Is a Food Shortage Coming to the Western Balkans?
Abstract
:1. Introduction
Paper | Material and Methods | Main Results |
---|---|---|
Acker et al., 2001 [24] | The paper analyzes the causes of the Balkan conflict linking food insecurity with political stability. | This research highlighted the role of agricultural education in post-conflict democratization. |
Papić-Brankov and Milovanović, 2015 [25] | Analysis of the Serbian food security system using Global Food Security Index Indicators. | The results showed the position of Serbia when food security is concerned and indicated two major weaknesses which influence the Serbian food system: low Gross Domestic Product per capita and corruption. |
Brankov and Lovre, 2017 [26] | The authors used the FAO package indicator to analyze the food security in the former Yugoslav republics. | The results showed that food security levels differ in analyzed countries, while Slovenia has the most favorable position when food security is concerned. |
Kovljenić and Raletić-Jotanović, 2020 [27] | Using multiple regression analysis, factors influencing food security in the former countries of Yugoslavia were analyzed. | The results showed that the general level of economic development, population growth, foreign trade, and agriculture investments significantly affect the level of food security. Additionally, results showed that Slovenia is the most nutritionally secure country, while the lowest level of food security has been observed in Bosnia and Herzegovina. |
Matkovski et al., 2020 [6] | Using the PROMETHEE method, Western Balkan and European Union countries are ranked according to food security. Also, factors affecting food security are estimated. FAO dimensions of food security are used. | The results show a significantly lower level of food security in the Western Balkan countries than in the EU. Also, results suggested that food security in the Western Balkans is not endangered, but it can become under crisis conditions. |
Božić and Nikolić, 2020 [28] | The food security system is analyzed using the Global Food Security Index for Serbia and neighboring countries: Bulgaria, Romania, Hungary, and Greece. | The results showed that Serbia lags behind the selected neighboring countries regarding food security. |
Brankov et al., 2021 [29] | The food self-sufficiency ratio is calculated for the South-East Europe countries. The influence of different factors affecting the self-sufficiency ratio is estimated. | The analyzed region showed a high level of food self-sufficiency, so it is ready to respond to crisis challenges. Also, this research highlighted regional cooperation, which should be strengthened. |
Đorđević et al., 2022 [30] | Theoretical presentation of food production in Serbia has been done since the arrival of Slavic tribes on the Balkan Peninsula up to modern times. | The results showed that although Serbia has been self-sufficient in food production throughout its history, there is space for improvement. |
Bogdanov et al., 2022 [31] | The report made a small attempt to evaluate the level of food self-sufficiency in the Western Balkan based on secondary data. | The results showed that all Western Balkan countries/territories, except Serbia, are net food importers. |
2. Materials and Methods
3. Results
3.1. Food Self-Sufficiency
3.2. Cereals Production and Demand
3.3. Fertilizers, Pesticides, and Irrigation Efficiency
3.4. Econometric Estimation of Input Use
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Coefficient | Std. Error | t-Ratio | p-Value | ||
---|---|---|---|---|---|
const | 0.00770808 | 0.0340386 | 0.2265 | 0.8223 | |
Fertilizers efficiency | 0.380233 | 0.0613847 | 6.194 | <0.0001 | *** |
Precipitation | 0.0406102 | 0.0336786 | 1.206 | 0.2367 | |
