Grau de conectividade entre os mercados de milho brasileiros

• Ano de defesa: 2019
• Autor(a) principal: Meza, Christian David Hurtado
• Orientador(a): Figueiredo, Adelson Martins
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus Sorocaba
• Programa de Pós-Graduação: Programa de Pós-Graduação em Economia - PPGEc-So
• Palavras-chave em Português: Milho; VAR; VECM; Conectividade; Preços; Integração de mercados; Decomposição da variância do erro de previsão; Corn; Spillover; Connectedness; Prices; Market integration; Variance decomposition
• Área do conhecimento CNPq: CIENCIAS SOCIAIS APLICADAS::ECONOMIA::ECONOMIA MONETARIA E FISCAL::TEORIA MONETARIA E FINANCEIRA
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/12283

Corn production is one of the main economic activities in Brazil and it is used in the domestic and foreign markets. In addition, Brazil’s corn production has an important growth potential, therefore, more economic agents-like consumers, producers, hedgers, speculators, importers, exporters, local´s governments- have been involved in the corn’s market, then all of them need to understand the behavior of the market. Against this background, it is necessary new research in order to understand futures and cash prices dynamic. Hence, the main objective of this study is to examine the relationships and interactions within the Brazilian’s corn market. We used the data from Brazil’s futures market and five spot markets-Cascavel (Paraná – PR), Chapecó (Santa Catarina – SC), Rio Verde (Goiás – GO), Campinas (São Paulo - SP) and Sorriso (Mato Grosso - MT)-from January 2004 through September 2019. We used a methodology developed by Francis Diebold and Kamil Yilmaz (2009), based on the generalized variance decomposition framework from a Vector Autoregressive Model (VAR) or a Vector Error Correction Model – VECM. This methodology allows to measure both static connectedness -using full sample- and dynamic connectedness -using rolling window-through the measure the spillover index from simple pairwise to system-wide. The results reveals that the markets are well-integrated, in both short and long runs. In the same way, the results suggest that Cascavel, Campinas and Futures markets are important transmitters of information; by contrast, Sorriso transmits little information to other cities. In the analysis using rolling windows, it is possible to identify that connectedness is affected not only by prices variations but also by national and international economic changes. The results are useful for those looking for references of corn’s market integration in Brazil.