Countries and international organizations seek to enhance food security amid numerous global threats. Recently, one of the most notable conflicts affecting global food security has been the Russia–Ukraine war. This study aims to assess the impact of the Russian-Ukrainian war on Egypt’s food security by comparing food product prices before and during the conflict, estimating a model to measure the war’s effect on food security levels during 2000–2022, and forecasting the future state of food security. Based on the estimated model, both the country’s food production capacity and real per capita income have a significant positive impact on the level of food security, while food prices exert a significant negative effect. Despite the repercussions of the Russian-Ukrainian war, Egypt’s food security index is expected to remain at a moderate level.
consumer pricesfuture predicting of food securityimport valueprices of food productsRussia–Ukraine conflictOngoing Research Funding program, King Saud University, Riyadh, Saudi ArabiaORF-2025-932The author(s) declared that financial support was received for this work and/or its publication. This work was supported by Ongoing Research Funding program, King Saud University, Riyadh, Saudi Arabia (ORF-2026-932).section-at-acceptanceAgricultural and Food EconomicsIntroduction
Food security remains one of the most critical challenges facing the global community in the 21st century, directly impacted by ecological, demographic, economic, and geopolitical factors. It is defined as the continuous availability of safe and nutritious food and the ability of individuals to obtain acceptable foods in socially appropriate ways without compromising dignity or cultural traditions (Arab Organization for Agricultural Development, League of Arab States, 2017). The foundational pillars of food security include availability, accessibility, acceptability, adequacy, and agency—the governance and policy frameworks that enable it (Arab Organization for Agricultural Development, League of Arab States, 2017). Amid global environmental and climatic changes, population growth, transformations in food systems, and ongoing conflicts, maintaining food security has become increasingly complex (Fanzo et al., 2017; Fujimori et al., 2019; Molotoks et al., 2021; Behnassi and El Haiba, 2022).
The ongoing Russia–Ukraine conflict represents a profound and urgent global shock with far-reaching implications for food security worldwide (Behnassi and El Haiba, 2022; Abay et al., 2023; Zhou et al., 2023). As two of the world’s largest exporters of major cereals, Russia and Ukraine together account for over one-third of global grain exports (Abdel Shafi, 2022). The outbreak of the war in February 2022 triggered immediate and severe disruptions. The FAO Food Price Index (FFPI) rose from 135.6 in January 2022 to 159.7 in March 2022, before gradually declining to 131.2 by January 2023 [Food and Agriculture Organization (FAO), 2023]. These price shocks have intensified food inflation and insecurity, particularly in low- and middle-income countries dependent on imports and among vulnerable populations that spend a large share of their income on food and energy (Lopez-Acevedo et al., 2022.
Regionally, the Middle East and North Africa (MENA) region bears disproportionate consequences. Inflationary waves in 2022 reached alarming levels, particularly in Lebanon (154%), Iran (43%), and Yemen (30%) (Lopez-Acevedo et al., 2022; Ministry of Planning and International Cooperation of the Republic of Yemen, Economic Studies and Forecasts Sector, 2022). These price surges are driven by rising global oil and food prices, trade disruptions, and logistical constraints intensified by the geopolitical conflict (Abdul Nabi, 2022; Molotoks et al., 2021). Furthermore, the war exacerbates food system vulnerabilities, exposing populations not only to hunger but also to nutritional deficiencies and malnutrition as dietary quality declines amid soaring prices and supply shortages (Information and Decision Support Center of the Egyptian Council of Ministers, 2022; Central Agency for Public Mobilization and Statistics, Population Statistics and Censuses Sector, 2022).
Egypt, the largest Arab nation with a population exceeding 100 million—about 22.6% of the Arab world’s total—and a net food importer, offers a critical case for examining the intersection of global conflict and domestic food security (Arab Organization for Agricultural Development, 2023). Egypt’s dependence on grain imports is substantial; in 2023, it imported roughly 8.16 million tons of wheat, primarily from Russia (67.5%) and Ukraine (11.9%), underscoring its vulnerability to disruptions in Black Sea trade [Food and Agriculture Organization (FAO), 2023]. The war’s impact on Egypt has been reflected in a sharp surge in consumer prices: the general Consumer Price Index (CPI) rose by 26.5% in January 2023 compared to the previous year, while food and beverage prices increased by nearly 48.1%, the highest among all consumption categories (Central Agency for Public Mobilization and Statistics, 2023) (see Figure 1).
The relative rate of change in the consumer price index in January 2023 compared to its counterpart in January 2022. Source: Central Agency for Public Mobilization and Statistics (2023).
Horizontal bar chart comparing expenditure categories, with food and beverages (48.1), restaurants and hotels (42.8), and culture and entertainment (30.6) as highest values, and communication as lowest (0.8).
Socioeconomic data reveal compounded vulnerabilities: about 73.9% of Egyptian households were aware of the war’s repercussions, 9.3% of household heads experienced employment changes—mainly in urban areas—and 19.8% reported income reductions due to unemployment shocks (Information and Decision Support Center of the Egyptian Council of Ministers, 2022). Nearly one-third of households lacked sufficient income to cover basic consumption needs, and up to 90% reduced protein intake in response to rising food prices driven by opportunistic mark-ups (Information and Decision Support Center of the Egyptian Council of Ministers, 2022; Central Agency for Public Mobilization and Statistics, Population Statistics and Censuses Sector, 2022). These findings underscore how global food supply shocks translate into severe national food insecurity risks.