Arable land | 0.114664 | 0.0361433 | 3.172 | 0.0033 | *** |
Rural population | 0.655492 | 0.0517909 | 12.66 | <0.0001 | *** |
Temperature change | −0.0588534 | 0.0261677 | −2.249 | 0.0315 | ** |
Statistics based on the weighted data: | |||||
Sum squared resid | 35.31887 | S.E. of regression | 1.050578 | ||
R-squared | 0.979263 | Adjusted R-squared | 0.976022 | ||
F(5, 32) | 302.2225 | p-value(F) | 6.12 × 10−26 | ||
Log-likelihood | −52.52946 | Akaike criterion | 117.0589 | ||
Schwarz criterion | 126.8844 | Hannan-Quinn | 120.5548 | ||
Statistics based on the original data: | |||||
Mean dependent var | −0.107951 | S.D. dependent var | 1.120360 | ||
Sum squared resid | 2.103051 | S.E. of regression | 0.256360 | ||
Test for normality of residual— Null hypothesis: error is normally distributed Test statistic: Chi-square (2) = 4.24099 with p-value = 0.119972 | |||||
Pesaran CD test for cross-sectional dependence— Null hypothesis: No cross-sectional dependence Asymptotic test statistic: z = 0.746223 with p-value = 0.455533 |
Coefficient | Std. Error | t-Ratio | p-Value | ||
---|---|---|---|---|---|
const | 0.0109142 | 0.0340949 | 0.3201 | 0.7510 | |
Fertilizers efficiency | 0.337896 | 0.0601721 | 5.615 | <0.0001 | *** |
GDP PPP | −0.0590066 | 0.0289188 | −2.040 | 0.0496 | ** |
Arable land | 0.119326 | 0.0341963 | 3.489 | 0.0014 | *** |
Rural population | 0.691550 | 0.0495851 | 13.95 | <0.0001 | *** |
Temperature change | −0.0517610 | 0.0260480 | −1.987 | 0.0555 | * |
Statistics based on the weighted data: | |||||
Sum squared resid | 33.68589 | S.E. of regression | 1.026004 | ||
R-squared | 0.981108 | Adjusted R-squared | 0.978156 | ||
F(5, 32) | 332.3715 | p-value(F) | 1.38 × 10−26 | ||
Log-likelihood | −51.63003 | Akaike criterion | 115.2601 | ||
Schwarz criterion | 125.0856 | Hannan-Quinn | 118.7559 | ||
Statistics based on the original data: | |||||
Mean dependent var | −0.107951 | S.D. dependent var | 1.120360 | ||
Sum squared resid | 2.068543 | S.E. of regression | 0.254248 | ||
Test for normality of residual— Null hypothesis: error is normally distributed Test statistic: Chi-square (2) = 1.62587 with p-value = 0.443554 | |||||
Pesaran CD test for cross-sectional dependence— Null hypothesis: No cross-sectional dependence Asymptotic test statistic: z = −1.04505 with p-value = 0.295999 |
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Variable | Description | Source | Expected Relationship |
---|---|---|---|
F | Fertilizers efficiency | FAOSTAT | Positive |
G | GDP PPP | World Bank | Negative |
P | Precipitation | World Bank | Positive |
A | Arable land | World Bank | Positive |
R | Rural population | World Bank | Negative |
T | Temperature change | World Bank | Negative |
Dependent Variable | Joint Test on Named Regressors | Breusch–Pagan Test Statistic | Hausman Test Statistic |
---|---|---|---|
SSR_cereals | Chi-square (6) = 91.3096 p-value = 0.0000 | Chi-square (1) = 12.2268 p-value = 0.216493 | Chi-square (4) = 3.36118 p-value = 0.499297 |
Model I | Model II | |
---|---|---|
Const | 0.00770808 | 0.0109142 |
Fertilizers efficiency | 0.380233 *** | 0.337896 *** |
GDP PPP | −0.0590066 ** | |
Precipitation | 0.0406102 | |
Arable land | 0.114664 *** | 0.119326 *** |
Rural population | 0.655492 *** | 0.691550 *** |
Temperature change | −0.0588534 ** | −0.0517610 * |
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Brankov, T.; Matkovski, B. Is a Food Shortage Coming to the Western Balkans? Foods 2022, 11, 3672. https://doi.org/10.3390/foods11223672
Brankov T, Matkovski B. Is a Food Shortage Coming to the Western Balkans? Foods. 2022; 11(22):3672. https://doi.org/10.3390/foods11223672
Chicago/Turabian StyleBrankov, Tatjana, and Bojan Matkovski. 2022. "Is a Food Shortage Coming to the Western Balkans?" Foods 11, no. 22: 3672. https://doi.org/10.3390/foods11223672