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An Agent-Based Model of Climate-Induced Agricultural Labor Migration

Author

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  • Cai, Ruohong
  • Oppenheimer, Michael

Abstract

Using an agent-based model, we simulate the climate-induced agricultural labor migration for alternative future climate scenarios. For each agent, the probability of migration is calculated as a function of a set of relevant factors using a logistic regression model. Historical U.S. agricultural employment data was used to calibrate the model. The simulation result showed that larger crop yield reduction induced by climate change tends to generate larger migration flows. Furthermore, we observed that the network effects tend to forecast a larger migration difference between alternative climate scenarios.

Suggested Citation

  • Cai, Ruohong & Oppenheimer, Michael, 2013. "An Agent-Based Model of Climate-Induced Agricultural Labor Migration," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150972, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea13:150972
    DOI: 10.22004/ag.econ.150972
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    Cited by:

    1. Trond G. Husby & Elco E. Koks, 2017. "Household migration in disaster impact analysis: incorporating behavioural responses to risk," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(1), pages 287-305, May.
    2. Kelsea B. Best & Jonathan M. Gilligan & Hiba Baroud & Amanda R. Carrico & Katharine M. Donato & Brooke A. Ackerly & Bishawjit Mallick, 2021. "Random forest analysis of two household surveys can identify important predictors of migration in Bangladesh," Journal of Computational Social Science, Springer, vol. 4(1), pages 77-100, May.

    More about this item

    Keywords

    Agricultural and Food Policy; Environmental Economics and Policy; Labor and Human Capital;
    All these keywords.

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