Factors Influencing Food Markets in Developing Countries: An Approach to Assess Sustainability of the Food Supply in Russia
Abstract
:1. Introduction
2. Materials and Methods
- GDPagr—national GDP in agriculture.
- DS—aggregated state support for domestic agricultural and food producers.
- Eagr—export of agricultural products and food.
- Iagr—import of agricultural products and food.
- TQagr—foreign trade quota in agricultural products and food (share of foreign trade turnover in overall domestic output of food and agricultural commodities).
- FS—food self-sufficiency.
- PRF—profitability of domestic agricultural producers (actual level, including subsidies).
- PSP—share of small farms (personal subsidiary plots, in case of Russia) in overall agricultural production.
- ER—national currency/USD exchange rate.
- WFPI—world food price index.
- DEPI—export food price index of a country.
- DFPI—domestic food price index.
- Winf—average annual inflation (world).
- Dinf—average annual inflation (country).
3. Results
3.1. Multitude M1
3.2. Multitude M2
3.3. Multitude M3
4. Discussion
5. Conclusions
Acknowledgments
Conflicts of Interest
References
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Authors | Countries under Study | Methodology Employed | Variables Considered |
---|---|---|---|
Hentschel et al. [28] | Ecuador | Small-area estimation method | Nutrient intake, consumption of the primary products, and socioeconomic characteristics. |
Lekashvili [29] | Georgia | Dynamic economic rows approach | Minimum living wage, average per capita income, expenditures for food, domestic food prices, share of agriculture in GDP, food exports, and food imports. |
Yao et al. [30] | China | Evaluation indexes system | Food production resources, food availability and stability, food access, and food utilization. |
Zou and Guo [31] | China | Factor analysis | Arable land area per capita, degree of agricultural mechanization, agricultural labor force, and an inflation rate of grain price. |
Sharma et al. [32] | India | Analytic hierarchy process approach and sensitivity analysis | Success factors in sustainable food supply chain management, and food safety. |
Babu et al. [33] | Africa, the Middle East, and India | Factor analysis | Food-related indicators (staple food left in storage and expenditure by the household on food), assets, technology indicators, market access indicators, and household characteristics. |
Scafetti et al. [34] | Bangladesh | Standard multiple regression analysis | Education and employment of household members, number of loans taken from microfinance institutions, income, illness that affects a household, health status of a household, and number of production sources available. |
Ali et al. [35] | Bangladesh | Binary logistic regression method | Household size, income per household, and access to credit. |
Ahungwa et al. [36] | Nigeria | Trend analysis and multiple regression analysis | Interplay of domestic food production and food importation to the overall GDP. |
Oladejo [37] | Nigeria | Cobb–Douglas regression model | Quantity of maize marketed, market price for maize, cost of harvesting, transport, and storage. |
