Financial Risk Management for Sustainable Agricultural Development Based on Corporate Social Responsibility in the Interests of Food Security
Abstract
:1. Introduction
2. Literature Review
3. Methodology
- The dependence of food security indicators (according to the materials of The Economist Intelligence Unit Limited (2021)) on the financial risks in agriculture (according to the materials of The Economist Intelligence Unit Limited (2021));
- The dependence of the selected key financial risks in agriculture on the World Giving Index (according to the materials of the Charities Aid Foundation (2021)).
- Change in average food costs (fc);
- Agricultural import tariffs (it);
- Funding for food safety net programmes (fs);
- Access to finance and financial products for farmers (fp);
- Access to diversified financial products for farmers (df);
- Access to market data and mobile banking (mb).
- Affordability (FS1);
- Availability (FS2);
- Quality and safety (FS3);
- Natural resources and resilience (FS4).
4. Results
4.1. Modeling of the Financial Risk Management for Sustainable Agricultural Development Based on Corporate Social Responsibility in the Interests of Food Security
- FS1 = 45.003 + 0.23 × fs + 0.18 × df. According to the obtained regression equation, with an increase in funding for food safety net programs by 1%, affordability increases by 0.23 points. With a 1% increase in access to diversified financial products, affordability increases by 0.18 points. Fobs = 124.57. For 86 observations and 2 variables at a significance level of 0.05 Ftabl = 4.00. Since Fobs > Ftabl (124.57 > 4.00), the F-test is passed. Consequently, the obtained equation is reliable at a significance level of 0.05. The coefficient of multivariable correlation R2 = 0.8661. Variance Inflation Factor (VIF): VIF = 1/(1 − R2) = 1/(1 − 0.8661) = 7.47. Since VIF does not exceed 10, multicollinearity is low, and spurious regression is absent.
- FS2 = 50.29 + 0.13 × df. According to the obtained regression equation, with an increase in access to diversified financial products by 1%, availability increases by 0.13 points. Fobs = 25.22. For 86 observations and 1 variable at a significance level of 0.05 Ftabl = 3.15. Since Fobs > Ftabl (25.22 > 3.15), the F-test is passed. Therefore, the obtained equation is reliable at a significance level of 0.05. The coefficient of multivariable correlation R2 = 0.4805. Variance Inflation Factor (VIF): VIF = 1/(1 − R2) = 1/(1 − 0.4805) = 1.92. Since VIF does not exceed 10, multicollinearity is low, and spurious regression is absent.
- FS3 = 45.17 + 0.18 × it + 0.22 × fs. According to the obtained regression equation, with an increase in agricultural import tariffs by 1%, quality and safety increases by 0.18 points. With an increase in funding for food safety net programs by 1%, quality and safety increases by 0.22 points. Fobs = 44.65. For 86 observations and 2 variables at a significance level of 0.05 Ftabl = 4.00. Since Fobs > Ftabl (44.65 > 4.00), the F-test is passed. Therefore, the obtained equation is reliable at a significance level of 0.05. The coefficient of multivariable correlation R2 = 0.7199. Variance Inflation Factor (VIF): VIF = 1/(1 − R2) = 1/(1 − 0.7199) = 3.57. Since VIF does not exceed 10, multicollinearity is low, and spurious regression is absent.
- FS4 = 42.56 + 0.15 × df. According to the obtained regression equation, with an increase in access to diversified financial products by 1%, natural resources and agricultural sustainability increase by 0.15 points. Fobs = 44.46. For 86 observations and 1 variable at a significance level of 0.05 Ftabl = 3.15. Since Fobs < Ftabl (44.46 > 3.15), the F-test is passed. Therefore, the obtained equation is reliable at a significance level of 0.05. The coefficient of multivariable correlation R2 = 0.5883. Variance Inflation Factor (VIF): VIF = 1/(1 − R2) = 1/(1 − 0.5883) = 2.43. Since VIF does not exceed 10, multicollinearity is low, and spurious regression is absent.
