USO DE MACHINE LEARNING PARA A ANÁLISE DE PROJETOS LEGISLATIVOS DE DESENVOLVIMENTO REGIONAL: O CASO DA ZONA FRANCA DE MANAUS

• Autor(a) principal: Rodrigues, Waldecy
• Data de Publicação: 2022
• Outros Autores: Cannavale, Victor, Trevisan, Daniela, Prata , David
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Informe Gepec (Online)
• Texto Completo: https://e-revista.unioeste.br/index.php/gepec/article/view/28611

This papper has as main objective to analyze the risk of bills for the Free Trade Zone of Manaus model (FTZM) being transformed into a legal norm, with the use of Machine Learning. This is a research with exploratory and structured analysis on open data from the Chamber of Deputies, in the period 2011-2018, with the application of a logistic regression model. As for the analysis of projects with themes relevant to regional development from FTZM, it was shown that, despite being important themes, the activities of the pole and, for the most part, being on the executive's agenda for the year, they do not receive the attention of groups and actors who may represent an influence for its effectiveness so far. The only exception is the IPI exemption project for common and electric bicycles, which, according to the model, had a highest statistical chance of being approved, which could lead to a great loss of competitiveness in the Manaus Free Trade Zone.