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An Agent-Based Model of Migration and Drought-Induced Crop Loss in Bangladesh
Kelsea Best, Vanderbilt University Nashville Tennessee, United States. kelsea.b.best@vanderbilt.edu
One possible human response to climate change and other environmental stresses is migration. However, migration is complex, multi-causal phenomenon, and the complexity of human migration poses a challenge for researchers who aim to study the effects of environmental changes on population mobility. This project aims to understand how changing environmental conditions and livelihood opportunities impact migration decisions in coastal Bangladesh. An original agent-based model (ABM) that combines stylized environmental change dynamics with livelihood is developed to understand how these dynamics impact migration decisions as well as what feedbacks may exist between them. The ABM is constructed such that agents represent households, consisting of individuals, within a single origin community. At each step of the model, an agent will first assess the expected utility of its different options within the community, including doing nothing, seeking employment internal to the community, and investing in non-agricultural livelihood options. After assessing livelihood options internal to the community, households with sufficient wealth and a sufficient number of family members will decide whether or not to send a household member as a migrant, also based on expected utility of a migration trip. The model’s representation of natural processes will be simulated in the form of drought, modeled stochastically, that impacts crop yields and crop-associated income. In this initial version of the ABM, agent decision-making is based on simple utility maximization. Future work will incorporate more complex decision-making theories into the model, as well as different destination locations and the possibility of return migration.
