Modelling land use, deforestation, and policy analysis: A hybrid optimization-ABM heterogeneous agent model with application to the Bolivian Amazon
Policy interventions designed to simultaneously stem deforestation and reduce poverty in tropical countries entail complex socio-environmental trade-offs. A hybrid model, comprising an optimising, agricultural household model integrated into the ‘shell’ of an agent-based model, is developed in order to explore the trade-offs of alternative policy bundles and sequencing options. The model is calibrated to the initial conditions of a small forest village in rural Bolivia. Heterogeneous farmers make individually optimal land-use decisions based on factor endowments and market conditions. Endogenously determined wages and policy provided jobs link the agricultural labour market and rural-urban migration rates. Over a simulated 20-year period, the policymaker makes “real-time” public investments and public policy that in turn impact welfare, productivity, and migration. National and local land-use policy interventions include conservation payments, deforestation taxes and international REDD payments that both impact land use directly and affect the policymaker’s budget. The results highlight trade-offs between reductions in deforestation and improvements in household welfare that can only be overcome either when international REDD payments are offered or when decentralized deforestation taxes are implemented. Yet, the sequencing of policies is also found to play a critical role in these results.
Lykke Andersen, Ugur Bilge, Ben Groom, David Gutierrez, Evan Killick, Juan Carlos Ledezma, Charles Palmer and Diana Weinhold