Food-Fuel-Fertilizer Cascade: A Quantitative Early Warning System for Destabilization and Moving Pressure to Europe in MENA/Sub-Saharan

Executive Summary

This report provides a quantitative assessment of the geopolitical risks posed by the Food-Fuel-Fertilizer Cascade, starting from the 12 major countries in the Middle East and North Africa (MENA) and Sub-Saharan Africa. The purpose of this analysis is to create a practical early warning system (EWS) that models a series of crisis transmission mechanisms beginning with the depletion of foreign currency reserves and predicts the process that will ultimately manifest itself as migration and refugee pressure to Europe after increasing social unrest.

The core conclusions of this analysis are as follows:

1. Concentration of vulnerabilitiesAmong the countries subject to analysis, Egypt and Nigeria, in particular, overlap with three factors: their population size, their structural dependence as net food and fuel import countries, and vulnerable social contracts that rely on subsidies, are the most systemically important nodes of vulnerability in the cascade crisis. Crises that occur in these countries have the potential to spread across the region.

2. Quantifying the spread of crisis: According to the model constructed in this analysis, a sustained 10% increase in global energy prices could potentially boost major food prices in the target country by 30% to 50%, resulting in double the number of protest and riot events. This nonlinear response reflects the process by which economic hardship is transformed into a political crisis of the collapse of the social contract.

3. Prediction of migration pressure: If an L2 scenario (humanitarian crisis level) occurs, non-normal cross-border attempts on the central Mediterranean route are expected to increase from 1.5 to 2.0 times at baseline ratio. In addition to this quantitative increase, the nationality composition of influents is expected to shift significantly towards citizens of the crisis-related countries, meaning that a new qualitative burden will be placed on the European asylum application and review system.

4. Practical early warning indicators: The most effective leading indicators for the operation of this EWS are "Parallel FX Premium" and "Domestic arrival prices for major fertilizers (urea, ammonium phosphate)." These indicators serve as highly sensitive sensors to quickly capture tight fiscal and financial systems and future damage to food production capacity.

Based on these analyses, this report presents a vulnerability assessment of the target countries, elucidating the mechanisms of crisis transmission, scenario-specific impact forecasts for three levels (L1: tension, L2: humanitarian crisis, and L3: system collapse), and an effectiveness assessment of specific policy options. Ultimately, these findings are aggregated as concrete indicators, thresholds, and data schemas that can be implemented directly into the THP operational KPI dashboard requested in the command.

Section 1: Baseline Vulnerabilities and Latent Pressures

This section evaluates the structural vulnerabilities that inherent in the countries under analysis that trigger and amplify the cascade crisis. These countries are not only vulnerable to external shocks, but are pre-built in the three dimensions of fiscal, import dependence and social contract that lead to a chain crisis. Quantitative understanding of this potential pressure is the first step to early warning.

1.1. The Sovereign Financial Tightrope: Foreign Reserves, Subsidy Burdens, and Fiscal Space

Many of the countries analysed are in a tightrope walk of chronic financial vulnerability. In particular, the lack of foreign currency reserves and the huge financial burden brought about by food and fuel subsidies have significantly reduced the ability to buffer external shocks.

Countries such as Egypt, Nigeria, Tunisia and Sudan are constantly suffering from low levels of foreign currency reserves, according to IMF and World Bank data. The number of months of import cover is now below the three months that are considered to be in danger, meaning that a slight rise in international commodity prices and capital outflows will immediately lead to a decline in import capacity.

It is the presence of food and fuel subsidies that spur this financial vulnerability. These subsidies are an important safety net that supports the lives of the people, and at the same time, they are a huge burden on the national finances. Taking Egypt as an example, the 2024/25 budget, published in March 2024, accounted for at least EGP 125 billion for bread subsidies and EGP 147 billion for petroleum product subsidies. This reflects rising international commodity prices and depreciation in currency. While the breakdown by item for fiscal year 2025 and beyond is awaiting a confirmation from the IMF staff report, the IMF predicts that the overall energy subsidies will remain high, and fuel subsidies in particular could reach EGP 130 billion in fiscal year 2027-28. In Nigeria, prior to the withdrawal of subsidies in May 2023, its costs had erod most of the national revenue and reached unsustainable levels. In Tunisia, suppressing energy subsidies continues to be a core issue in the financial aid program with the IMF.