Broader regional studies reveal complex trade and inflationary dynamics under conflict conditions. Ghanem A. M. et al. (2023) and Ghanem A. M. K. et al. (2023) identify significant statistical increases in the food CPI in Saudi Arabia, correlated with rises in the FFPI and demographic pressures. Their analysis shows that a 10% increase in the FFPI corresponds to a 6.98% rise in food import value and a 7.87% increase in the food trade deficit (Ghanem A. M. et al., 2023; Ghanem A. M. K. et al., 2023). Furthermore, diversification of grain import sources among Gulf Cooperation Council (GCC) members varies considerably, with Saudi Arabia, Oman, Qatar, and the UAE adopting multi-source strategies, while Kuwait and Bahrain maintain geographically concentrated sourcing, as reflected in Herfindahl–Hirschman indices (Ghanem Adel et al., 2024). Internationally coordinated efforts, such as the Black Sea Grain Initiative—signed by Russia, Ukraine, and Turkey under United Nations auspices—have aimed to stabilize grain exports through designated ports, inspection mechanisms, and secure passage corridors. However, geopolitical uncertainties persist, as demonstrated by Russia’s suspension and subsequent reinstatement of the agreement in 2022, highlighting the continued fragility of global food supply chains [Food and Agriculture Organization (FAO), 2023]. Methodologically, this study employs advanced econometric techniques appropriate for time series and panel data analysis, including ordinary least squares, generalized least squares, Durbin-Watson and Breusch-Godfrey tests for autocorrelation, and co-integration frameworks (Gujarati and Porter, 2009; Ismail, 2001; Dickey and Fuller, 1979; Johansen, 1996; Johansen and Juselius, 1992). The study employs the Global Food Security Index (GFSI) from The Economist, Global Food Security Index (2022), utilizing its multidimensional framework encompassing affordability, availability, quality and safety, and sustainability and resilience to provide a comprehensive assessment of national food security. This study therefore addresses the critical research question: What is the magnitude and nature of the Russia–Ukraine war’s impact on Egypt’s food security, and through which economic and supply-chain mechanisms are these effects transmitted? To answer this, the analysis examines: (1) the evolution of food security indicators and food prices before and after the conflict; (2) the econometric relationships between global shocks and domestic food production, import values, and consumer food prices; and (3) forecasts of Egypt’s food security trajectory through 2025 under current and scenario-based assumptions. By situating Egypt’s food security within the broader global system affected by conflict and trade disruptions, this study contributes to the empirical literature on conflict-induced food insecurity and informs policy interventions aimed at strengthening resilience in import-dependent economies confronting systemic shocks.
Materials and methodsTheoretical framework and conceptual foundation
This study is grounded in the theoretical framework of food security as defined by the Arab Organization for Agricultural Development, League of Arab States (2017) and operationalized through the Global Food Security Index (GFSI) published by The Economist, Global Food Security Index (2022). Food security is understood as the ability of individuals to access sufficient, safe, and nutritious food at all times for an active and healthy life. This multidimensional concept encompasses five core pillars: (1) Availability—the presence of adequate food supplies; (2) Accessibility—the physical and economic ability to obtain food; (3) Acceptability—the diversity, cultural suitability, and social appropriateness of food; (4) Adequacy—the sufficiency and sustainability of food in both quantity and quality; and (5) Agency—the policies, systems, and governance structures that enable and maintain food security (Arab Organization for Agricultural Development, League of Arab States, 2017). The economic rationale for this study draws on established principles in agricultural economics, macroeconomic theory, and international trade theory. Food security outcomes are shaped by the interaction of supply-side factors (domestic agricultural production capacity, input availability), demand-side factors (population size, income levels, prices), and external shocks (global commodity prices, geopolitical conflicts). The Russia–Ukraine war constitutes a major exogenous shock to global food supply chains, particularly for wheat, maize, barley, and sunflower oil—commodities in which both countries are key exporters [Abdel Shafi, 2022; Food and Agriculture Organization (FAO), 2023]. These disruptions transmit to import-dependent economies such as Egypt through higher international food prices, increased import costs, and domestic inflationary pressures, ultimately undermining household food access and national food security (Lopez-Acevedo et al., 2022; Ghanem A. M. et al., 2023; Ghanem A. M. K. et al., 2023).
Transmission mechanisms and theoretical foundations of the simultaneous-equation framework
The prevailing empirical literature on conflict and food security predominantly relies on single-equation or partial-equilibrium models that estimate reduced-form relationships between conflict events and isolated outcomes such as domestic food prices or composite food security indices. Representative examples include studies by Lopez-Acevedo et al. (2022), which examine food price inflation in MENA in response to global supply shocks; Ghanem A. M. et al. (2023) and Ghanem A. M. K. et al. (2023), which links the world food price index to domestic food consumer price indices in Saudi Arabia; and Abay et al. (2023), which assess overall food security outcomes during the Russia–Ukraine war. While these contributions provide valuable insights into average correlations, they suffer from several critical limitations that reduce their capacity to inform policy in import-dependent economies.
First, standard single-equation models treat key variables—such as domestic food production, consumer food prices, import values, and food security indices—either as purely exogenous regressors or as isolated dependent variables. This specification implicitly assumes weak or negligible interdependencies among these variables, which is empirically and theoretically inconsistent with the structure of food systems in countries with high import dependency such as Egypt. In reality, domestic production affects both the volume of imports needed and the level of domestic food prices, while food prices in turn influence household consumption patterns and overall food security outcomes. Similarly, global food price shocks affect the cost of imports, which feed back into domestic price inflation and food security status. By ignoring these feedback loops, single-equation models yield estimates that are subject to simultaneity bias—they confound direct effects of shocks with indirect effects transmitted through multiple channels—and therefore cannot decompose the conflict’s total impact into its production, price, and trade components (Gujarati and Porter, 2009).
