From Input-Output Matrixes to Agent-Based Models: A Case Study on Carbon Credits in a Local Economy

Analytical macroeconomic scenarios are currently the most common approach to assist in the development and evaluation of economic policies. Reproducing and evaluating the results found by analytic models is one major hurdle to be overcome by social simulation on its early development in any specific knowledge area. This work describes an initial step toward moving from algebraic input-output economic models to agent-based models, in order to get more flexibility, adding decision capabilities to the agents and exploring more complex scenarios. We study economic scenarios of carbon credits for reducing deforestation in a region of Para state, in the Brazilian Amazonia. The objective is to investigate the underlying assumptions of the analytic model through an agent-based approach, deriving new challenges to be tackled by future agent-based models.