrative Efficiency Index and the PEARLS system variables applied to credit unions over the years 2014 and 2016. The objective of the research was to identify which indicators of the PEARLS system are outstanding for the Analysis of the efficiency in credit cooperatives to realize the efficiency relation with the PEARLS system, having as problem question: Which accounting indicators of the PEARLS system are determinant for efficiency analysis of the credit cooperatives of Brazil? The theoretical approach highlights the PEARLS system constructs, concepts related to credit cooperatives and previous studies, as well as the applied methodology (Factor Analysis and Panel Data). The data were collected on the BACEN website that comes from accounting statements in the years 2014 to 2016. Subsequently, the data were adjusted in electronic spreadsheets, the indicators were calculated and exposed the methodology to be applied. Due to the large number of variables, the quantitative data were grouped using the Econometric statistical Factor Analysis technique, with the purpose of consolidating the variables in order to identify by means of factors which would be statistically significant to the (IEA). Finally, from the regression models with panel data, we verified the influence of the variables of the PEARLS system related to the (IEA), which was found by means of an equation, where the latent variables were statistically significant, therefore in a total Of 12 variables only 3 did not represent statistically significant. The latent variables F1, F3, F4, F6, F7, F8, F9, F10 and F12 are latent. The contribution of the work to the academy was the disclosure of the latent variables explaining statistically the administrative efficiency index, the exposure of the information in the COSIF chart of accounts made available by the BACEM associated with the indicators of the PEARLS system.