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A systematic review of the impact of food security governance measures as simulated in modelling studies

Nature Food volume 3, pages 619–630 (2022)Cite this article

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Abstract

To effectively address food security, we need tools that assess governance measures (for example, strategic storage reserves, cash transfers or trade regulations) ex ante. Simulation models can estimate the impact of such measures via scenarios with differently governed food systems. On the basis of a systematic review of 110 simulation studies published over 2000–2021, we examined how food security governance has been represented, and identified needs for future simulation model development. We found that studies commonly used agent-based, system dynamics, and computable general equilibrium models; tended to be production, trade or consumption centric; assessed the impact of a wide variety of mostly treasure- or authority-based measures; and applied diverse food security indicators, mostly of access or availability. We also identified blind spots (for example, simulation of nodal measures) and proposed how to address these blind spots (for example, telecoupling) and to make food security governance simulation studies fit for meta-analyses (for example, harmonizing food security indicators for comparison).

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Fig. 1: PRISMA flow diagram illustrating the identification and screening process.
Fig. 2: Domains, scales, geographic focus and food system representation of different types of simulation models.
Fig. 3: Food value chain coverage by food security governance simulation studies.
Fig. 4: Social and spatial targeting of governance measures.

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Data availability

The datasets generated during the current study are available in the FoodSecGovSim2 Code Repository on github (https://github.com/ateeuw/FoodSecGovSim2) and on the Data Repository on Dataverse (https://doi.org/10.7910/DVN/Q9WXC2)107. Source data are provided with this paper.

Code availability

The code used to generate the results described in this review can be found in the FoodSecGovSim2 Code Repository on github (https://github.com/ateeuw/FoodSecGovSim2).

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Acknowledgements

This research was made possible thanks to the funding of the 4TU.HTSF DeSIRE programme of the four universities of technology in the Netherlands and the National Science Foundation-China (grant agreement 42001228). The authors thank Y. Georgiadou for helping us define and categorize governance measures.

Author information

Authors and Affiliations

  1. Department of Natural Resources, Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, the Netherlands

    Aleid Sunniva Teeuwen, Markus A. Meyer, Yue Dou & Andrew Nelson

  2. Department of Agriculture, Ecotrophology and Landscape Development, Anhalt University of Applied Sciences, Bernburg, Germany

    Markus A. Meyer

Authors
  1. Aleid Sunniva Teeuwen
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  2. Markus A. Meyer
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Contributions

Conceptualization: A.S.T., M.A.M. and A.N. Formal analysis: A.S.T. Methodology: A.S.T. and M.A.M. Supervision: M.A.M., Y.D. and A.N. Original draft: A.S.T. Review and editing: A.S.T., M.A.M., Y.D. and A.N.

Corresponding author

Correspondence to Aleid Sunniva Teeuwen.

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Peer review information

Nature Food thanks Aogán Delaney, Derek Headey and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1

Domains of food security governance simulation models.

Extended Data Fig. 2

Social and spatial targeting of governance measures by different simulation models.

Extended Data Table 1 Framework and definitions used for governance classification
Full size table

Supplementary information

Supplementary Information

Supplementary Notes 1 and 2, Supplementary Tables 1 and 2, Supplementary Figs. 1–5 and supplementary references.

Reporting Summary

Supplementary Data 1

This table contains all the indicators used by the reviewed body of food security governance simulation modelling studies to assess the impact of governance on food security. The indicators are arranged according to the number of studies that use them, and the food security dimension (access, availability, utilization and stability) they belong to.

Supplementary Data 2

This dataset contains: (1) a list of all the screened studies and information on the databases we found them on, their eligibility and, if applicable, their reasons for rejection; (2) the ineligibility criteria; and (3) a simplified list of all eligible studies. More information can be found in the Dataverse repository (data availability statement).

Supplementary Data 3

This dataset contains information on (1) the PRISMA 2020 statement, comprising a 27-item checklist addressing the introduction, methods, results and discussion sections of a systematic review report, and (2) the 12-item PRISMA 2020 extension for abstracts.

Supplementary Data 4

Analyses of the quantitative impacts of governance measures on food security are important to inform decision makers about the effectiveness of different governance measures and, through this, speed up the alleviation of food insecurity. To facilitate such analyses, we explored which studies and governance measures within the reviewed pool of literature could be compared as they used the same food security indicators, measured with the same spatial and temporal precision, and were implemented either inside a jurisdiction, outside it or globally. Using these criteria for comparability, we found 26 groups with three to six studies, exploring up to 13 governance measures, that could potentially be compared in meta-analyses.

Source data

Source Data Fig. 2

This dataset contains information about which food security governance simulation studies use different model types in combination with different (1) model domains, (2) spatial scales, (3) geographic foci and (4) food value chain echelons.

Source Data Fig. 3

This dataset contains information on which combinations of food value chain echelons are covered by different food security governance simulation studies.

Source Data Fig. 4

This dataset contains information on food security governance studies' use of socially and spatially disaggregated data, and assessment of socially and spatially targeted governance.

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Teeuwen, A.S., Meyer, M.A., Dou, Y. et al. A systematic review of the impact of food security governance measures as simulated in modelling studies. Nat Food 3, 619–630 (2022). https://doi.org/10.1038/s43016-022-00571-2

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