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Evaluating the Prediction Performance of the International Food Security Assessment's Production Models: A Cross-Validation Approach

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  • Zereyesus, Yacob Abrehe
  • Baquedano, Felix
  • Morgan, Stephen

Abstract

The U.S. Department of Agriculture (USDA), Economic Research Service (ERS) International Food Security Assessment (IFSA) model was developed to help USDA and its stakeholders evaluate the food security status of 76 low- and middle-income countries. The IFSA model provides an estimate of total food demand and food production, both elements in measuring food security. The demand side of the IFSA model is used to estimate the prevalence of country-level food insecurity based on an aggregate food consumption threshold of 2,100 calories per capita per day. The gap between aggregate domestic food production and food demand is used to estimate the implied additional supply required for each of the 76 countries in the IFSA, which is an indication of potential import needs, including food aid. The primary objective of the IFSA’s supply-side modeling work is to project production. This research evaluates the production model to determine the best performing prediction model specification. This report advances previous research by using a data-driven approach to select the best performing model specification.

Suggested Citation

  • Zereyesus, Yacob Abrehe & Baquedano, Felix & Morgan, Stephen, "undated". "Evaluating the Prediction Performance of the International Food Security Assessment's Production Models: A Cross-Validation Approach," USDA Miscellaneous 333530, United States Department of Agriculture.
    • Handle: RePEc:ags:usdami:333530
    DOI: 10.22004/ag.econ.333530
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    References listed on IDEAS

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    1. Meade, Birgit & Rosen, Stacey & Beghin, John, "undated". "A Consistent Food Demand Framework for International Food Security Assessment," Technical Bulletins 262292, United States Department of Agriculture, Economic Research Service.
    2. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    3. Hertel, By Thomas W. & Baldos, Uris L.C. & Fuglie, Keith O., 2020. "Trade in technology: A potential solution to the food security challenges of the 21st century," European Economic Review, Elsevier, vol. 127(C).
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    1. repec:ags:aaea22:335783 is not listed on IDEAS
    2. Ac-Pangan, Walter & Hendricks, Nathan P. & Zereyesus, Yacob A. & Kee, Jennifer Y. & Jelliffe, Jeremy L. & Morgan, Stephen N. & Cardell, Lila & Nava, Noé J., 2023. "Global grain supply forecasting," 2023 Annual Meeting, July 23-25, Washington D.C. 335783, Agricultural and Applied Economics Association.
    3. Ac-Pangan, Walter & Hendricks, Nathan P. & Zereyesus, Yacob & Kee, Jennifer & Jelliffe, Jeremy & Morgan, Stephen & Cardell, Lila & Nava, Noé J., 2023. "Improving Existing Methods of IFSA Supply Forecasting," 2023 Conference, April 24-25, 2023, St. Louis, Missouri 379027, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.

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