O mercado de caminhões no Brasil: um estudo econométrico dos determinantes das vendas de veículos

• Ano de defesa: 2016
• Autor(a) principal: Gonçalves, Carlos Aurélio Bustamante
• Orientador(a): Oliveira, Antonio Carlos Manfredini da Cunha
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Mercado de caminhões; Demanda veicular; Estudo econométrico de demanda; Demanda de caminhões no Brasil; Vendas de caminhões; Demanda de veículos comerciais de carga; Modelo econométrico de demanda de caminhões no Brasil; Regressão linear múltipla; Causalidade vendas-crédito
• Palavras-chave em Inglês: Truck market; Vehicle demand; Econometric study for demand; Demand for trucks in Brazil; Truck sales; Demand for cargo vehicles; Econometric model of demand for trucks in Brazil; Multiple linear regression; Causality sales-credit
• Link de acesso: http://hdl.handle.net/10438/17541

This is a study on the demand for new trucks in Brazil from 1996 to 2015, and an investigation on the factors that influence it. This topic is relevant due to the scarcity of studies concerning the subject, and due to the overwhelming domination of trucks in cargo transport in Brazil. It aims identify and quantify the variables that drive the sales of trucks. To reach this goal, econometric models were constructed based on secondary data. Variables usually adopted in other studies on automotive demand were confirmed and even refined and new variables were successfully introduced. This study innovates by identifying three groups of variables, and by detailing the effects and the lags of their influence: variables specific to the truck market, variables related to GDP, and variables related to the decision maker’s confidence. Additionally, a causality analysis involving credit and truck sales was performed, unexpectedly resulting in sales causing credit. Through these results, this study disseminates knowledge about the behavior of the truck market to the entire productive chain, contributing to evolve the quality of decisions and the efficiency of the entire system.