Agent-based model simulations of future changes in migration flows for Burkina Faso |
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| Authors: | Dominic Kniveton Christopher Smith Sharon Wood |
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| Institution: | 1. Department of Geography, School of Global Studies, University of Sussex, Brighton BN1 9QJ, United Kingdom;2. Representation & Cognition Group, School of Informatics, University of Sussex, Brighton BN1 9QJ, United Kingdom |
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| Abstract: | Attempts to quantify the numbers of migrants generated by changes in climate have commonly been calculated by projecting physical climate changes on an exposed population. These studies generally make simplistic assumptions about the response of an individual to variations in climate. However, empirical evidence of environmentally induced migration does not support such a structural approach and recognises that migration decisions are usually both multi-causal and shaped through individual agency. As such, agent-based modelling offers a robust method to simulate the autonomous decision making process relating to environmental migration. The Theory of Planned Behaviour provides a basis that can be used to effectively break down the reasoning process relating to the development of a behavioural intention. By developing an agent-based model of environmental migration for Burkina Faso from the basis of a combination of such theoretical developments and data analysis we further investigate the role of the environment in the decision to migrate using scenarios of future demographic, economic, social, political, and climate change in a dryland context. We find that in terms of climate change, it can be seen that that change to a drier environment produces the largest total and international migration fluxes when combined with changes to inclusive and connected social and political governance. While the lowest international migration flows are produced under a wetter climate with exclusive and diverse governance scenarios. In summary this paper illustrates how agent-based models incorporating the Theory of Planned Behaviour can be used to project evidence based future changes in migration in response to future demographic, economic social and climate change. |
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