Motivated by the deterioration in global food security conditions, this paper develops a parsimonious machine learning model to derive a multi-year outlook of global severe food insecurity from macro-economic projections. The objective is to provide forecasts that are internally consistent with wide...

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1. Verfasser:	Andree, Bo Pieter Johannes (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Washington, D.C The World Bank 2022
Schlagworte:	Agriculture Economic Shocks Food and Nutrition Policy Food Crises Food Insecurity Food Security Food Security Policy Health, Nutrition and Population Humanitarian Needs Machine Learning Macro-Economic Projection Pre-Pandemic Food Security Social Development Vulnerability
Online-Zugang:	kostenfrei
Zusammenfassung:	Motivated by the deterioration in global food security conditions, this paper develops a parsimonious machine learning model to derive a multi-year outlook of global severe food insecurity from macro-economic projections. The objective is to provide forecasts that are internally consistent with wider economic assessments, allowing both food security policies and economic development policies to be informed by a cohesive set of expectations. The model is validated on holdout data that explicitly test the ability to forecast new data from history and extrapolate beyond observed intervals. It is then applied to the World Economic Outlook database of April 2022 to project the severely food insecure population across all 144 World Bank lending countries. The analysis estimates that the global severely food insecure population may remain above 1 billion through 2027 unless large-scale interventions are made. The paper also explores counterfactual scenarios, first to investigate additional risks in a downside economic scenario, and second, to investigate whether restoring macroeconomic targets is sufficient to revert food insecurity back to pre-pandemic levels. The paper concludes that the proposed model provides a robust and low-cost approach to maintain reliable long-term projections and produce scenario analyses that can be revised systematically and interpreted within the context of available economic outlooks
Beschreibung:	1 Online-Ressource (44 Seiten)
DOI:	10.1596/1813-9450-10202