Methodology

The Challenge

Nearly a quarter of all food crosses international borders, with crop trade doubling in two decades. Yet, over 90% of global food exports come from fewer than 10 countries, leaving millions dependent on fragile trade corridors increasingly threatened by climate change, water scarcity, and conflict. The Jameel Index reveals that 55% of countries face vulnerabilities in their food imports, as seen during events like the Russian invasion of Ukraine, which disrupted markets, raised prices, and pushed households into hunger.

Food trade relies on three key actors:

1. National leaders who set tariffs, reserves, and trade policies;
2. Private-sector players who allocate capital and logistics based on risk; and
3. Multilaterals and NGOs who respond with policies, funding, and relief.

However, these decisions often rely on incomplete or outdated data.

When crises like droughts or export bans strike, leaders must act quickly to identify at-risk countries, crops, and populations. Yet, fragmented data sources fail to capture cascading effects across borders, leading to reactive measures like export bans, misallocated resources, and skyrocketing food prices. With shocks becoming more frequent and severe, timely, forward-looking insights are critical to safeguarding global food security.

Vision

We envision a world where governments, companies, and agencies can predict food-trade disruptions, strengthen fragile links, and ensure affordable nutrition for all. The Jameel Index transforms agronomic, economic, climate, and geopolitical data into a clear measure of food-trade vulnerability. Delivered via a web dashboard, it reveals how shocks in one region impact import-dependent nations, nutrition, and economies, guiding leaders toward preventive policies, trade diversification, and strategic investments for global food security.

Background

The Jameel Index measures food security in the context of trade. The goal of the Index is to provide policy- and decision-makers with insights concerning the threats posed by climatic and other global changes to food trade as well as the potential, resultant impacts to national food security. Thus, it does not represent an index of food security per se, but rather serves as a measure of food security risk as it relates to trade. This focus provides a lens through which policy- and decision-makers can better understand how varied factors affect and will affect the ability to import food and how these factors combine to impact key dimensions of food security.

The intent was to draw on readily available data but compile and organize it in a novel and transparent way that adds richness to the multidimensional question of what constitutes vulnerability to dependence on food imports.

The Jameel Index seeks to capture a broad spectrum of the vulnerabilities to a nation’s food imports. Therefore, it cannot be described by any single indicator, but rather as a composite index. Adger et al., 2004 as suggests:

The most common, quantitative vulnerability assessment method is the employment of a composite index comprising a set of indicators. These indicators represent the vulnerability of a studied system and are mathematically combined into a single composite index.

Given that the Jameel Index will combine both biophysical and socioeconomic dimensions of food trade to assess current vulnerability and future global change scenarios, a composite index is suggested. Composite indices are commonly used for assessing climate change vulnerability (Eakin and Luers, 2006, Füssel and Klein, 2006, Soares et al. 2012, Wirehn, et al ,2015)

In developing the Jameel Index, the experience and guidance of the UNDP in Measuring human development: A primer (UNDP 2007, page 20) has been applied:

Composite indices have their limitations, but they can still be used with care to advocate policies and promote accountability. They should be simple to interpret, transparent in methodology, able to display complex and multidimensional issues, and useful in benchmarking performance and assessing policies. In general, a composite index is a unit- less number that combines various indicators or statistics to convey a larger picture. A composite index is formed when individual indicators are compiled into a single index on the basis of some underlying model. Ideally, a composite index should measure a multidimensional concept that cannot be captured by a single indicator alone—such as poverty, competitiveness, sustainability, market integration, etc. For human development, the main composite index is the HDI, which combines attributes of health, education and income.

Composite indices should not be seen as an end in themselves, rather they should be seen as opportunities to initiate discussion and debate on policy, bearing in mind their inherently limited scope and inability to show causality (UNDP 2007).

Enhanced framework for the Jameel Index

For the Jameel Index we have expanded the classic taxonomy of composite indices of where “individual indicators are compiled into a single index” (Greco et al 2019) to a recursive framework where meta- indicators are assimilated into a single index. The meta-indicators are themselves composite indices focused on a single component related to food imports formed from summation across commodities of weighted indicators and normalized as illustrated in Figure 1.

