Predicting the Potential Impact of Emergency on Global Grain Security: A Case of the Russia–Ukraine Conflict
Abstract
:1. Introduction
2. Construction of the Grain Security Evaluation Indicator System
3. Materials and Methods
3.1. Study Area
3.2. Simulation of the Grain Security Composite Index Based on the Multi-Indicator Comprehensive Evaluation Method
3.3. ARIMA Prediction Model
3.4. Scenario Assumptions of the Russia–Ukraine Conflict
3.5. Data Source and Preprocessing
4. Results
4.1. Current Status of Grain Security in Russia and Ukraine
4.1.1. Current Status of Grain Production
4.1.2. Current Status of Grain Trade
4.1.3. Current Status of Food Prices
4.2. Historical Assessment of the Impact of the Russia–Ukraine Conflict on Global Grain Security
4.3. Predicting the Potential Impact of the Russia–Ukraine Conflict on Global Grain Security in the Future
4.3.1. Parameter Estimation and Validity Test of ARIMA Prediction Model
4.3.2. Prediction of the Possible Impact of the Russia–Ukraine Conflict in 2030
5. Discussion
6. Conclusions
- (1)
- Russia and Ukraine have an important position in global food supply and trade, and in food markets. The two countries are not only major grain producers of wheat, barley, and corn but also important grain exporters. In 2023, Russia is the world’s fourth largest wheat producer and the largest wheat exporter, the tenth largest corn producer and the sixth largest corn exporter, and the second largest barley producer and the third largest barley exporter. Ukraine is the world’s eleventh largest wheat producer and seventh largest exporter, the eighth largest corn producer and fourth largest exporter, and the seventh largest barley producer and the sixth largest barley exporter.
- (2)
- Global food prices have reached a record high due to the impact of the Russia–Ukraine conflict. Under the continuous impact of the conflict, food prices show a fluctuating trend of first increasing and then decreasing, and wheat price has increased the most. This may increase the uncertainty of the global food market and may have serious consequences for global food security.
- (3)
- The conflict between Russia and Ukraine had a negative impact on global grain security. Global grain security showed an upward trend during the period without the R–U conflict (2001–2021) but a downward trend during the period with the R–U conflict (2001–2022). It is expected that by 2030, the global grain security level will show a trend of first decreasing and then increasing with and without the R–U conflict scenarios, but the change will be greater with the R–U conflict scenario. These results conclude that the future of global grain security will be affected by the continued impact of the conflict between Russia and Ukraine, and the prospects for achieving the 2030 SDGs are more worrisome.
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Appendix B
Appendix C
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First-Layer Index | Second-Layer Index | Third-Layer Indicator (Unit) | Description | Type 1 |
---|---|---|---|---|
Grain security composite index (GSCI) | ) | : Gross per capita production index number | production Index number/population index | positive |
: Cereal yield (hg/ha) | Harvested production per unit of harvested area for crop products | positive | ||
: Cereal import dependency ratio (%) | = (cereal imports − cereal exports)/(cereal production + cereal imports − cereal exports) | negative | ||
Food loss (tonnes) | Amount of the commodity in question lost through wastage during the year at all stages between the level at which production is recorded and the household, i.e., storage and transportation. | negative | ||
: Per capita food production value variability (thousand int$) | = standard deviation of the per capita food production value/average per capita food production value | negative | ||
) | : Gross domestic product per capita ($) | gross domestic product converted by purchasing power parity/total population | positive | |
: The agriculture orientation index for government expenditures | share of agriculture in government expenditures/share of agriculture in GDP | positive | ||
Value of food imports in total merchandise exports (%) | value of food imports/total merchandise exports | negative | ||