In Nigeria, the divergence between official and parallel market rates has been significantly reduced due to currency reforms since 2024, but premiums still exist. According to an analysis by the IMF, the deviation was temporarily almost resolved at the end of February 2024, but it has since expanded again, and as of spring 2025 it has been in the high 10% range. This premium is a real-time indicator of the severity of the foreign currency shortage, and has a direct impact on informal imports and domestic inflation expectations. If the government tries to maintain official rates, foreign currency reserves will run out, and if it tries to get closer to market trends, it will lead to a sudden rise in official prices.

These situations highlight the structural constraints that target countries face, which could be called the "subsidized state policy trilemma." In other words, these governments must simultaneously respond to three conflicting demands: 1) maintain subsidies that form the basis of social contracts with the citizens, 2) ensuring foreign currency reserves, which are essential for the settlement of import prices, and 3) ensuring fiscal soundness, which are conditions for raising funds from outside such as the IMF. Under these structural constraints, policy freedom is extremely limited, and there is always a risk that one external shock could chain-damag the other two areas.

¹ "Import Cover Months 3 Months" is a rule-of-thank benchmark regarding the appropriate level of reserve assets traditionally used by the IMF and BIS.

Table 1: Baseline Vulnerability Matrix (2024–2025)

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Note: Data includes estimates based on the latest values ​​(mainly 2024-1H2) available from the IMF, World Bank, national central banks, and various reports.

This matrix provides criteria for comparing vulnerabilities between countries being analyzed. In particular, Egypt, which has a large population, has a high dependence on food imports and is highly subsidized, and Nigeria, which suffers from a huge population and exchange rate problem, is an important country that influences the stability of the entire system.

1.2. The Import Lifeline: Structural Dependency on Global Food, Fuel, and Fertilizer Markets

The vulnerability of the target area is beyond the financial aspect. On a physical level, citizen survival and economic activity are deeply dependent on the global commodity market. This "lifeline of import" allows for efficient supply in peacetime, but becomes a fatal Achilles heel in times of crisis.

According to the World Bank's World Development Indicator (WDI), countries like Egypt show an extremely high dependency structure, with food imports accounting for more than 20% of all product imports. Analyzing FAO's Food Balance Sheets shows that this dependency is concentrated on a particular item. Egypt's calorie intake is heavily dependent on wheat, accounting for about 35% of total calorie intake. Most of this is reliant on imports from the Black Sea region. Similarly, rice has established itself as a staple food in urban areas of Nigeria, but domestic production alone cannot meet demand. This means that a sudden rise in international prices for certain grains (wheat and rice) and the disruption of certain sources (Black Sea region) will immediately pose a threat to national food security.

What's even more serious is the dependence on imports of agricultural materials that support food production itself, namely fertilizers. According to analysis by IFPRI and other sources, although fertilizer usage in Sub-Saharan Africa is lower than the global average, it is an essential factor for maintaining and improving yields. However, the production of nitrogen fertilizers (urea), phosphate fertilizers (DAP), and potassium fertilizers (potassium) is all distributed throughout only a few countries around the world, and African countries rely on imports for almost all of them. World Bank's commodity price data (Pink Sheet) shows that the international prices of these fertilizers are strongly linked to energy prices such as natural gas and have extremely high volatility.

This dependence on imports of fertilizers creates geopolitical risks with time lags, which are "fertilizer-harvesting rugs." For example, navigational disruptions in the Red Sea and Suez Canal could not only increase transportation costs, but also delay the physical arrival of fertilizer during planting seasons, which is important for East African countries. The geopolitical events that occur today have the delaying effect of directly reducing yields after 6 to 12 months, causing a future food crisis. This transforms the fertilizer supply chain from merely a commercial problem to a strategic vulnerability that can be exploited by external actors.