Second, existing studies typically employ conflict dummy variables or composite global shock indices (e.g., the FAO Food Price Index) as exogenous drivers, with the implicit assumption that their impacts are homogeneous across different economic contexts. However, the transmission mechanisms vary substantially across countries depending on their degree of import dependence, the geographic concentration of import sources, the effectiveness of government subsidy programs, and the flexibility of domestic production capacity. For Egypt specifically, the highly concentrated import structure (67.5% of wheat sourced from Russia, 11.9% from Ukraine prior to the war) creates an acute vulnerability that general global models cannot adequately capture. Moreover, studies that focus exclusively on prices or single indicators of food security cannot reveal whether the conflict’s primary impact operates through availability (production), affordability (prices), or household purchasing power (real income), each of which requires distinct policy responses.
Third, conventional regression approaches cannot fully account for the dynamic and recursive nature of food system responses to external shocks. Once prices rise in response to import disruptions, for example, farmers’ production incentives may change, which subsequently affects future supply and trade volumes. These lagged adjustment processes and feedback mechanisms cannot be represented in static, single-equation frameworks.
In response to these limitations, the present study develops and estimates a system of four simultaneous structural equations that is explicitly grounded in three complementary economic theories: (1) agricultural production theory, (2) price transmission and demand–supply theory, and (3) import-demand and international trade theory. This theoretical architecture ensures that the model is not an ad hoc empirical construction but rather a coherent representation of the mechanisms through which geopolitical shocks propagate through food systems in import-dependent economies.
Equation 1—Food Production Equation (Production Theory Foundation): following the Cobb–Douglas production framework widely used in agricultural economics (Fanzo et al., 2017; Fujimori et al., 2019), domestic food production is modeled as a function of factor inputs (land, labor, water, and capital). This equation captures the availability dimension of food security: increases in production reduce import dependency and lower the pressure on both foreign exchange and domestic prices. The theoretical expectation is that each input exerts a positive, albeit diminishing marginal, effect on output.
Equation 2—Food Price Equation (Price Transmission and Demand–Supply Theory): building on established agricultural economics principles and international trade theory (Ghanem A. M. et al., 2023; Ghanem A. M. K. et al., 2023; Lopez-Acevedo et al., 2022), food prices are modeled as determined by the interaction of domestic supply, global commodity prices, population-driven demand pressures, and energy costs. The price equation explicitly captures how affordability and accessibility dimensions of food security are affected by the interplay of production, global shocks, and demographic factors. The theoretical rationale is that higher domestic production alleviates price pressure (negative relationship), while higher world prices and population growth exert inflationary pressure (positive relationships). Critically, this equation embeds the transmission of conflict-driven global price shocks into Egypt’s domestic markets, a relationship documented in prior work but which cannot be jointly analyzed with production and import responses in single-equation frameworks.
Equation 3—Import Demand Equation (International Trade Theory): the import equation is grounded in classical import-demand theory, which specifies that the volume and value of imports depend on the gap between domestic supply and demand, international relative prices, and the exchange rate. By modeling imports as a joint outcome (rather than an exogenous input), the system captures how production expansion substitutes for imports (reducing foreign exchange pressure) and how world prices transmit to the country’s trade balance. This equation reveals the trade vulnerability of Egypt and the mechanisms by which the Russia–Ukraine conflict disrupts external food security.
Equation 4—Food Security Index Equation (Multidimensional Framework): the fourth equation links production, prices, and real per capita income to the multidimensional Global Food Security Index (GFSI) adopted by Arab Organization for Agricultural Development, League of Arab States (2017) and operationalized by The Economist, Global Food Security Index (2022). This equation integrates all three theoretical foundations: production determines the availability pillar, prices determine the affordability/accessibility pillar, and real income captures household purchasing power and the effectiveness of social protection systems. By jointly specifying this equation alongside the others, the model traces how external shocks affect each dimension of food security and their combined impact on the overall index.
How the Simultaneous-Equation System Addresses Prior Limitations: Unlike conventional single-equation approaches, the proposed system allows for the following advances: (i) Joint estimation of interdependent outcomes, which yields consistent parameter estimates free of simultaneity bias; (ii) Decomposition of transmission channels, revealing whether the conflict’s impact operates primarily through production, prices, trade, or income effects—information critical for targeted policy responses; (iii) Explicit behavioral grounding, where each equation represents a distinct economic relationship derived from established theory, rather than a purely data-driven specification; and (iv) Counterfactual and scenario analysis, enabling policymakers to assess the relative effectiveness of different interventions (e.g., production expansion vs. income support vs. import diversification) in strengthening resilience.
The four-equation simultaneous system provides a theoretically coherent, empirically rigorous, and policy-relevant framework for quantifying conflict-driven food insecurity in import-dependent economies. It directly addresses the limitations of prior single-equation studies cited above and provides the foundation for the novel empirical contribution claimed in the introduction.
Global food security index (GFSI)
The study employs the GFSI as the primary metric for evaluating Egypt’s food security status. The GFSI is a composite index that assesses 113 countries using weighted sub-indices across four key dimensions:
1 Affordability (30.0%): Measures consumers’ capacity to purchase food and their susceptibility to price shocks, as well as the extent and effectiveness of public programs and policies designed to mitigate such shocks when they occur.
2 Availability (25.0%): Reflects the adequacy of national food supplies, the risk of supply disruptions, a country’s capacity to ensure consistent provision, and research efforts aimed at expanding agricultural production.
