A Beta Regression Approach to Modelling Country-Level Food Insecurity
Anamaria Roxana Martin1, Tabita Cornelia Adamov2, Iuliana Merce2
1Doctoral School Engineering of Plant and Animal Resources, University of Life Sciences "King Mihai I" from Timisoara, Calea Aradului No. 119, 300645 Timisoara, Romania.
Foods (Basel, Switzerland)
|September 13, 2025
Summary
Reducing food insecurity globally requires addressing economic factors. Key drivers of food insecurity include low consumption expenditure, high income inequality, inflation, and low economic globalization, impacting the Zero Hunger goal.
Area of Science:
- Economics
- Agricultural Economics
- Development Studies
Background:
- Food insecurity persists globally despite agricultural advancements.
- Achieving Sustainable Development Goal 2 (Zero Hunger) necessitates understanding its drivers.
- Structural determinants of country-level food insecurity require quantitative assessment.
Purpose of the Study:
- To identify and quantitatively assess structural determinants of country-level food insecurity.
- To provide empirical evidence for policy-making towards Zero Hunger.
- To analyze the influence of economic, agricultural, political, and demographic factors.
Main Methods:
- Beta regression model applied to cross-sectional data.
- Analysis included 153 countries.
- Integrated economic, agricultural, political, and demographic variables.
Main Results:
- Low household consumption expenditure, high income inequality (GINI), high inflation, and low economic globalization significantly predict higher food insecurity.
- Land area and productivity per hectare showed minor inverse effects.
- Unemployment, political stability, and conflict were not significant predictors in this model.
Conclusions:
- Economic capacity, reduced inequality, inflation control, and global trade are crucial for mitigating food insecurity.
- Policy interventions should focus on these economic and trade-related factors.
- Future research can explore time-series, panel, or spatial analyses for deeper insights.
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