Detalhes bibliográficos
Ano de defesa: |
2010 |
Autor(a) principal: |
Holanda, Francisco das Chagas da Costa |
Orientador(a): |
Não Informado pela instituição |
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: |
|
Link de acesso: |
http://www.repositorio.ufc.br/handle/riufc/6177
|
Resumo: |
This work analyzes the performance of the APIS Araripe Project, which was developed to meet the supply chain of beekeeping in the Picos Microregion in the federative state of Piauí, in the period 2005 to 2007, having, as a result, the increase the honey production and its productivity. At first, regressions were made, using only data of the dummies of the year (2004 and 2007), in the region influenced by the project, to assess its impact, through the analysis of difference in differences (D in D). The results show that the action of the project has been altered the productivity, extensively and in a positive way, which mean that the productivity of honey, in general, has been benefited, in that region. Likewise the productivity, the production has also been affected in a positive way, by the action of the project. Another result comes out after controlling the regression by the number of beehives populated (colhab) and lost clusters (enxperd): according to the studies, the production is not directly affected by the actions of the project. One could say that the increase in production is due to the increased number of beehives populated and yet the losses reduction of swarms. However, no one can assure these factors were improved by the action of the project, because it would require a deeper analysis. Observing the influence of the project on productivity / honey production, it was identified the factors that were decisive influence in simple regression models. |