4.2. Seed Production Development Trends in Russia in the Context of Food Security
- Rostov Region—winter wheat, sunflower for grain, spring barley, and grain maize;
- Krasnodar Territory—winter wheat, grain maize, peas, sugar beet, sunflower for grain, and soybeans;
- Altay Territory—spring wheat, oats, buckwheat and rapeseed, sunflower for grain, soybeans, and peas;
- Saratov Region—sunflower for grain, winter wheat, and buckwheat;
- Voronezh Region—spring barley, sugar beet, winter wheat, sunflower for grain, grain maize, soybeans, and potatoes;
- The Republic of Tatarstan—spring barley, potatoes, oats, rapeseed, peas, buckwheat, and sugar beet;
- Kursk Region—grain maize, soybeans, sugar beet, winter wheat, spring barley, and buckwheat;
- Krasnoyarsk Territory—oats, rapeseed, spring wheat, and potatoes;
- Belgorod Region—soybeans, winter wheat, grain maize, and sugar beet;
- Amur Region—soybeans;
- Stavropol Territory—peas, winter wheat, and rapeseed;
- Bryansk Region—potatoes and grain maize;
- Orel Region—buckwheat, winter wheat, spring barley, grain maize, soybeans, and sugar beet;
- The Republic of Bashkortostan—buckwheat, spring wheat, spring barley, oats, peas, potatoes, and sugar beet;
- Lipetsk Region—sugar beet, sunflower for grain, spring barley, soybeans, and rapeseed.
- Transition from regular seeds to elite seeds;
- Increase in the use of production capacities;
- Voluntary certification of quality.
5. Discussion
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
N | Country | N | Country |
---|---|---|---|
1 | Algeria | 2 | Mali |
3 | Argentina | 4 | Mexico |
5 | Australia | 6 | Morocco |
7 | Austria | 8 | Myanmar |
9 | Bahrain | 10 | Nepal |
11 | Bangladesh | 12 | Netherlands |
13 | Belgium | 14 | New Zealand |
15 | Benin | 16 | Nicaragua |
17 | Bolivia | 18 | Nigeria |
19 | Brazil | 20 | Norway |
21 | Bulgaria | 22 | Pakistan |
23 | Cambodia | 24 | Paraguay |
25 | Cameroon | 26 | Peru |
27 | Canada | 28 | Philippines |
29 | Chile | 30 | Poland |
31 | China | 32 | Portugal |
33 | Colombia | 34 | Romania |
35 | Congo (Dem. Rep.) | 36 | Russia |
37 | Costa Rica | 38 | Saudi Arabia |
39 | Côte d’Ivoire | 40 | Senegal |
41 | Czech Republic | 42 | Serbia |
43 | Denmark | 44 | Slovakia |
45 | Dominican Republic | 46 | South Africa |
47 | Ecuador | 48 | Spain |
49 | Egypt | 50 | Sri Lanka |
51 | El Salvador | 52 | Sweden |
53 | Ethiopia | 54 | Switzerland |
55 | Finland | 56 | Tajikistan |
57 | France | 58 | Tanzania |
59 | Germany | 60 | Thailand |
61 | Ghana | 62 | Tunisia |
63 | Greece | 64 | Turkey |
65 | Hungary | 66 | Uganda |
67 | India | 68 | Ukraine |
69 | Indonesia | 70 | United Arab Emirates |
71 | Ireland | 72 | United Kingdom |
73 | Israel | 74 | United States |
75 | Italy | 76 | Uruguay |
77 | Japan | 78 | Uzbekistan |
79 | Jordan | 80 | Venezuela |
81 | Kazakhstan | 82 | Vietnam |