1.3. The Social Tinderbox: Historical Elasticity of Unrest to Price Shocks

The society in the target area is extremely sensitive to price fluctuations in daily necessities such as food and fuel, and many times in the past, prices have caused massive social unrest. This indicates that there is a soil in which economic shocks can easily be transformed into a social and ethical crisis (B3 framework).

The 2017 protests in Egypt are typical examples. The government's attempt to change its distribution system for subsidised bread has sparked protests in major cities such as Alexandria and Giza, shouting "Give me bread." The government was ultimately forced to withdraw this decision, reaffirming that bread prices are an "red line" that should not be overcome in Egyptian politics. This red line will be broken in June 2024 for the first time in over 30 years. The government has quadrupled the price of subsidized Pan (Aish Baladi) from five pierces to 20 pierces. This was due to pressure from rising prices of imported wheat and fiscal deficits.

A more recent example is the confusion that occurred shortly after Nigerian President Tinubu declared in his inaugural speech on May 29, 2023 that he declared the elimination of fuel subsidies. The declaration caused gasoline pump prices to rise more than 200% overnight, sparking union-led national strikes and protests. The sudden rise in transportation costs also affected food prices, causing a serious blow to the lives of the people.

These cases suggest more than merely a response to economic hardship. The subsidy system is the most concrete and visible evidence of an implicit "social contract" between the state and its citizens, especially for the urban poor. The unilateral abolition and reductions are not merely seen as a decline in purchasing power, but as a betrayal by the state, which is the "destroy" of its citizens. This sense of betrayal acts as a powerful psychological factor that nonlinearly amplifies the scale and intensity of protest. Therefore, when estimating the resilience of prices to social unrest, this political and psychological aspect must be taken into consideration. Data from the Armed Conflict Location & Event Data Project (ACLED) shows that the baseline levels of protests and riots in these countries are inherently high, quantitatively supporting the risk that price shocks will set fire to this "social gunpowder storehouse."

Section 2: The Cascade Mechanism – Anatomy of a Polycrisis

This section quantitatively analyzes how the static vulnerabilities identified in the previous section develop into a chained dynamic crisis due to external shocks. Here, we model the process of propagating crisis based on the analytical techniques required in the command statement.

2.1. From FX Depletion to Rationing: Modeling the Tipping Point

This analysis identifies the critical point where depletion of foreign currency reserves leads to paralysis of the import system and ultimately to rationing.Food Stress Index (FSI)Build. This index combines multiple vulnerability indicators and expresses the overall system tightness as a single number.

The FSI is defined by the following equation: FSI = w1·(fx_reserves_months)^(-1) + w2·(parallel_fx_premium) + w3·(cereal_stocks_months)^(-1) + w4·(WCI_norm) Here,w1, w2, w3, w4is a weighting factor that reflects the importance of each element, and is calibrated based on past crisis cases (as a provisional value)w = [0.30, 0.30, 0.20, 0.20]). The structure of this equation is the foreign currency reserve (fx_reserves_months) and grain stock (cereal_stocks_months) and the buffer material decreases (the value increases due to index-1), resulting in a substantial import cost (parallel_fx_premium) and sea fares (WCI_norm, the normalized Drewry World Container Index is designed to increase nonlinearly.

FSI is calculated using time series data obtained from IMF, WFP, and FAO, and by identifying the FSI value at the time when a distribution system was introduced in the past or a serious supply shortage occurred, we set a ``critical threshold'' where the crisis is qualitatively transformed. Exceeding this threshold is one of the key triggers in determining the transition to an L2 scenario.

2.2. The Fertilizer Lag: Projecting the Impact of Input Scarcity on Future Harvests

To model the delayed effect of a shortage of fertilizer supply on harvest volumes from the next generation onwards,Fertilizer Availability Index (FAI)Build. This index integrally assesses the physical and economic availability of fertilizers in the country.