Olaniyi and Ismaila [38] | Nigeria | Binary logic regression analysis | Household size, membership of social organization, and farm size. |
Maharjan and Joshi [39] | Nepal | Binary logic regression analysis | Programs targeting small landholding farms, employment, household size, irrigation, and participation in community organizations. |
Sekhampu [40] | South Africa | Binary logic regression analysis | Household size, household income, level of education, and employment. |
Mori-Clement et al. [41] | Uzbekistan | Autoregressive integrated moving average models | Water inflow, oil prices, market exchange rate, and international prices of imported commodities. |
Syrovátka and Grega [42] | Czech Republic | Correlation and paired regression analysis | Complementary and substitution relationships in consumer demand for food commodities. |
M1 | M2 | M3 | |||
---|---|---|---|---|---|
Regressand Y | Regressors X | Regressand Y | Regressors X | Regressand Y | Regressors X |
GDPagr (Y1) | DS (X1.1) | FS (Y2) | GDPagr (X2.1) | Eagr (Y3) | GDPagr (X3.1) |
TQagr (X1.2) | DS (X2.2) | DS (X3.2) | |||
PRF (X1.3) | Eagr (X2.3) | ER (X3.3) | |||
PSP (X1.4) | Iagr (X2.4) | WFPI (X3.4) | |||
WFPI (X1.5) | ER (X2.5) | DEPI (X3.5) | |||
DEPI (X1.6) | Winf (X2.6) | DFPI (X3.6) | |||
DFPI (X1.7) | Dinf (X2.7) | Winf (X3.7) | |||
DEPI (X2.8) | Dinf (X3.8) | ||||
DFPI (X2.9) |
Years | Variables | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
GDPagr, $ Bln | DS, $ Bln | Eagr, $ Bln | Iagr, $ Bln | TQagr, % | FS, % | PRF, % | PSP, % | ER, RUB | WFPI, Rate | DEPI, Rate | DFPI, Rate | Winf, % | Dinf, % | |
1995 | 56.3 | 4.3 | 3.9 | 13.1 | 15.1 | 81.0 | 21.8 | 47.7 | 3.6 | 135.0 | 75.0 | 38.0 | 13.5 | 197.4 |
1996 | 61.5 | 4.9 | 4.5 | 16.4 | 16.9 | 83.0 | 21.8 | 48.6 | 5.1 | 120.0 | 98.0 | 23.0 | 9.0 | 47.8 |
1997 | 55.6 | 5.4 | 4.3 | 18.0 | 20.1 | 84.0 | 21.8 | 50.2 | 5.8 | 105.0 | 65.0 | 38.0 | 5.6 | 14.8 |
1998 | 54.9 | 2.5 | 3.7 | 14.6 | 16.7 | 83.0 | 21.8 | 57.3 | 9.7 | 95.0 | 93.0 | 55.0 | 4.4 | 27.7 |
1999 | 29.6 | 1.4 | 3.4 | 10.7 | 23.8 | 79.0 | 21.8 | 54.7 | 24.6 | 94.0 | 92.0 | 65.0 | 4.5 | 85.7 |
2000 | 28.9 | 1.9 | 4.5 | 9.6 | 24.4 | 86.0 | 6.7 | 51.6 | 28.1 | 97.0 | 69.0 | 80.0 | 4.0 | 20.8 |
2001 | 34.3 | 2.3 | 4.6 | 11.4 | 23.3 | 86.0 | 11.7 | 50.2 | 29.2 | 95.0 | 72.0 | 77.0 | 3.9 | 21.5 |
2002 | 34.1 | 1.9 | 5.8 | 12.4 | 26.7 | 87.0 | 11.7 | 53.8 | 31.3 | 100.0 | 100.0 | 100.0 | 2.9 | 15.8 |
2003 | 36.2 | 2.2 | 7.0 | 14.5 | 29.7 | 87.0 | 11.7 | 52.6 | 30.7 | 110.0 | 80.0 | 112.0 | 3.0 | 13.7 |
2004 | 45.5 | 2.7 | 7.9 | 16.5 | 26.8 | 87.0 | 11.7 | 47.9 | 28.8 | 115.0 | 103.0 | 117.0 | 2.9 | 10.9 |
2005 | 54.2 | 2.8 | 10.6 | 20.6 | 28.8 | 87.0 | 16.7 | 49.3 | 28.3 | 125.0 | 120.0 | 127.0 | 3.1 | 12.7 |
2006 | 59.4 | 4.1 | 12.7 | 24.2 | 31.1 | 86.0 | 15.8 | 48.1 | 27.2 | 155.0 | 110.0 | 162.0 | 3.1 | 9.7 |
2007 | 76.7 | 5.7 | 18.3 | 25.9 | 28.8 | 87.0 | 15.8 | 44.3 | 25.6 | 200.0 | 180.0 | 180.0 | 3.1 | 9.0 |
2008 | 100.2 | 9.6 | 18.1 | 33.9 | 26.0 | 86.0 | 14.8 | 43.4 | 24.9 | 155.0 | 120.0 | 175.0 | 4.9 | 14.1 |