3 Quality and Safety (22.5%): Represents the diversity and nutritional quality of diets within a country, along with the rigor and enforcement of food safety standards.
4 Sustainability and Adaptation (22.5%): Reflects a country’s vulnerability to the impacts of climate change and natural resource risks, as well as its capacity to adapt and implement strategies that mitigate these threats.
Table 1 presents the detailed relative weights of the GFSI components, and Table 2 outlines the classification framework used to interpret different levels of food security.
The relative weight of Food Security Index components.
The scale
Relative weight %
Affordability of costs
30.0
Change in average cost of food
23.85
Proportion of population below the global poverty line
19.23
Inequality-adjusted income index
16.92
Agricultural trade
19.23
Food Security Nets Program
20.77
Availability
25.0
Access to agricultural inputs
11.71
Agricultural research and development
11.71
Farm infrastructure
9.01
Fluctuation of agricultural production
11.26
Loss of food
11.26
Supply Chain Infrastructure
9.91
supply sufficiency
11.71
Political and social barriers to access
10.81
Food security and access policy commitments
12.61
Quality and safety
22.5
Dietary diversity
19.5
Nutritional standards
20.33
Availability of micronutrients
19.51
Protein quality
20.33
Food safety
20.33
Sustainability and resilience
22.5
Risk exposure
17.0
Waters
16.5
lands
16.5
Oceans, rivers and lakes
15.5
Political commitment to resilience
19.0
Disaster risk management
15.5
Source: Global Food Security Index (2023).
The classification of food security levels.
Range
Description
80–100
Very good
70–79.9
Good
55–69.9
Moderate
40–54.9
Weak
0–39.9
Very weak
Statistical analysis: T-test for price comparisons
To evaluate the importance of price changes before and during the Russia–Ukraine war, this study applied an independent samples t-test (William, 2003). The t-statistic was computed using the following formula:
t=X¯1−X¯2(1n1+1n2)×(n1−1)σ12+(n2−1)σ22n1+n2−2
Where X¯1 and X¯2 represent the mean Consumer Price Index (CPI) for food products before and during the war, respectively; n1 and n2 denote the sample sizes; and σ12 and σ22 represent the variances. The calculated t-values were then compared with the critical values at the 1% significance level to determine statistical significance.
Econometric model specificationRationale for model choice
The proposed econometric model is structured to capture the complex interdependencies among key food security variables and their responses to the Russia–Ukraine conflict. A system of simultaneous equations was chosen over single-equation models for the following reasons:
1 Endogeneity concerns: food security determinants—including production, prices, and imports—are interrelated. For instance, domestic production affects import demand and prices, while prices affect consumption patterns and overall food security outcomes. Single-equation models would yield biased estimates because of simultaneity bias.
2 Behavioral realism: the model structure mirrors real-world economic behaviors and causal pathways through which external shocks propagate. Production capacity affects domestic prices and import requirements, global prices and population growth drive domestic inflation, and both production and prices jointly determine overall food security levels.
3 Policy relevance: the model facilitates scenario analysis and forecasting under various policy interventions, such as agricultural investment, production expansion, and import diversification.
Variable selection and theoretical justification
The model incorporates four endogenous variables capturing the core dimensions of Egypt’s food security system and nine exogenous variables representing structural determinants and external shocks.
Endogenous variables
Y₁: Food Production Index—Represents domestic production capacity, reflecting the availability dimension of food security. Higher production levels reduce import dependence and help stabilize prices (Fanzo et al., 2017; Fujimori et al., 2019).
Y₂: Consumer Price Index for Food Commodities—Reflects the affordability and accessibility dimensions of food security. Increases in food prices directly reduce household purchasing power and limit food access, especially among low-income populations (Lopez-Acevedo et al., 2022).
Y₃: Value of Food Imports (million USD)—Indicates supply stability and trade dependency. Economies reliant on food imports are more vulnerable to global price fluctuations and supply chain disruptions (Ghanem A. M. et al., 2023; Ghanem A. M. K. et al., 2023; Ghanem Adel et al., 2024).
Y₄: Egypt’s Global Food Security Index (GFSI)—A composite indicator representing the overall food security status, integrating the dimensions of availability, accessibility, quality, and sustainability (The Economist, Global Food Security Index, 2022).
Exogenous variables
X₁: Crop Area (million hectares)—Serves as a proxy for agricultural land resources; expansion of cultivated land enhances production capacity (Molotoks et al., 2021).
X₂: Agricultural Employment (million workers)—Represents labor input in agricultural production, reflecting the sector’s capacity and productivity (El-Agrody et al., 2010).
X₃: Irrigation Water (billion m3)—A vital input for crop production in arid regions such as Egypt, directly influencing yields and total output.
X₄: Agricultural Investments (million EGP)—Capital formation in agriculture promotes technological adoption, infrastructure development, and productivity improvements (Fujimori et al., 2019).
X₅: World Food Price Index—Captures global food price dynamics and their transmission to domestic markets through trade channels [Food and Agriculture Organization (FAO), 2023; Ghanem A. M. et al., 2023; Ghanem A. M. K. et al., 2023].
X₆: Total Population (million)—Reflects demographic pressure that increases food demand, affecting prices and import requirements (Molotoks et al., 2021).
X₇: Global Oil Prices (USD/barrel)—Affect transportation and input costs (e.g., fertilizers, fuel), thereby influencing overall production expenses (Ministry of Planning and International Cooperation of the Republic of Yemen, Economic Studies and Forecasts Sector, 2022).
X₈: Exchange Rate (EGP/USD)—Impacts import costs and domestic price levels of traded commodities (Ghanem Adel et al., 2024).
