Análise dos efeitos de encadeamento na bioeconomia e na economia de baixo carbono no Brasil

• Ano de defesa: 2020
• Autor(a) principal: Robinson, Andrey Luis dos Santos
• Orientador(a): Giacomelli Sobrinho, Valny
• Banca de defesa: Feistel, Paulo Ricardo, Oliveira, Cassius Rocha de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Centro de Ciências Sociais e Humanas
• Programa de Pós-Graduação: Programa de Pós-Graduação em Economia e Desenvolvimento
• Departamento: Economia
• País: Brasil
• Palavras-chave em Português: Bioeconomia; Bioenergia; Matriz insumo-produto ampliada; Encadeamentos
• Palavras-chave em Inglês: Bioeconomy; Bioenergy; Augmented input-output matrix; Linkage effects
• Área do conhecimento CNPq: CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/21860

The strategy of identifying and investing in those economic sectors capable of standing out of the others dates back to the late 1950s, when Hirschman put forward the linkage hypothesis. According to it, the difference between the most and least advanced sectors paves the way for the deliberate undertaking of induced investments in a Keynesian-like multiplier effect. Development should be set off by governmental investments in sectors with outstanding performance (key sectors), the activity of which would propel that of the others. Forward linkages (FL) single out the most spread (by-) products throughout the economy, whereas backward linkages (BL) highlight the sectors that are the most dependent on the others. Such effects are measured by indices calculated from the rows and columns of inverse input-output matrices. It looks like the linkage hypothesis appears to fit in an energy transition scenario to check how bioenergy consumption affects other sectors of the economy. By adding (IPA) to the basic input-output (IP) model energy inputs and making use of the linkage hypothesis, it is possible to spotlight the most dependent sectors and the most used inputs. Therefore, the objective of this study is to build up a model that allows for not only identifying them, but also for comparing the results disclosed by the standard (IP) and by the augmented (IPA) input-output matrix. To this end, data for Brazil in 2018 are employed. Hence, when all of the country’s energy inputs are indistinctively taken into account, the Transport sector is the most dependent one, and Petroleum and Oil Products are the most demanded (spread) energy inputs by the economy. The results change when the emphasis is placed upon bioenergy inputs. In this case, the Paper and Pulp sector is the most dependent one, while Black Liquor turns out to be the most widely consumed bioenergy input. It can be concluded that such changes drive both the investments and the development strategy to be designed. For instance, reducing the use of fossil fuels (Oil Products) would harm investments in the Transport sector, whereas the option for a bioeconomic strategy of development would favour the Paper and Pulp sector.