: The FAO cereal price index | a measure of the monthly change in international prices of a basket of food commodities | negative | ||
: Food price inflation | fluctuation of grain commodity price series in a certain period | negative | ||
: Rail line density (%) | the ratio between the length of railway routes available for train service | positive | ||
) | : Percentage of arable land equipped for irrigation (%) | ratio of the irrigated land area to the cultivated land area | positive | |
: Corruption index | the pervasiveness of corruption in a country by assessing the risk of corruption | negative | ||
Urban absorption capacity | average (annual) real percentage change in GDP − the urban population growth rate | positive |
Number | Asia | Europe (EU) | Latin America and Caribbean (LAC) | Sub-Saharan Africa (SSA) |
---|---|---|---|---|
1 | Azerbaijan | Austria | Argentina | Benin |
2 | Bangladesh | Belgium | Bolivia (Plurinational State of) | Botswana |
3 | China | Belarus | Brazil | Burkina Faso |
4 | India | Bulgaria | Chile | Democratic Republic of the Congo |
5 | Indonesia | Czechia | Colombia | Côte d’Ivoire |
6 | Israel | Denmark | Costa Rica | Ethiopia |
7 | Japan | Finland | Dominican Republic | Ghana |
8 | Jordan | France | Ecuador | Kenya |
9 | Kazakhstan | Germany | El Salvador | Madagascar |
10 | Kuwait | Greece | Guatemala | Malawi |
11 | Lebanon | Hungary | Honduras | Mali |
12 | Malaysia | Ireland | Mexico | Mozambique |
13 | Mongolia | Italy | Nicaragua | Niger |
14 | Nepal | Lithuania | Panama | Nigeria |
15 | Oman | Netherlands | Paraguay | Senegal |
16 | Pakistan | Norway | Peru | Sierra Leone |
17 | Philippines | Portugal | Uruguay | South Africa |
18 | Republic of Korea | Romania | Togo | |
19 | Saudi Arabia | Russian Federation | Uganda | |
20 | Sri Lanka | Slovakia | Zambia | |
21 | Thailand | Spain | ||
22 | Türkiye | Sweden | ||
23 | Uzbekistan | Switzerland | ||
24 | Viet Nam | Ukraine | ||
25 | United Kingdom of Great Britain and Northern Ireland |
First-Layer Index | Second-Layer Index | Third-Layer Indicator | Weight |
---|---|---|---|
Grain security composite index (GSCI) | ) | : Gross per capita production index number | 0.047 |
: Cereal yield | 0.045 | ||
: Cereal import dependency ratio | 0.038 | ||
Food loss | 0.107 | ||
: Per capita food production value variability | 0.048 | ||
) | : Gross domestic product per capita | 0.084 | |
: The agriculture orientation index for government expenditures | 0.043 | ||
Value of food imports in total merchandise exports | 0.075 | ||
: The FAO cereal price index | 0.249 | ||
: Food price inflation | 0.100 | ||
: Rail line density | 0.032 | ||
) | : Percentage of arable land equipped for irrigation | 0.053 | |
: Corruption index | 0.037 | ||
Urban absorption capacity | 0.040 |
Senario | Base Period | E | Y | ||
---|---|---|---|---|---|
Without the R–U conflict | 2001–2021 | 0 | ) | ||
With the R–U conflict | 2001–2022 |
Scenario | Difference Order | T-Test Value | p-Value | AIC | Critical Value | ||
---|---|---|---|---|---|---|---|
1% | 5% | 10% | |||||
With the “Russia-Ukraine conflict” scenario (2000–2022) | 0 | −4.854 | 0.000 *** | −48.613 | −3.964 | −3.085 | −2.682 |
1 | −1.894 | 0.335 | −44.975 | −4.223 | −3.189 | −2.73 | |
2 | −0.188 | 0.940 | −32.951 | −4.332 | −3.233 | −2.749 | |
Without the “Russia-Ukraine conflict” scenario (2000–2021) | 0 | −2.476 | 0.121 | −54.599 | −4.223 | −3.189 | −2.73 |
1 | −1.34 | 0.611 | −39.153 | −4.332 | −3.233 | −2.749 | |
2 | −3.574 | 0.006 *** | −35.925 | −3.924 | −3.068 | −2.674 |
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Xu, Y.; Wang, Z.; Dong, W.; Chou, J. Predicting the Potential Impact of Emergency on Global Grain Security: A Case of the Russia–Ukraine Conflict. Foods 2023, 12, 2557. https://doi.org/10.3390/foods12132557
Xu Y, Wang Z, Dong W, Chou J. Predicting the Potential Impact of Emergency on Global Grain Security: A Case of the Russia–Ukraine Conflict. Foods. 2023; 12(13):2557. https://doi.org/10.3390/foods12132557
Chicago/Turabian StyleXu, Yuan, Zhongxiu Wang, Wenjie Dong, and Jieming Chou. 2023. "Predicting the Potential Impact of Emergency on Global Grain Security: A Case of the Russia–Ukraine Conflict" Foods 12, no. 13: 2557. https://doi.org/10.3390/foods12132557