Evaluating the Prediction Performance of the International Food Security Assessment's Production Models: A Cross-Validation Approach
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DOI: 10.22004/ag.econ.333530
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- Beghin, John C. & Meade, Birgit & Rosen, Stacey, 2014.
"A Consistent Food Demand Framework for International Food Security Assessment,"
Staff General Research Papers Archive
38196, Iowa State University, Department of Economics.
- Beghin, John C. & Meade, Birgit & Rosen, Stacey, 2015. "A consistent food demand framework for international food security assessment," ISU General Staff Papers 201502040800001029, Iowa State University, Department of Economics.
- John C. Beghin & Birgit Meade & Stacey Rosen, 2015. "A Consistent Food Demand Framework for International Food Security Assessment," Center for Agricultural and Rural Development (CARD) Publications 14-wp550, Center for Agricultural and Rural Development (CARD) at Iowa State University.
- Meade, Birgit & Rosen, Stacey & Beghin, John, 2015. "A Consistent Food Demand Framework for International Food Security Assessment," Technical Bulletins 262292, United States Department of Agriculture, Economic Research Service.
- Beghin, John C. & Meade, Birgit Gisela Saager & Rosen, Stacey, 2014. "A Consistent Food Demand Framework for International Food Security Assessment," 2014: Food, Resources and Conflict, December 7-9, 2014. San Diego, California 197167, International Agricultural Trade Research Consortium.
- 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).
- 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).
- Hertel, Thomas & Baldos, Uris Lantz & Fuglie, Keith O., 2019.
"Trade in Technology: A Potential Solution to the Food Security Challenge of the 21st Century,"
Conference papers
333121, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
- Thomas W. Hertel & Uris L.C. Baldos & Keith O. Fuglie, 2020. "Trade in Technology: A Potential Solution to the Food Security Challenges of the 21st Century," NBER Working Papers 27148, National Bureau of Economic Research, Inc.
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Keywords
International Development; Research Methods/ Statistical Methods;NEP fields
This paper has been announced in the following NEP Reports:- NEP-AGR-2023-05-08 (Agricultural Economics)
- NEP-INT-2023-05-08 (International Trade)
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