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Evidence-based investment selection: Prioritizing agricultural development investments under climatic and socio-political risk using Bayesian networks

Author

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  • Barbaros Yet
  • Christine Lamanna
  • Keith D Shepherd
  • Todd S Rosenstock

Abstract

Agricultural development projects have a poor track record of success mainly due to risks and uncertainty involved in implementation. Cost-benefit analysis can help allocate resources more effectively, but scarcity of data and high uncertainty makes it difficult to use standard approaches. Bayesian Networks (BN) offer a suitable modelling technology for this domain as they can combine expert knowledge and data. This paper proposes a systematic methodology for creating a general BN model for evaluating agricultural development projects. Our approach adapts the BN model to specific projects by using systematic review of published evidence and relevant data repositories under the guidance of domain experts. We evaluate a large-scale agricultural investment in Africa to provide a proof of concept for this approach. The BN model provides decision support for project evaluation by predicting the value—measured as net present value and return on investment—of the project under different risk scenarios.

Suggested Citation

  • Barbaros Yet & Christine Lamanna & Keith D Shepherd & Todd S Rosenstock, 2020. "Evidence-based investment selection: Prioritizing agricultural development investments under climatic and socio-political risk using Bayesian networks," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-22, June.
    • Handle: RePEc:plo:pone00:0234213
    DOI: 10.1371/journal.pone.0234213
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    References listed on IDEAS

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    6. Florin, Madeleine J. & van Ittersum, Martin K. & van de Ven, Gerrie W.J., 2013. "Family farmers and biodiesel production: Systems thinking and multi-level decisions in Northern Minas Gerais, Brazil," Agricultural Systems, Elsevier, vol. 121(C), pages 81-95.
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    Cited by:

    1. Min Cui & Jizhou Zhang & Xianli Xia, 2022. "The Relationship between Child Rearing Burden and Farmers’ Adoption of Climate Adaptive Technology: Taking Water-Saving Irrigation Technology as an Example," Agriculture, MDPI, vol. 12(6), pages 1-22, June.
    2. Leslie Lipper & Jyotsna Puri & Romina Cavatassi & Nancy McCarthy, 2022. "How does climate change affect the evidence we need for agricultural development?," Agricultural Economics, International Association of Agricultural Economists, vol. 53(6), pages 911-923, November.
    3. Lotte Yanore & Jaap Sok & Alfons Oude Lansink, 2024. "Do Dutch farmers invest in expansion despite increased policy uncertainty? A participatory Bayesian network approach," Agribusiness, John Wiley & Sons, Ltd., vol. 40(1), pages 93-115, January.

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