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Markov Chain Models of Refugee Migration Data

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  • Vincent Huang
  • James Unwin

Abstract

The application of Markov chains to modelling refugee crises is explored, focusing on local migration of individuals at the level of cities and days. As an explicit example we apply the Markov chains migration model developed here to UNHCR data on the Burundi refugee crisis. We compare our method to a state-of-the-art `agent-based' model of Burundi refugee movements, and highlight that Markov chain approaches presented here can improve the match to data while simultaneously being more algorithmically efficient.

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  • Vincent Huang & James Unwin, 2019. "Markov Chain Models of Refugee Migration Data," Papers 1903.08255, arXiv.org.
    • Handle: RePEc:arx:papers:1903.08255
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    References listed on IDEAS

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    1. Nagurney, Anna, 1989. "Migration equilibrium and variational inequalities," Economics Letters, Elsevier, vol. 31(1), pages 109-112.
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    3. Anna Klabunde & Frans Willekens, 2016. "Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges," European Journal of Population, Springer;European Association for Population Studies, vol. 32(1), pages 73-97, February.
    4. Richard Bellman, 1954. "Some Applications of the Theory of Dynamic Programming---A Review," Operations Research, INFORMS, vol. 2(3), pages 275-288, August.
    5. Richard Bellman, 1954. "On some applications of the theory of dynamic programming to logistics," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 1(2), pages 141-153, June.
    6. Hendrik Baumann & Werner Sandmann, 2016. "Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-19, March.
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