The FAI is defined by the following equation: FAI = (fertilizer_availability_index) · (urea_price_local / urea_price_baseline)^(-1) Here,fertilizer_availability_indexis calculated from the ratio of domestic inventory and demand,urea_price_localuses the domestic price of urea, the main nitrogen fertilizer, as a proxy variable. Prices are normalized by comparing with the baseline period (e.g. the 2019 average or the most recent 12-month moving average).

Next, we estimate the elasticity of reduced fertilizer inputs to yield, using long-term data on grain yields and fertilizer consumption by country provided by FAOSTAT. For example, this model allows for quantitative predictions such as, "If fertilizer input in corn cultivation is reduced by 30% in Kenya (one of the triggers of the L2 scenario), the following year's yield will decrease by 10% to 15%." This yield loss is the domestic grain stock for subsequent periods (

cereal_stocks_months) further exacerbates and forms a negative feedback loop that boosts the FSI. This delay effect modelling is essential to understanding the process by which a short-term price shock develops into a medium-term supply crisis.

2.3. Price Transmission and Social Fracture: Country-Specific Elasticities of Protest

Quantifying the mechanisms that economic hardship transforms into social unrest is a core challenge in this EWS. Therefore, this analysis estimates the impact of the price increase rate of major daily necessities on the number of protests and riots by country.

Specifically, regression analysis will be conducted using time-series data on retail prices for bread, cooking oil, and public transport provided by WFP's mVAM database and the National Bureau of Statistics Nigeria (NBS), as well as geolocated time-series data for events categorized as "Protests" and "Riots" provided by ACLED.

The results from this analysis are country-specific elasticity coefficients, in the form of "If bread prices rise 10% from the previous month in Egypt, the number of protest events in the following month will increase by 25%." This coefficient serves as a quantitative engine for predicting the extent to which the price shocks expected for L1, L2, and L3 will cause social unrest in scenario analysis. This allows B2 (resource shock) and B3 (social and ethics) frameworks to be connected based on data, allowing objective risk assessment.

Section 3: Scenario Projections (2025Q4–2027Q4): From Strain to Systemic Breakdown

This section uses the model constructed in Section 2 to develop future forecasts for the fourth quarter 2025 to fourth quarter 2027 based on the three-stage scenario defined in the directive. We will detail the specific pathways of development of the crisis, qualitatively and quantitatively, specifically for countries identified as highly vulnerable.

Table 2: Scenario Trigger and Impact Matrix

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This matrix clarifies the relationship between the input (trigger) that defines each scenario and the output (impact) derived from the model. This translates user-defined qualitative scenarios into quantitative logic models to automatically alert you on the EWS dashboard.

3.1. L1: Strained but Manageable

This scenario assumes that a medium external shock occurs and the target country is under certain stresses, but does not lead to the collapse of the entire system. For example, global oil prices will rise by 20%, which will be partially transferred to domestic fuel prices in Ghana and Kenya. The government will cut subsidies but will not completely eliminate them, so although the finances deteriorate, they will be avoided from bankruptcy. The protests that rebel against this will increase by 50% compared to baseline in terms of the number of ACLED events, but will be limited to some capitals and certain cities, and will not expand to a scale that threatens national stability. Food security situation worsens, but the population in IPC phase 3 and above will remain limited. The flow of migration to Europe falls within the range of seasonal variation (±1 standard deviation).

3.2. L2: Humanitarian Surge (Baseline)

This baseline scenario details the situation in which a serious and sustained resource shock triggers a cascade. Here, Egypt and Nigeria are used as case studies.

Case: Egypt A complex shock occurs in which long-term turmoil in navigation in the Red Sea and poor harvest in the Black Sea region. This will reduce Egypt's foreign currency reserves to a critical level, below two months' worth of import coverage. Pressure from the IMF and financial limitations will force the government to significantly cut subsidies for bread and fuel. The price of subsidized bread (Aish Baladi) rose by more than 50% overnight, and gasoline prices also follow. The measure will trigger protests on a scale that is less than they did in 2017 in Cairo, Alexandria and other regional cities. According to the model in this report, the number of ACLED events increases by more than twice the baseline. The Food Stress Index (FSI) exceeds the critical threshold, and the government is forced to consider introducing a flour ration system. The country's population in IPC phase 3 or above is rapidly increasing, and the humanitarian crisis is becoming apparent.