X₉: Real Per Capita Income (EGP)—Represents household purchasing power, which directly shapes food accessibility and dietary quality (Arab Organization for Agricultural Development, League of Arab States, 2017; Information and Decision Support Center of the Egyptian Council of Ministers, 2022).
Model equations
The econometric model consists of four structural behavioral equations:
Equation 1 models food production as a function of agricultural inputs—land, labor, water, and capital—following a Cobb–Douglas-type production framework.
Equation 2 defines food price inflation as determined by domestic production (negative relationship), global food prices (positive transmission), population pressure (demand-driven inflation), and energy costs.
Equation 3 models import demand as inversely related to domestic production and positively associated with global food prices and exchange rate depreciation.
Equation 4 represents the food security index as positively affected by production capacity and income, and negatively influenced by food price inflation. This model structure has not been previously applied in studies analyzing Egypt’s food security under geopolitical conflict, thereby offering a novel empirical contribution to the existing literature.
Estimation method
The model was estimated using Ordinary Least Squares (OLS) for each equation. The identification condition for simultaneous equation systems requires the matrix of endogenous variables to be triangular, with diagonal elements equal to 1 and all elements above the diagonal equal to 0 (Gujarati and Porter, 2009). Table 3 presents this matrix structure for the proposed model, confirming that the system meets the identification condition and can be consistently estimated using OLS.
Matrix of endogenous and exogenous variables.
Y₁
Y₂
Y₃
Y₄
X₁
X₂
X₃
X₄
X₅
X₆
X₇
X₈
X₉
1
0
0
0
-a₁
-a₂
-a₃
-a₄
0
0
0
0
0
-b₁
1
0
0
0
0
0
0
-b₂
-b₃
-b₄
0
0
-c₁
0
1
0
0
0
0
0
-c₂
0
0
-c₃
0
-d₁
-d₂
0
1
0
0
0
0
0
0
0
0
-d₃
The proposed model econometrically measures the impact of the Russia–Ukraine war on food security in Egypt. Comprising four behavioral equations, the model was developed based on the internal variables most affected by wars and economic crises. Given its reliance on time series data, several issues were anticipated in the behavioral equations, including residual autocorrelation—a statistical problem that violates the assumption of independence and can result in inaccurate parameter estimates. In this study, autocorrelation was tested using the Durbin–Watson test and the Breusch–Godfrey serial correlation Lagrange Multiplier test. The statistical software EViews was employed to detect autocorrelation by comparing the probability value (p-value) with the significance level (α). When the p-value exceeded the significance level, no autocorrelation was present in the residuals; conversely, when the p-value was lower than the significance level, autocorrelation was detected. To estimate parameters in cases where residuals exhibited autocorrelation, this study employed the generalized least squares method and the generalized difference method (Ismail, 2001).
Results
The current state of food security in Egypt can be assessed using the GFSI, which encompasses several dimensions: affordability, availability, quality and safety, and sustainability and adaptation. Since the GFSI has been calculated for 113 countries, including Egypt, beginning in 2012, this study’s analysis of food security was confined to the period 2012–2022. The food affordability index, measured on a scale from 0 to 100, ranged between 51.4 in 2018 and 72.9 in 2021, with an annual average of approximately 61.9 during 2012–2022 (see Figures 2, 3). The food availability index varied from 48.7 in 2013 to 61.5 in 2019, averaging 55.0 over the study period. The food quality and safety index ranged from 45.9 in 2022 to 59.0 in 2017, with an annual mean of 54.7. Lastly, the sustainability and adaptation index fluctuated between 40.6 in 2016 and 55.8 in 2022, with an annual average of 46.1 during the same period.
The evolution of the components of the Global Food Security Index for Egypt during the period 2012–2022. Source: The Economist, Global Food Security Index (2022).
Line chart comparing four categories from 2010 to 2023: Affordability in blue, Availability in orange, Quality and Safety in gray, and Sustainability and Adaptation in yellow. Affordability and Availability fluctuate between 50 and 70 percent, Quality and Safety remains steady near 55 percent, and Sustainability and Adaptation consistently lags below 50 percent but shows gradual improvement toward 2023.
The evolution of the Global Food Security Index score for Egypt during the period 2012–2022. Source: Data contained in Figure 2.
Bar chart showing annual percentage values from 2012 to 2022. Values fluctuate, starting at 53.8 percent in 2012, peaking at 58.5 percent in 2021, and measuring 56.0 percent in 2022.
Overall, Egypt’s GFSI ranged from 50.9 in 2018 to 58.5 in 2021, with an annual average of approximately 55.0 during 2012–2022. The coefficient of variation for the GFSI was calculated at 3.58, indicating that Egypt’s food security level remained relatively stable throughout the study period. Moreover, Egypt’s food security index during this period can be characterized as follows (see Table 4).
The food security index for Egypt during 2012–2022.
Years
2012–2013
2014–2016
2017–2019
2020–2022
Description
Weak
Moderate
Weak
Moderate
Source: Global Food Security Index (2023).
Figure 4 illustrates the changes in both Egypt’s GFSI score and its global ranking among 113 countries in 2022 compared with the period 2012–2021. Egypt’s GFSI score improved during 2012–2014 and 2016–2020, with increases ranging from 0.5 points in 2020 to 5.1 points in 2018. However, the score declined in 2015 and 2021 by 0.9 and 2.5 points, respectively. Egypt’s ranking in the GFSI also fell between 2012 and 2016 and again in 2021, with declines of five positions in 2016 and 11 positions in 2015.
