A Data-Driven Approach to Robust Predictions of Food Insecurity Crises

58 Pages Posted: 31 May 2019

See all articles by Erin Lentz

Erin Lentz

University of Texas at Austin - Lyndon B. Johnson School of Public Affairs

Hope Michelson

University of Illinois at Urbana-Champaign

Katherine Baylis

University of California, Berkeley

Yujun Zhou

University of Illinois at Urbana-Champaign - Department of Agricultural and Consumer Economics

Date Written: October 6, 2018

Abstract

Globally, over 800 million people are food insecure. Current methods for identifying food insecurity crises are not based on statistical models and fail to systematically incorporate readily available data on prices, weather, and demographics. As a result, policymakers cannot rapidly identify food insecure populations, hampering responses to mitigate hunger. We develop a replicable, near real-time model incorporating spatially and temporally granular market data, remotely-sensed rainfall and geographic data, and demographic characteristics. We train the model on 2010-2011 data from Malawi and forecast 2013 food security. Our model correctly identifies the food security status of 77% of the most food insecure village clusters in 2013 while the prevailing approach fails to correctly classify any of these village clusters. Our results show the power of modeling food insecurity to provide early warning and suggest model-driven approaches could dramatically improve food insecurity responses.

Keywords: Food Insecurity, Crisis, Prediction, Early Warning, Sub-Saharan Africa, Famine

Suggested Citation

Lentz, Erin and Michelson, H.C. and Baylis, Katherine and Zhou, Yujun, A Data-Driven Approach to Robust Predictions of Food Insecurity Crises (October 6, 2018). Available at SSRN: https://ssrn.com/abstract=3381344 or http://dx.doi.org/10.2139/ssrn.3381344

Erin Lentz

University of Texas at Austin - Lyndon B. Johnson School of Public Affairs ( email )

2300 Red River St., Stop E2700
PO Box Y
Austin, TX 78713
United States

H.C. Michelson (Contact Author)

University of Illinois at Urbana-Champaign ( email )

601 E John St
Champaign, IL Champaign 61820
United States

Katherine Baylis

University of California, Berkeley

310 Barrows Hall
Berkeley, CA 94720
United States

Yujun Zhou

University of Illinois at Urbana-Champaign - Department of Agricultural and Consumer Economics ( email )

1301 W. Gregory Drive
Urbana, IL 61801
United States

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