Geração e distribuição de riqueza da cultura do milho nas principais cidades produtoras do Brasil
Ano de defesa: | 2015 |
---|---|
Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal de Uberlândia
BR Programa de Pós-graduação em Ciências Contábeis Contabilidade Financeira UFU |
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: | |
Link de acesso: | https://repositorio.ufu.br/handle/123456789/12615 https://doi.org/10.14393/ufu.di.2015.30 |
Resumo: | The Brazilian Agribusiness represents 22% of the GDP (MARTINELLI et al., 2011), it generates around 16 million jobs and feeds 200 million people (SANTOS, 2014). On the other hand, there are studies showing that primary and secondary sectors have had considerable increase. These movements might be linked to economic factors such as a Deindustrialization and Dutch Disease as well as Re-primarization. These discussions are based on studies conducted by Rowthorn and Welles (1997), Marqueti (2002), Feijó, Carvalho and Almeida (2005), Dias and Pinheiro (2007), Bresser-Pereira (2008), Nassif (2008), Tregenna (2009), Oreiro and Feijó (2010), Filgueiras et al. (2012), Strack and Azevedo (2012), Beine, Bos and Coulombe (2012) and Dülger et al. (2013). The corn, commodity which accounts for 80% of the Brazilian grain production, elevates the country to the third position of the world after the USA and China (EMBRAPA, 2014). It will be the object of study in this essay, which used quantitative research, descriptive approach, bibliography and documental data. This essay will also try to measure the distribution and wealth creation in the main producer regions during dry weather and summer (Rio Verde-GO, Primavera do Leste-MT, Londrina-PR, Barreiras-BA, Balsas-MA, Unaí-MG, Chapadão do Sul-MS, Campo Mourão-PR and Cruz Alta-RS). In order to get to these results, two statistical techniques were used. The first panel data and the second Anova. The former was used to identify which factors have the biggest statistical significance in relation to gross revenue, i e how the increase of a factor had impact on gross revenue. The latter made it possible to get time and space analyzed i e how much and to what extent the factors participated in each producer region. In summer, the results show that the variables altd , areac , rendmed , qtdprod , mobra , agrot and preco show statistical significance in relation to gross revenue. In dry weather, the variables ndprecip , tempmax , tempmin , prodreg , produtmed , areac , mobra , muda , fert , agrot , maq , outros , terra , juros and preco show statistical significance, the others, for the two analyses did not show statistical significance. After the analyses, it was concluded that in dry weather, the regions, Rio Verde (GO), Primavera do Leste (MT) and Londrina (PR) have in common the fact that all these factors were altered in wealth creation . In the case of Rio Verde, the factor terra changed between 2005 and 2014 from 2% to 13%, but with peaks of 23%, 27% and 23% in the years 2011, 2012 and 2013, respectively. In Primavera do Leste (MT) the factors terra and fertilizantes grew the most during the analyzed period. Just as it happened in Rio Verde and Primavera do Leste, in Londrina (PR) the factor terra had a considerable growth. When time and space are concerned, in summer, in the main producing cities in Brazil (Barreiras, Rio Verde, Balsas, Unaí, Chapadão do Sul, Campo Mourão, Londrina, Primavera do Leste and Cruz Alta) what was most remarkable was the increase of land participation in the wealth creation.. |