The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model

TL;DR

This paper empirically analyzes how geopolitical risks influence global food market volatility using advanced GJR-GARCH-MIDAS models, revealing the importance of long-term risks and model choice for understanding food price fluctuations.

Contribution

It introduces a multi-dimensional geopolitical risk measure and compares fixed and rolling window models, demonstrating the superior performance of rolling window and two-factor models in capturing food market volatility.

Findings

Rolling window models better describe overall food market volatility.

Two-factor models have stronger explanatory power for volatility.

Long-term volatility of wheat, maize, and soybean is significantly affected by realized volatility.

Abstract

The current international landscape is turbulent and unstable, with frequent outbreaks of geopolitical conflicts worldwide. Geopolitical risk has emerged as a significant threat to regional and global peace, stability, and economic prosperity, causing serious disruptions to the global food system and food security. Focusing on the international food market, this paper builds different dimensions of geopolitical risk measures based on the random matrix theory and constructs single- and two-factor GJR-GARCH-MIDAS models with fixed time span and rolling window, respectively, to investigate the impact of geopolitical risk on food market volatility. The findings indicate that modeling based on rolling window performs better in describing the overall volatility of the wheat, maize, soybean, and rice markets, and the two-factor models generally exhibit stronger explanatory power in most cases. In terms of short-term fluctuations, all four staple food markets demonstrate obvious volatility clustering and high volatility persistence, without significant asymmetry. Regarding long-term volatility, the realized volatility of wheat, maize, and soybean significantly exacerbates their long-run market volatility. Additionally, geopolitical risks of different dimensions show varying directions and degrees of effects in explaining the long-term market volatility of the four staple food commodities. This study contributes to the understanding of the macro-drivers of food market fluctuations, provides useful information for investment using agricultural futures, and offers valuable insights into maintaining the stable operation of food markets and safeguarding global food security.