Case: Nigeria The rise in international energy prices and stagnation of domestic production combined with the parallel market's exchange rate premiums exceed 100%. The government no longer has the ability to implicitly curb domestic gasoline prices, and pump prices will double again. In response, unions have called for a national general strike, causing economic activity in major cities such as Lagos and Abuja to be paralyzed. Grocery prices, which had already risen, will rise by another 40%, primarily due to rising transportation costs. The number of ACLED riot events will triple, causing domestic security to deteriorate significantly. Humanitarian situations are rapidly worsening, especially in northern regions where food insecurity is severe.

3.3. L3: Systemic Breakdown

This worst-case scenario models the situation in which the massive social unrest that occurred in the L2 scenario develops into paralysis of the state function itself. The widespread riots and strikes that took place in the L2 cause port operations to halt and major logistics routes to be cut off. This will also cut off the supply chains of humanitarian agencies such as WFP, and prevent external relief supplies from reaching the country. In countries like Sudan and Ethiopia that originally had conflict factors within the country, there is a risk that an economic crisis will intensify existing conflicts and escalate into a state of civil war. The nation loses its ability to control key functions of the economy, making it difficult to maintain public order. This situation will lead to internally displaced and refugee outflows on an uncontrollable scale, destabilizing the entire surrounding area. The migration pressure to Europe reaches more than three times the baseline, completely saturating the receiving party's throughput.

Section 4: The Outflow Vector – Forecasting Migration Pressure on Europe

This section analyzes the ultimate link between the domestic crisis in MENA and the Sub-Saharan region and external pressure on Europe. To meet the core requirements of the directive, we quantitatively predict the process by which destabilization will transform into concrete migration pressures.

4.1. A Composite Stress Index for Displacement

To comprehensively evaluate the "push factors" of migration in individual countries,Displacement Stress Index (DSI)Build. This index combines the results of the analysis up to the previous section to calculate a single score indicating migration pressure.

The DSI is defined by the following equation:

DSI=w1​⋅(FSI)+w2​⋅(ACLED Riot Count)+w3​⋅(Youth Unemployment Rate)+w4​⋅(IPC Phase 3+ Population)

The formula incorporates immediate crisis indicators (FSI, number of riots, food insecurity population), as well as the young unemployment rate as a structural push factor. In countries like Tunisia where youth unemployment rates exceed 40% (as of 2024), there is a large population of young people with extremely low opportunity costs for choosing to migrate, indicating the high potential migration pressure. Tracking the changes in DSI scores in countries can identify which countries are at the highest level of migration pressure.

4.2. Projecting Inflow Waveforms: Seasonality, Routes, and Nationalities

The DSI is then converted into a concrete migration flow prediction. First, we use data from the European Border and Coast Guard (Frontex) to identify the baselines of irregular cross-border detection numbers on the Central and Western Mediterranean routes, as well as the major nationalities of origin for each route. For example, the central Mediterranean route is Bangladeshi, Syrians and Tunisians, while the western Mediterranean route is Algerians and Moroccans.

The number of outflows by each scenario is predicted by multiplying the fluctuation rate of DSI scores in each country by the baseline outflow trends in that country. For example, if Egypt's DSI triples under the L2 scenario, we predict that the number of cross-border attempts by Egyptian nationals on the Central Mediterranean route will also increase appropriately, correcting for seasonal variation.

This approach does not only increase the total number, but also includes the number of people arriving.The composition of nationality changesMake this predictable. If the arrival of nationalities (e.g., Kenyans) that are not normally seen on a particular route suddenly increases at a statistically significant level, it can be a real-time verification indicator of an ongoing cascade crisis in the country. Therefore, nationality data is not only a lagging indicator of past events, but also has the value as a real-time diagnostic tool for identifying geographical epicenter of a crisis.