83 | Kenya | 84 | Yemen |
85 | Malaysia | 86 | Zambia |
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Region | Share in the Total Structure of Acreage, % | Acreage, Thousand Ha. |
---|---|---|
Rostov Region | 5.9 | 4748.0 |
Krasnodar Territory | 4.7 | 3727.2 |
Volgograd Region | 3.9 | 3090.9 |
Voronezh Region | 3.4 | 2685.9 |
Tambov Region | 2.3 | 1831.1 |
Kursk Region | 2.1 | 1666.3 |
Belgorod Region | 1.8 | 1425.2 |
Lipetsk Region | 1.7 | 1372.6 |
Orel Region | 1.6 | 1313.2 |
Ryazan Region | 1.3 | 1020.4 |
Crops | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|
Cereals and legumes | 59.4 | 59.6 | 58.2 | 58.4 | 59.9 |
Industrial | 17.2 | 17.4 | 19.1 | 19.9 | 19.4 |
Potatoes, vegetables, and melons | 2.7 | 2.6 | 2.5 | 2.4 | 2.3 |
Forage | 20.7 | 20.4 | 20.2 | 19.3 | 18.5 |
Total | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 |
Winter Wheat | Spring Wheat | Sunflower for Grain | |||
Orel Region | 3.54 | Penza Region | 3.41 | Lipetsk Region | 4.13 |
Belgorod Region | 3.70 | Tyumen Region | 3.52 | Altay Territory | 4.97 |
Tambov Region | 3.73 | Orenburg Region | 4.06 | Tambov Region | 6.54 |
Kursk Region | 4.34 | Kurgan Region | 4.69 | Samara Region | 6.72 |
Saratov Region | 5.50 | Republic of Tatarstan | 5.25 | Orenburg Region | 6.81 |
Voronezh Region | 5.80 | Republic of Bashkortostan | 5.41 | Krasnodar Territory | 6.92 |
Stavropol Territory | 6.86 | Novosibirsk Region | 7.22 | Voronezh Region | 7.89 |
Volgograd Region | 6.91 | Krasnoyarsk Territory | 7.49 | Volgograd Region | 7.99 |
Krasnodar Territory | 12.32 | Altay Territory | 8.65 | Rostov Region | 10.63 |
Rostov Region | 16.66 | Omsk Region | 9.52 | Saratov Region | 13.14 |
Spring Barley | Grain Maize | Oat | |||
Samara Region | 3.01 | Rostov Region | 4.01 | Udmurtian Republic | 2.90 |
Ryazan Region | 3.45 | Orel Region | 4.58 | Kemerovo Region | 3.30 |
Orel Region | 3.82 | Republic of North Ossetia—Alania | 5.17 | Omsk Region | 3.42 |
Rostov Region | 3.85 | Tambov Region | 5.36 | Irkutsk Region | 3.54 |
Republic of Bashkortostan | 5.10 | Bryansk Region | 6.09 | Tyumen Region | 4.52 |
Lipetsk Region | 5.38 | Belgorod Region | 6.33 | Republic of Tatarstan | 4.60 |
Kursk Region | 5.65 | Voronezh Region | 6.59 | Novosibirsk Region | 4.83 |
Tambov Region | 5.74 | Kabardino-Balkarian Republic | 6.96 | Republic of Bashkortostan | 6.24 |
Voronezh Region | 6.29 | Kursk Region | 10.25 | Krasnoyarsk Territory | 8.61 |
Republic of Tatarstan | 8.34 | Krasnodar Territory | 15.53 | Altay Territory | 8.90 |
Soybean | Rapeseed | Pea | |||
Lipetsk Region | 2.60 | Lipetsk Region | 4.33 | Tambov Region | 3.97 |
Altay Territory | 3.96 | Ryazan Region | 4.47 | Ryazan Region | 4.02 |
Orel Region | 4.38 | Stavropol Territory | 4.49 | Republic of Bashkortostan | 4.41 |
Voronezh Region | 4.68 | Novosibirsk Region | 4.80 | Republic of Tatarstan | 4.92 |
