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GTAP Resource #5593

"Economic Impacts of Bioelectricity from Forest Biomass when Forest Producers have Comparative Advantage: the case of Brazil"
by Alves, Gabriel and Angelo Gurgel

Forest biomass has been used as an energy source since the begging of human king. Compared with other countries, Brazil has a natural advantage to produce commercial forests. The bioelectricity in the country, however, derive mostly from sugarcane industry. This study aimed to understand the impacts and pathways of an eventual expansion of forest plantations dedicated to electricity production on the domestic economy, especially on the forestry, energy and other competitors’ sectors. We employ a dynamic-recursive computable general equilibrium model of world economy to project alternative scenarios about forest bioenergy expansion in Brazil. The results suggest that the increase in forest biomass for electric power generation is highly dependent on governmental incentives and technological advances. A consistent participation of the forest biomass in the grid has almost no economic impacts on other sectors using forest based inputs, such as pulp and paper and iron and steel industries, neither on land use competitor sectors, like the agricultural sector. Even with very high public incentives to increase forest biomass, the impacts on GDP are negligible. Land use dynamics from larger increase in planted forest will not influence deforestation rates of native vegetation. Therefore, although the upscaling of forest biomass to bioelectricity in Brazil has very low negative impacts on other economic sectors, GDP or land use dynamics, only governmental incentives will ensure the growth and strengthening of forest bioelectricity as an energy source in the country.

Resource Details (Export Citation) GTAP Keywords
Category: 2018 Conference Paper
Status: Published
By/In: Presented at the 21st Annual Conference on Global Economic Analysis, Cartagena, Colombia
Date: 2018
Created: Gurgel, A. (4/15/2018)
Updated: Gurgel, A. (4/15/2018)
Visits: 2,175
- Dynamic modeling
- Renewable energy
- Land use
- South America

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