Three essays on machine learning and food security
type: CreativeWork
description: This dissertation contains three chapters studying the interactions between weather shocks, food prices, food policy and food security. Food insecurity has resurfaced to be a vital issue in the past two decades in sub-Saharan Africa. Income and price shocks that endanger food security could from different aspects, including drought, flood, increased volatility in international and domestic market prices, and changes in agricultural policies. Knowing when and where food insecurities happen and the reasons why they happen matters for improving humanitarian and aid responses, as well as making the right agricultural policy. My dissertation focusses on the factors that are central to food security, including the market price of grains, weather shocks in grain production areas, and agricultural policies. The first chapter focuses on the effect of stockholding policy on food prices based on evidence from Zambia. This chapter evaluates the effect of the purchase and sales activities of the Zambian Food Reserve Agency (FRA) on maize market prices across more than thirty markets in Zambia using monthly price data from 2003 to 2008. To deal with the endogeneity of the purchases and sales activities on the prices, I use predicted FRA purchase and sales targets as instrumental variables. Results show that the purchase activities help to raise producer prices during harvest seasons and that selling of maize stocks at subsidized price help to decrease maize prices during lean seasons. Controlling for other policies, I find evidence that FRA activities stabilize retail prices in major district markets within the cropping year. The reduced volatility in price from the policy would help households to become food secure yet at the cost of substantial financial burdens to the government. However, there is limited evidence found that the FRA is able to reduce price volatility between years. The second chapter builds a framework for food security predictions using readily available publ…
abstract: This dissertation contains three chapters studying the interactions between weather shocks, food prices, food policy and food security. Food insecurity has resurfaced to be a vital issue in the past two decades in sub-Saharan Africa. Income and price shocks that endanger food security could from different aspects, including drought, flood, increased volatility in international and domestic market prices, and changes in agricultural policies. Knowing when and where food insecurities happen and the reasons why they happen matters for improving humanitarian and aid responses, as well as making the right agricultural policy. My dissertation focusses on the factors that are central to food security, including the market price of grains, weather shocks in grain production areas, and agricultural policies. The first chapter focuses on the effect of stockholding policy on food prices based on evidence from Zambia. This chapter evaluates the effect of the purchase and sales activities of the Zambian Food Reserve Agency (FRA) on maize market prices across more than thirty markets in Zambia using monthly price data from 2003 to 2008. To deal with the endogeneity of the purchases and sales activities on the prices, I use predicted FRA purchase and sales targets as instrumental variables. Results show that the purchase activities help to raise producer prices during harvest seasons and that selling of maize stocks at subsidized price help to decrease maize prices during lean seasons. Controlling for other policies, I find evidence that FRA activities stabilize retail prices in major district markets within the cropping year. The reduced volatility in price from the policy would help households to become food secure yet at the cost of substantial financial burdens to the government. However, there is limited evidence found that the FRA is able to reduce price volatility between years. The second chapter builds a framework for food security predictions using readily available publ…
author: Zhou, Yujun
language: en
keywords: food security, machine learning, development economics
date published: 2020-10-07T22:44:29Z
date modified: 2026-07-22T22:24:48Z
provider: University of Illinois - Urbana-Champaign
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Illinois at Urbana-Champaign

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2142/108594