O impacto potencial do desenvolvimento dos portos do Arco Norte na valorização das fazendas de SINOP-MT: uma análise do corredor da BR-163

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: Silva, Marcel Agar
Orientador(a): Gurgel, Angelo Costa
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Palavras-chave em Inglês:
Link de acesso: http://hdl.handle.net/10438/17984
Resumo: The state of Mato Grosso stands out as the main grain producer in Brazil, however its outstanding growth as a producer was not followed by logistics projects that allowed the production to be properly exported. Grains are mainly transported through the South and Southeast ports which are far away from the North and Central North, two important producer regions in the state. The grains production travel long distances through highways, which is not appropriated to low added value products. It affects directly the grower profitability since high freight costs impact both revenue, decreasing, and input costs, increasing. To improve this current scenario many logistics projects are under development in order to allow the grain to be exported through the northern ports. Those ports tend to reduce the freight costs impact in the growers profitability. This paper aims to analyze the logistical improvements impacts in the cash generator asset, the farm. To accomplish this goal two methodologies, based on cash generation, were used: Dicounted Free Cash Flow and Ebitda Multiple. The methodologies were applied in two different moments the current one and the one after the logistical improvements impact. The comparison between the two moments will show the asset appreciation that stems from the logistical improvements. The asset appreciation variated between 29% and 81% in the discounted free cash flow methodology and between 26% and 68% in the Ebitda multiple methodology, depending on the scenario under analysis.