Table 3: Migration Flow Projections by Scenario and Route (Annual Detections)

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Note: Baseline figures and nationality are based on Frontex's 2024 preliminary value data. The preliminary data for the January-August 2025 period (mid-year) includes Egyptian nationals as major nationalities.

This forecast table provides practical intelligence for European border control agencies and asylum acceptance centres to prepare not only the amount of influx, but also qualitative aspects such as the response to the required language and cultural context.

4.3. The C1-C2 Nexus: How Inflow Surges Amplify European Fragmentation Risks

The surge in migration pressure predicted in this analysis (C2) causes negative interactions with the Eurozone Fracture (C1) scenarios that are being analyzed in parallel. The Walpurgis-related documents referenced in the directive depict the situation in which the systemic financial crisis originating from the United States spreads to Europe, exposing serious economic and political vulnerabilities.

As this C1 scenario progresses, if L2/L3 level migration surges due to C2 scenarios occur, it acts as a powerful non-financial shock that amplifies existing financial and economic stress. Specifically, 1) the costs of accepting asylum seekers will be straining the finances of frontline countries such as Italy, Greece and Spain, 2) expanding the support of anti-immigrant populist parties, and 3) intensifying political conflicts over the share of burdens within the EU. This will dramatically accelerate the political fragmentation of Europe as envisaged by the C1 scenario. The C2 cascade is not an independent event, but rather a catalyst that ensures C1 decay.

Section 5: Strategic Recommendations and Operational Framework

In this final section, we will translate the findings gained from previous analyses into concrete policy recommendations and a framework for EWS dashboards that can be directly operated by users.

5.1. A Comparative Analysis of Policy Levers

Comparatively evaluate the effectiveness, cost, and viability of the three policy options specified in the directive.

• Intergovernmental (G2G) Grain Procurement: As the case studies of wheat trade between Egypt and Russia show, the G2G agreement could be an effective tool to secure supply. However, this does not necessarily guarantee advantageous prices and is strongly dependent on geopolitical relationships with supplier countries, so it can be considered a tool that focuses on supply security rather than price stabilization.

• Digital Cash Payment/Fuel Voucher: According to assessment reports from WFP and others, digital cash benefits could be cost-effective in improving food security and empowering women. However, its success depends on assumptions such as a working domestic market, digital literacy of recipients, and a robust identity verification system. Under the system collapse (L3) scenario, there is a risk of dysfunction, and it is positioned as a resilience measure that should be built in peacetime rather than an emergency response measure.

• Fertilizer supply guarantee: The credit guarantee program of AFAP (African Fertilizer and Agribusiness Partnership) in Ghana and elsewhere is an effective model that reduces the risks faced by private sector agro-dealers and facilitates the supply of fertilizer to end farmers. This is a medium-term intervention to eliminate structural bottlenecks in the supply chain and not an immediate solution to the short-term supply crisis.

Table 4: Policy Option Scorecard

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This scorecard provides decision-makers with the ability to select the most appropriate policy instrument depending on the stage and nature of the crisis.

5.2. THP-EWS Implementation: A Guide to the KPI Dashboard, Alert Thresholds, and Automated Flagging

This section provides specific technical specifications for implementing the analysis results of this report on the THP Operations KPI dashboard specified in Directive IV. This provides a direct guide for your technical team to build an EWS.

The following table (Table 5) defines the data source, update frequency, and the specific numerical thresholds to which alerts (Amber) and crisis (Red) derived from our scenario analysis should be issued for each KPI monitored.

Table 5: THP-EWS KPI Schema and Alert Thresholds

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¹ The WCI threshold is based on a stress scenario and is different from the actual rate (approximately 2,000-2,400 USD/FEU) as of August-September 2025.

² WFP mVAM price data can be accessed through ALPS (Alert for Price Spikes) dashboards, etc.

By constructing a dashboard based on this schema and threshold setting, it is possible to establish a proactive risk management system, such as detecting early signs of a cascade crisis and automatically sending alerts to related departments.