2009 | 79.7 | 8.8 | 15.9 | 29.9 | 28.7 | 88.0 | 9.4 | 47.1 | 31.7 | 190.0 | 123.0 | 215.0 | 1.5 | 11.7 |
2010 | 86.4 | 8.6 | 15.8 | 37.3 | 30.7 | 86.0 | 8.3 | 48.3 | 30.4 | 230.0 | 140.0 | 203.0 | 2.8 | 6.9 |
2011 | 115.2 | 9.1 | 21.3 | 43.9 | 28.3 | 87.0 | 11.8 | 43.7 | 29.4 | 215.0 | 145.0 | 230.0 | 3.9 | 8.4 |
2012 | 113.8 | 9.2 | 26.0 | 41.7 | 29.7 | 89.0 | 12.1 | 43.2 | 30.9 | 205.0 | 140.0 | 220.0 | 3.1 | 5.1 |
2013 | 116.3 | 9.5 | 25.6 | 43.8 | 29.8 | 88.0 | 13.0 | 42.6 | 32.0 | 210.0 | 150.0 | 250.0 | 2.8 | 6.8 |
2014 | 84.2 | 8.1 | 18.9 | 36.7 | 34.8 | 89.0 | 16.2 | 41.4 | 44.5 | 200.0 | 130.0 | 270.0 | 2.8 | 7.8 |
2015 | 95.1 | 8.2 | 16.0 | 24.3 | 30.9 | 90.0 | 16.0 | 40.5 | 64.6 | 205.0 | 135.0 | 280.0 | 2.2 | 15.5 |
Variable | Coefficient | Relationship | Significance |
---|---|---|---|
Y1-intercept | 50,910.851 | ||
DS | 6.144 | Positive | The lowest positive |
TQagr | −1753.373 | Negative | The most negative |
PRF | 316.859 | Positive | The highest positive |
PSP | −284.492 | Negative | Low negative |
WFPI | −68.374 | Negative | The least negative |
DEPI | 222.632 | Positive | Average positive |
DFPI | 168.690 | Positive | Average positive |
Variable | Coefficient | Relationship | Significance |
---|---|---|---|
Y2-intercept | 81.660899 | ||
GDPagr | −0.000098 | Negative | The least negative |
DS | 0.000001 | Positive | The lowest positive |
Eagr | 0.000251 | Positive | Low positive |
Iagr | −0.000255 | Negative | Low negative |
ER | 0.054895 | Positive | Low positive |
Winf | 1.035337 | Positive | The highest positive |
Dinf | −0.077381 | Negative | The most negative |
DEPI | −0.025403 | Negative | Average negative |
DFPI | 0.043132 | Positive | Low positive |
Variable | Coefficient | Relationship | Significance |
---|---|---|---|
Y3-intercept | −9851.349 | ||
GDPagr | 0.207 | Positive | The lowest positive |
DS | −0.312 | Negative | The least negative |
ER | 177.309 | Positive | The highest positive |
WFPI | −1.480 | Negative | Low negative |
DEPI | 31.263 | Positive | Low positive |
DFPI | 15.147 | Positive | Low positive |
Winf | −60.227 | Negative | The most negative |
Dinf | 3.203 | Positive | Low positive |
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Erokhin, V. Factors Influencing Food Markets in Developing Countries: An Approach to Assess Sustainability of the Food Supply in Russia. Sustainability 2017, 9, 1313. https://doi.org/10.3390/su9081313
Erokhin V. Factors Influencing Food Markets in Developing Countries: An Approach to Assess Sustainability of the Food Supply in Russia. Sustainability. 2017; 9(8):1313. https://doi.org/10.3390/su9081313
Chicago/Turabian StyleErokhin, Vasilii. 2017. "Factors Influencing Food Markets in Developing Countries: An Approach to Assess Sustainability of the Food Supply in Russia" Sustainability 9, no. 8: 1313. https://doi.org/10.3390/su9081313
APA StyleErokhin, V. (2017). Factors Influencing Food Markets in Developing Countries: An Approach to Assess Sustainability of the Food Supply in Russia. Sustainability, 9(8), 1313. https://doi.org/10.3390/su9081313