The change in score and global ranking of Egypt according to the World Food Security Index in 2022 compared to the period 2012–2021. Source: Data contained in Figure 3.
Bar chart comparing the amount of change in degree (blue) and change in order (orange) from 2012 to 2021. Positive and negative values are presented for each year, with the largest increase in 2018 and the most substantial decrease in order occurring in 2015. Data values are labeled on each bar.Price comparison before and during the Russia–Ukraine war
To empirically evaluate the impact of the Russia–Ukraine conflict on domestic food prices, independent samples t-tests were performed to compare the mean food CPI values before the war (2000–2021) and during the war (2022–2023). The results are presented in Table 5. The t-test revealed a statistically significant rise in food prices during the conflict period (t = 5.23, p < 0.01), with the mean CPI increasing from 162.4 (SD = 42.3) before the war to 198.7 (SD = 51.6) during the war. This result aligns with regional evidence identifying the Russia–Ukraine conflict as a major catalyst of unprecedented food inflation across the Middle East and North Africa (MENA). Lopez-Acevedo et al. (2022) reported that average food inflation in the region reached 14.8%, with extreme cases observed in Lebanon (154%), Iran (43%), and Yemen (30%).
Test (t) of the significance of the difference between the average consumer price index of food products before and during the Russian-Ukrainian war.
Commodity group
Average price index of food products
σ2
t-value
January 2021–January 2022
February 2022–January 2023
January 2021–January 2022
February 2022–January 2023
General price index
114.42
133.60
9.81
39.73
9.76
Food and beverages
105.09
135.40
23.06
81.90
10.58
Cereals and bread
98.89
142.70
10.16
187.70
11.22
Meat and poultry
104.64
133.50
16.60
92.48
9.91
Fish and seafood
101.25
134.00
2.80
109.70
11.14
Dairy, cheese, eggs
106.73
141.40
24.37
252.20
7.50
Oils and fats
122.95
163.60
193.70
77.51
8.64
Fruits
125.18
137.70
64.29
48.90
4.15
Vegetables
98.06
121.30
141.63
153.10
4.79
Sugar and sugary foods
96.10
119.40
23.58
21.01
12.31
Other food products
95.32
118.91
6.05
97.54
8.35
Source: data contained in Figure 5.
Recent studies highlight that the conflict’s impact extends beyond immediate price shocks. The disruption of Black Sea grain exports—which previously accounted for about 30% of global wheat and barley supplies—has generated sustained volatility in international markets (Behnassi et al., 2023). In Egypt, the government raised the price of subsidized bread from 5 to 20 piasters in June 2024—the first increase in more than three decades—affecting roughly 70 million citizens dependent on food subsidies (Al Arabiya, 2024). This policy adjustment underscores the growing difficulty of maintaining subsidy programs amid escalating import costs, a pattern observed across numerous import-dependent nations (Smith, 2024, in paper) (see Figure 5).
Average consumer price index (CPI) of food products before and during the Russian-Ukrainian war. Source: Central Agency for Public Mobilization and Statistics (2023).
Horizontal bar chart comparing price indices for food categories and the general price index before and during the war, showing significant increases during the war, especially in oils and fats, cereals and bread, and fruits.Estimation of the simultaneous equations model
The estimated coefficients of the four-equation simultaneous system are reported in Table 6. All equations exhibit strong explanatory power, with R2 values ranging from 0.89 to 0.99, and meet standard diagnostic criteria for model adequacy. The equations were estimated using Ordinary Least Squares (OLS), incorporating autoregressive correction terms AR(1) where necessary to resolve issues of serial correlation.
Estimated equations of the model for the period 2000–2022.
Source: statistical analysis of the data used in this study.
Food production index
The estimated equation for domestic food production is Equation 5:
LnŶ1=0.595+1.251LnX1+0.209LnX2+0.038LnX4
All input variables have positive and statistically significant effects on food production. Crop area (X₁) exhibits the strongest influence, with an elasticity of 1.251, indicating that a 1% increase in cultivated land leads to a 1.25% rise in food production. This finding suggests increasing returns to scale from land expansion, likely due to Egypt’s capacity to convert underutilized agricultural areas into productive land through reclamation initiatives.
Agricultural employment (X₂) has an elasticity of 0.209, indicating that labor remains a key factor in Egypt’s agricultural sector, though its marginal productivity is lower than that of land—consistent with labor-intensive production systems in developing economies. Agricultural investment (X₄) exhibits a positive but relatively small elasticity of 0.038, suggesting that while capital formation enhances production capacity, its effects may emerge over longer periods or require complementary factors such as technological innovation and infrastructure development to reach full potential.
Notably, the irrigation water variable (X₃) was excluded from the final model specification, likely due to multicollinearity with crop area or limited time-series variability in water availability. This finding underscores the critical yet constrained role of water resources in Egypt’s arid agricultural context.
These findings are consistent with agricultural production theory, emphasizing that improving domestic food availability requires focusing on land expansion and enhancing labor productivity. Recent research highlights the vital role of domestic production growth in conflict-affected food systems. The Global Report on Food Crises (FSIN and GNAFC, 2024) indicates that 349 million people across 79 countries face acute food insecurity—an increase of 200 million from pre-COVID-19 levels—driven largely by supply disruptions caused by the Ukraine conflict and climate shocks. For Egypt, boosting domestic wheat production is crucial to reducing import dependency; however, the country’s arid climate and limited water resources pose significant challenges, underscoring the need for climate-smart agricultural technologies and efficient irrigation systems [Swedish International Agricultural Network Initiative (SIANI), 2023; Ghanem, 1999; Talebian et al., 2024].