Tambov Region | 5.60 | Republic of Tatarstan | 5.17 | Novosibirsk Region | 5.54 |
Krasnodar Territory | 7.16 | Kemerovo Region | 5.27 | Altay Territory | 5.63 |
Primorye Territory | 8.75 | Kaliningrad Region | 5.70 | Omsk Region | 5.78 |
Kursk Region | 12.69 | Tula Region | 6.04 | Krasnodar Territory | 8.35 |
Belgorod Region | 13.02 | Altay Territory | 7.38 | Rostov Region | 8.72 |
Amur Region | 22.72 | Krasnoyarsk Territory | 10.50 | Stavropol Territory | 12.20 |
Potato | Buckwheat | Sugar Beet | |||
Moscow Region | 2.28 | Saratov Region | 1.15 | Republic of Bashkortostan | 3.80 |
Kemerovo Region | 2.32 | Republic of Tatarstan | 1.58 | Belgorod Region | 5.27 |
Krasnoyarsk Territory | 3.15 | Kursk Region | 2.13 | Orel Region | 5.43 |
Sverdlovsk Region | 3.50 | Tula Region | 2.29 | Penza Region | 5.54 |
Tula Region | 3.57 | Orenburg Region | 2.43 | Republic of Tatarstan | 6.34 |
Republic of Bashkortostan | 3.62 | Kemerovo Region | 3.07 | Tambov Region | 9.48 |
Voronezh Region | 3.66 | Novosibirsk Region | 4.18 | Lipetsk Region | 10.40 |
Nizhny Novgorod Region | 3.82 | Republic of Bashkortostan | 7.23 | Voronezh Region | 10.46 |
Bryansk Region | 5.88 | Orel Region | 8.98 | Kursk Region | 11.54 |
Republic of Tatarstan | 5.99 | Altay Territory | 55.94 | Krasnodar Territory | 17.25 |
Federal District | 2017 | 2018 | 2019 | 2020 | ||||
---|---|---|---|---|---|---|---|---|
Elite | 1–4 Reproductions | Elite | 1–4 Reproductions | Elite | 1–4 Reproductions | Elite | 1–4 Reproductions | |
Central | 59.3 | 560.6 | 59.3 | 574.8 | 56.7 | 616.7 | 62.7 | 618.7 |
North-western | 12.2 | 40.7 | 13.8 | 36.9 | 8.4 | 40.2 | 9.3 | 42.1 |
Southern | 25.4 | 212.6 | 28.3 | 248.6 | 22.9 | 199.2 | 24.4 | 178.6 |
North Caucasus | 3.2 | 53.5 | 3.7 | 64.2 | 2.5 | 62.7 | 3.5 | 60.1 |
Volga | 200.9 | 1048.0 | 218.1 | 1048.7 | 256.8 | 1066.1 | 309.5 | 999.4 |
Ural | 71.4 | 412.9 | 67.2 | 390.9 | 85.4 | 418.5 | 103.2 | 463.9 |
Siberian | 157.3 | 968.0 | 177.0 | 969.1 | 187.1 | 1015.6 | 213.9 | 1088.6 |
Far Eastern | 11.8 | 35.6 | 5.8 | 46.9 | 9.4 | 61.8 | 16.9 | 59.5 |
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Polukhin, A.A.; Panarina, V.I. Financial Risk Management for Sustainable Agricultural Development Based on Corporate Social Responsibility in the Interests of Food Security. Risks 2022, 10, 17. https://doi.org/10.3390/risks10010017
Polukhin AA, Panarina VI. Financial Risk Management for Sustainable Agricultural Development Based on Corporate Social Responsibility in the Interests of Food Security. Risks. 2022; 10(1):17. https://doi.org/10.3390/risks10010017
Chicago/Turabian StylePolukhin, Andrey A., and Veronika I. Panarina. 2022. "Financial Risk Management for Sustainable Agricultural Development Based on Corporate Social Responsibility in the Interests of Food Security" Risks 10, no. 1: 17. https://doi.org/10.3390/risks10010017