To avoid a concern expressed in the literature that “[c]omposite indices may, however, invite simplistic policy conclusions if they address only the ‘big picture’ and ignore specific indicators (Saisana and Tarantola, 2002 page 5),” the Jameel Index output will present not only the final single composite index, but will also provide all the meta-indicator values that went into the Index. This will allow users to explore or investigate indicators specific to their own use cases.

The Five Meta-Indicators

The five meta-indicators are introduced below and are described in detail in the next section.

The criteria for selecting meta-indicators was to have a few as possible that cover the major elements that impact the food trade aspects of food security. The Five meta-indicators selected map directly to three of the six dimensions of food security (Table 2). The five meta-indicators were vetted by a panel of twelve food policy and trade experts in a series of three virtual and one in-person workshops.

Meta-indicators are developed based on five trade related Topical Indicators listed in Table 2. They will be described in detail in the next section.

#	Topical Indicator	Food Security Dimension
1	Food Import Dependency Ratio	Availability, Access
2	Feed Import Dependency Ratio	Availability, Access
3	Food Import to Foreign Exchange Ratio	Stability
4	Exporter Reliability	Stability
5	Supply Chain Robustness	Stability

From Meta-Indicators to the Jameel Index

The topical indicators are first calculated for each of eight key traded agricultural commodities chosen for the Index. The eight commodities included in the Jameel Index are:

1. Wheat
2. Maize
3. Rice
4. Soy
5. Dairy
6. Meat
7. Sugar
8. Oils

These eight are in the top ten of the key traded agricultural commodities related to nutrition and hunger as defined by the Food Consumption Score (WFP, 2008) and in the top ten in value and/or volume (WTO, 2023).

The primary data sources for the indicators come from FAOSTAT and the UN Comtrade databases. Some indicators use modeled data and will be presented in the discussion on each indicator. The indicators for each of the eight commodities are calculated from the raw data. For example, import dependency ratio for wheat for a country takes the import quantity and divides it by the total demand in the country to produce a ratio. The ratio for each commodity is then weighted and summed to produce the meta-indicator for the country. The details of weighting for each indicator are presented in the next section.

From Continuous to Categorical Meta -Indicator

The meta-indicators have different units of measurement, which require normalization before aggregation into a composite index. For the Jameel Index, the normalization process involves mapping the meta- indicators into a five-tier vulnerability classification system, illustrated below in Figure 2. The classification is meant to reflect how vulnerable a country’s food security might be for a given level of the meta-indicator. For example, a score of .9 on the Food Dependency Import Ratio would translate to an EXTREME vulnerability while a score of .1 would be a VERY LOW vulnerability.

The determination of the levels of meta-indicator scores to the five-vulnerability classification was a complex and comprehensive process:

Step	Description
1	A comprehensive review of the food security and trade literature to identify key vulnerabilities and establish theoretical foundations for the index framework.
2	Statistical analysis of global food trade data from FAOSTAT and UN Comtrade databases to identify patterns, correlations, and critical thresholds for vulnerability assessment.
3	Jameel Index development team collaboration with international food security experts to refine indicator selection and weighting methodologies through iterative design processes.
4	Expert elicitation through three virtual workshops and one in-person workshop with a panel of twelve leading food policy and trade experts to validate the index framework and threshold determinations.
5	Survey responses and feedback collection from additional stakeholders including policymakers, practitioners, and researchers to ensure the index meets real-world application needs and usability requirements.

Using the Jameel-1 thresholds, the meta-indicators were mapped from continuous raw scores to categorical classes in two forms: Text: Very Low, Low, Medium, High and Extreme and Ordinal where they are mapped from Text to a score of 1 to 5. : 1 -Very Low, 2 - Low, 3- Medium, 4- High and 5- Extreme. The greater the score, the greater the vulnerability.

The Meta Indicators as stand-alone indicators are valuable pieces of information for users of the Jameel Index and will be presented in the tables, maps and graphs of the visualization platform.

In depth: Meta-Indicators