Abstract
We investigate fat tails and network interconnections of geopolitical risk index and food prices, including the price of corn, rice, and wheat, using seven Bayesian vector heterogeneous autoregression fashions. This paper differentiates dynamically between network interlinkages between these variables during the short, medium, and long runs. We found some noteworthy results in our study. In the first place, network interlinkages exhibit remarkable differences over time. Interlinkages between variables in our designed networks are increased in the short, medium, and long term due to transient events occurring in markets during the studied period. During the Russia-Ukraine conflict, the long-term ties within the system are more significantly impacted. Additionally, based on net-directional linkages, each market’s role shifts (from sending to receiving shock and vice versa) during the pre- and post-Ukraine-Russia conflict, whereas these roles persist during the COVID-19 pandemic. Observations of short- and medium-term trends reveal that the geopolitical risk index is shock receivers transmitted to these markets by the rice and corn markets. The results indicate that the geopolitical risk index persists as shock receivers in terms of long-horizon measures.
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Notes
Note that we the lag number used in MA representation to Q = 100 horizons. Other values of Q are also considered, such as Q = {150, 200, 250} for the robustness checks.
The results from these models can be provided by authors upon request.
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Le Thanh Ha contributed to all stages of preparing, drafting, writing, and revising this review article. Le Thanh Ha made a substantial, direct, and intellectual contribution to the work during different preparation stages. Le Thanh Ha read, revised, and approved the final version of this manuscript.
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Appendix
Appendix
Horizon-specific network interlinkage measures. Note. We plot the posterior median, and one standard deviation percentiles of the posterior distribution of horizon-specific network interlinkage measures, \({D}_{d}\). Network interlinkages at short horizons (from 1 day to 1 week), at medium horizons (from 1 week to 1 month), and at long horizons (larger than 1 month) are, respectively, displayed at the top, middle, and bottom panels
Short-horizon (1 day to 1 week) net-directional linkages. Note. Positive (negative) values mean that the considered market plays a role of a transmitter (receiver) of shock
Medium-horizon (1 week to 1 month) net-directional linkages. Note. Positive (negative) values mean that the considered market plays a role of a transmitter (receiver) of shock
Long-horizon (greater than 1-month) net-directional linkages. Note. Positive (negative) values mean that the considered market plays a role of a transmitter (receiver) of shock
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Ha, L.T. Fat tails, serial dependence, and interlinkages of the geopolitical risk and food market during the COVID-19 pandemic and war crisis: an application of Bayesian vector heterogeneous autoregressions. Environ Sci Pollut Res (2023). https://doi.org/10.1007/s11356-023-29565-8
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DOI: https://doi.org/10.1007/s11356-023-29565-8
Keywords
- Bayesian vector heterogeneous autoregressions
- Network interlinkages
- Geopolitical risk
- Food prices
- COVID-19, Ukraine-Russia conflict