Food security, prices, and geopolitical risk: A dynamic panel threshold model

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Type of the article: Research Article

Food security is a major worldwide concern that has received heightened focus due to the COVID-19 pandemic, which disrupted global food supply chains and agri-food value networks. This paper seeks to determine the threshold at which food security is considered vulnerable to geopolitical shifts. Thus, using a dynamic panel threshold model on a sample of 40 countries, covering both advanced and emerging economies, this paper explores the link between food security – measured by the Global Food Security Index (GFSI) and its four key pillars (affordability, availability, quality and safety, sustainability and adaptation) and geopolitical tensions, represented by the Geopolitical Risk Index (GPRI), over the period from 2012 to 2021. The analysis also accounts for key variables such as agricultural land use, the impact of COVID-19, shares of urban population, price levels, and GDP per capita. The main findings indicate that the inflationary impact of geopolitical risk is statistically significant. A point (threshold value) of 0.022 was identified for geopolitical risk, beyond which global food security is substantially weakened due to increased inflation. The findings reveal that geopolitical risks exacerbate price surges across key commodities, including fertilizers, food, and oil, thereby amplifying inflationary pressures arising from fiscal measures taken in response to geopolitical shocks. Moreover, elevated geopolitical risks heighten uncertainty regarding the inflation outlook, complicating trade-offs between monetary and fiscal policies.

Acknowledgment
This work was sponsored by the Economic Research Forum (ERF) and has benefited from both financial and intellectual support. The views expressed in this work are entirely those of the author(s) and should not be attributed to ERF, its Board of Trustees, or donors.

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    • Table 1. Data description
    • Table 2. Descriptive statistics summary
    • Table 3. Linearity tests
    • Table 4. Estimation of the threshold
    • Table A1. Estimation results of the Dynamic Panel Threshold model
    • Conceptualization
      Samer Mehibel, Reda Hamza Boudjana, Amel Bouzid
    • Data curation
      Samer Mehibel, Reda Hamza Boudjana
    • Formal Analysis
      Samer Mehibel, Manuel A. Zambrano-Monserrate
    • Investigation
      Samer Mehibel, Reda Hamza Boudjana
    • Methodology
      Samer Mehibel, Reda Hamza Boudjana
    • Project administration
      Samer Mehibel
    • Supervision
      Samer Mehibel, Amel Bouzid
    • Validation
      Samer Mehibel, Manuel A. Zambrano-Monserrate, Amel Bouzid, Messaoud Lazereg
    • Visualization
      Samer Mehibel, Manuel A. Zambrano-Monserrate, Messaoud Lazereg
    • Writing – original draft
      Samer Mehibel, Reda Hamza Boudjana, Manuel A. Zambrano-Monserrate, Amel Bouzid, Messaoud Lazereg
    • Writing – review & editing
      Samer Mehibel, Reda Hamza Boudjana, Manuel A. Zambrano-Monserrate, Amel Bouzid, Messaoud Lazereg
    • Software
      Reda Hamza Boudjana