This equation shows exceptional explanatory power (R2 = 0.99), indicating that the included variables effectively capture food price dynamics in Egypt. Domestic food production (Y₁) has a negative elasticity of −0.249 (p < 0.01), consistent with the theoretical expectation that greater domestic output eases inflationary pressures by reducing import dependence and expanding market supply. This finding reinforces the policy focus on strengthening production as a central strategy for price stabilization.
The world food price index (X₅) exhibits a positive elasticity of 0.156, indicating that international commodity price shocks are transmitted to Egypt’s domestic food markets. Although the pass-through coefficient is moderate compared with the full transmission reported in some studies, it suggests that Egyptian consumers are partially shielded from global price volatility, likely due to government subsidies and price controls. However, this protection imposes a considerable fiscal burden on the national budget. Population growth (X₆) exerts the strongest positive effect, with an elasticity of 1.034, indicating that demographic expansion drives demand-side inflationary pressure. A 1% rise in population results in a slightly greater than proportional (1.03%) increase in food prices, reflecting the heightened demand in a rapidly growing population exceeding 105 million by 2024. This finding aligns with Malthusian concerns that population growth may outpace the capacity of food supply systems.
The significant AR(1) term (0.857) indicates strong price persistence and gradual adjustment dynamics in Egypt’s food markets. This autoregressive component suggests that current food prices are strongly affected by those of the previous period, reflecting structural rigidities, adaptive expectations, and lagged transmission of shocks. These findings align with recent empirical evidence on the pass-through effects of international commodity price volatility to domestic food markets. Ghanem A. M. et al. (2023) and Ghanem A. M. K. et al. (2023) reported that a 10% rise in the FAO Food Price Index resulted in a 1.22% increase in Saudi Arabia’s food CPI, while Ghanem Adel et al. (2024) identified similar transmission mechanisms across GCC countries. The conflict’s influence on fertilizer prices constitutes an additional inflationary channel, as Russia and Belarus—major global fertilizer suppliers—have driven a near doubling of fertilizer costs since 2020, thereby increasing production expenses for Egyptian farmers operating under fertilizer-intensive, arid conditions (Smith, 2024, in paper).
Value of food imports
The import value equation is estimated as Equation 7:
This equation provides key insights into Egypt’s import behavior and external vulnerability. Domestic production (Y₁) shows a strong negative elasticity of −1.842 (p < 0.01), indicating substantial substitution effects between domestic supply and imports. A 1% increase in domestic food production results in a 1.84% decrease in import value, demonstrating that production expansion is highly effective in lowering foreign exchange expenditure and reducing import dependency. This more-than-proportional substitution effect suggests that increased domestic output not only replaces imported quantities but also diminishes demand for higher-value imported processed foods and specialty products.
The world food price index (X₅) exhibits a near-unity positive elasticity of 0.931, confirming that increases in international prices translate almost directly into higher import expenditures. Combined with Egypt’s concentrated import structure—67.5% sourced from Russia and 11.9% from Ukraine before the war—this high elasticity highlights the country’s acute vulnerability to global market shocks and supply disruptions originating in the Black Sea region. Population growth (X₆) shows a positive elasticity of 0.404, indicating that demographic expansion exerts upward pressure on import demand as domestic production struggles to meet rising consumption needs. The significant AR(1) coefficient (0.425) suggests moderate persistence in import expenditures, likely driven by long-term trade contracts, shipping delays, and institutional rigidity in import structures.
These findings underscore the substantial fiscal strain the conflict has placed on food-importing nations. Egypt’s import bill has surged due to both higher unit prices and increased transportation costs, as the country now procures wheat from more distant suppliers following disruptions in the Black Sea region (Smith, 2024, in paper). Recent evidence also points to growing geopolitical fragmentation as a key obstacle to global food trade. Since Russia’s 2022 invasion, governments have enacted 67 new trade measures, including 38 export bans and licensing restrictions, further intensifying global challenges related to food accessibility and affordability (Stockholm Environment Institute, 2024). For Egypt, diversifying import sources and expanding strategic grain reserves are essential policy priorities to mitigate future supply shocks.
This equation integrates the various pathways through which economic and agricultural factors shape overall food security outcomes. Production capacity (Y₁) exerts a positive and significant influence on food security, with an elasticity of 0.227 (p < 0.01), confirming that higher domestic agricultural output enhances the availability dimension of food security. However, the relatively modest magnitude of this coefficient indicates that production growth alone is insufficient to meaningfully improve food security without simultaneous advancements in accessibility and household purchasing power. Food price inflation (Y₂) exhibits a negative but relatively small elasticity of −0.074 (p < 0.05), indicating that rising food prices weaken food security by diminishing affordability and accessibility, especially among low-income households. The modest magnitude likely reflects the mitigating influence of government subsidy programs that shield vulnerable populations from price shocks, although these measures impose substantial fiscal burdens on the state.
Real per capita income (X₉) shows the strongest positive effect, with an elasticity of 0.664 (p < 0.01), underscoring that economic development and household purchasing power are the primary drivers of improved food security. A 1% rise in per capita income results in a 0.66% increase in the food security index, highlighting that sustained economic growth, job creation, and poverty reduction are vital complements to agricultural production policies.
The significant AR(1) coefficient (0.432) indicates moderate persistence in food security status, reflecting the gradual pace of food system transformation and the lagged effects of policy interventions.
