Impactos socioeconómicos y ambientales de compensaciones por la reducción de emisiones de deforestación en Bolivia: resultados del modelo OSIRIS-Bolivia
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Abstract
Bolivia tiene un gran potencial para mitigar el cambio climático a través de la reducción de la deforestación. Mientras que las posibles complicaciones han sido intensamente debatidas, se ha realizado poco análisis cuantitativo al respecto. Introducimos el modelo OSIRIS-Bolivia, con el fin de crear una base cuantitativa para la toma de decisiones. OSIRIS-Bolivia es una herramienta en Excel capaz de analizar los efectos de los incentivos REDD en Bolivia. Esta herramienta está basada en un modelo econométrico-espacial de la deforestación en el periodo 2001-2005, y usa información sobre cobertura forestal, tasas de deforestación, condiciones geograficas, y causantes de la deforestación, así como los costos de oportunidad agrícolas, para más de 120.000 píxeles en todo el país. Se trata de un modelo de equilibrio parcial, en el sentido que toma en cuenta el hecho de que reducciones en la deforestación en un lugar causarán una reducción en la oferta de productos agrícolas, lo que a su vez hará subir los precios agrícolas y aumentará la presión para deforestar en otro lugar (fugas de carbono). El modelo nos puede ayudar a resolver preguntas como: ¿donde es más probable que funcione REDD?, ¿cuanto dinero necesitamos para reducir la deforestación en cierto porcentaje?, ¿cuales son los potenciales problemas de REDD?
Bolivia has significant potential to abate climate change by reducing deforestation. This opportunity presents economic and environmental tradeoffs. While these tradeoffs have been hotly debated, they have as yet been the subject of little quantitative analysis. We introduce the OSIRIS-Bolivia model to provide a quantitative basis for decision-making. OSIRIS-Bolivia is an Excel-based tool for analyzing the potential effects of incentive payments to reduce emissions from deforestation (REDD) in Bolivia. It is based on a spatial econometric model of deforestation in Bolivia during the period 2001-2005, and uses information on forest cover, deforestation rates, geographical conditions, and drivers of deforestation, including agricultural opportunity costs, for more than 120,000 pixels covering the whole country. OSIRIS-Bolivia is based on a partial equilibrium model in which reductions in deforestation in one region reduce the supply of agricultural products to the domestic market, which in turn causes an increase in the price of agricultural products, making conversion of land to agriculture more attractive and thus stimulating an increase in deforestation in other regions (leakage). The model can help answer questions such as: Where in Bolivia are carbon incentive payments most likely to result in reduced deforestation? Who are most likely to benefit from REDD? How much money will it take to reduce deforestation by a given amount? To what extent might transaction costs or preferences for agricultural income undermine the goals of the REDD program?
Bolivia has significant potential to abate climate change by reducing deforestation. This opportunity presents economic and environmental tradeoffs. While these tradeoffs have been hotly debated, they have as yet been the subject of little quantitative analysis. We introduce the OSIRIS-Bolivia model to provide a quantitative basis for decision-making. OSIRIS-Bolivia is an Excel-based tool for analyzing the potential effects of incentive payments to reduce emissions from deforestation (REDD) in Bolivia. It is based on a spatial econometric model of deforestation in Bolivia during the period 2001-2005, and uses information on forest cover, deforestation rates, geographical conditions, and drivers of deforestation, including agricultural opportunity costs, for more than 120,000 pixels covering the whole country. OSIRIS-Bolivia is based on a partial equilibrium model in which reductions in deforestation in one region reduce the supply of agricultural products to the domestic market, which in turn causes an increase in the price of agricultural products, making conversion of land to agriculture more attractive and thus stimulating an increase in deforestation in other regions (leakage). The model can help answer questions such as: Where in Bolivia are carbon incentive payments most likely to result in reduced deforestation? Who are most likely to benefit from REDD? How much money will it take to reduce deforestation by a given amount? To what extent might transaction costs or preferences for agricultural income undermine the goals of the REDD program?
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No. 22