These findings confirm that food security outcomes depend fundamentally on the interaction between availability (production), accessibility (prices and income), and purchasing power. According to the FAO’s (2024) Regional Overview for the Near East and North Africa, 66.1 million people—14% of the Arab region’s population—faced hunger in 2023, while 186.5 million (39.4%) experienced moderate or severe food insecurity (FAO, 2024). Conflict remains the leading driver, with undernourishment rates in conflict-affected countries reaching 26.4%, — compared with 6.6% in non-conflict areas. Egypt’s moderate GFSI score reflects its intermediate standing: although it has avoided the extreme food crises seen in Yemen and Sudan, persistent vulnerabilities remain, particularly in affordability and dietary quality (WFP, 2025).
It should be noted that the model’s equations are free from residual autocorrelation, as confirmed by the Durbin–Watson test, and there is no evidence of heteroscedasticity based on the ARCH test results. Overall, the equations in the estimated model effectively represent the data used in the analysis, as indicated by model efficiency measures such as Theil’s inequality coefficient, which is approximately zero (Table 7).
Indicators for measuring the efficiency of the estimated model equations during the period 2000–2022.
Indicator
Equation
1
2
3
4
Root mean squared error
0.031
0.131
0.137
0.034
Mean absolute error
0.025
0.108
0.106
0.026
Mean abs. percent error
0.562
2.930
1.224
0.671
Theil inequality coef.
0.003
0.015
0.008
0.004
Source: equations of the estimated model in this study.
Finally, this study projected Egypt’s food security status for 2025 by estimating the endogenous and exogenous variables of the model describing the impact of the Russia–Ukraine war on food security. General trend equations were employed to forecast the exogenous variables (Table 8) and to assess their predictive accuracy using the indicators presented in Table 9. The endogenous variables were subsequently estimated by substituting the predicted values of the exogenous variables into the model equations. Based on the effects of the Russia–Ukraine war on both endogenous and exogenous factors, Egypt’s food security index is expected to remain moderate, increasing from 56.0 in 2022 to 60.06 in 2025. This improvement is attributed to the country’s horizontal and vertical agricultural expansion policies, implemented within the framework of available economic resources and aligned with Egypt’s Agricultural Strategy 2030.
Estimated general trend equations for explanatory variables included in the proposed model during the period 2000–2022.
** Significant at the probability level 1%. Source: data in this study.
Indicators for measuring the efficiency of the general trend equations estimated for the explanatory variables included in the proposed model.
Variables
Indicator
Root mean squared error
Mean absolute error
Mean abs. percent error
Theil inequality coef.
Crop area
0.030
0.026
0.963
0.006
Agricultural employment
0.352
0.280
4.136
0.024
Agricultural investments
0.349
0.282
12.476
0.067
World Food Price Index
0.190
0.167
3.699
0.021
Total population
0.008
0.007
0.167
0.001
Real per capita income
0.029
0.022
0.278
0.002
Source: equations in Table 8.
Among Egypt’s most important horizontal agricultural expansion initiatives are the New Delta Project, covering 700 thousand hectares; the South Valley Development Project (Toshka Al-Khair), spanning 460 thousand hectares; the North and Central Sinai Development Project, encompassing approximately 200 thousand hectares; and the Egyptian Rural Development Project, extending over 630 thousand hectares. Additional projects are also being implemented across Upper Egypt and the New Valley, covering a combined area of 270 thousand hectares. Vertical agricultural expansion, by contrast, is pursued through the development of high-yield crop varieties, the adoption of modern agricultural practices, the expansion of protected cultivation, and increased investment in the agricultural sector. The total volume of agricultural investments is projected to reach 36.96 billion Egyptian pounds by 2025 (see Table 10).
Predictive values of endogenous and exogenous variables of the proposed model until 2025.
Variables
2023
2024
2025
Crop area in million hectares
6.97
7.05
7.12
Agricultural employment in million workers
5.64
5.12
4.55
Agricultural investments in billion pounds
31.19
33.95
36.96
World Food Price Index
132.82
137.55
142.45
Total population in million
103.65
106.06
108.53
Real individual income in thousand pounds
3854.51
3928.45
4003.80
Food Production Index
104.35
104.00
103.19
Consumer Price Index for Food
243.04
250.45
258.39
Food Security Index
58.98
59.55
60.06
Source: data in Tables 6, 8.
Conclusion
This study examined how the Russia–Ukraine conflict transmits through production, price, and trade channels to influence Egypt’s food security, using a novel simultaneous-equation modeling framework. The analysis shows that strengthening domestic agricultural production is the most effective safeguard against global supply shocks, as it reduces import dependence and moderates price volatility. At the same time, increasing household incomes is crucial to maintaining affordability and ensuring access to diverse, nutritious diets amid ongoing inflationary pressures. Policy pathways derived from these findings underscore the need to integrate climate-smart agricultural practices—such as precision irrigation and drought-tolerant crop varieties—with strategic grain reserve management and diversification of import sources. When complemented by targeted social protection programs and inclusive economic growth strategies, these measures can strengthen resilience and ensure stable food access for vulnerable populations. Beyond Egypt, this framework provides a replicable model for other import-dependent nations aiming to quantify the effects of geopolitical disruptions on food systems and develop targeted resilience strategies. By integrating rigorous econometric modeling with sustainable food systems policy, this study enhances understanding of how global conflicts intersect with national food security challenges and offers a pathway toward more resilient and adaptive agricultural economies.
Data availability statement
Publicly available datasets were analyzed in this study. This data can be found here: Central Agency for Public Mobilization and Statistics.
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Edited by: Ping Huang, GuiZhou University of Commerce, China
Reviewed by: Yasmen S. Abdelrazek, Faculty of Agriculture Saba Basha, Egypt
Noorhan Gamal, Pharos University in Alexandria, Egypt