AGLINK-COSIMO
Source: Commission modelling inventory and knowledge management system (MIDAS)
Date of Report Generation: Thu Mar 06 2025
Dissemination: Public
© European Union, 2025
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Overview
Acronym
AGLINK-COSIMO
Full title
AGricultural LINKage - COmmodity SImulation Model
Main purpose
A global agricultural economic model used to simulate the medium-term development of annual supply, demand and prices for the main agricultural commodities produced, consumed and traded worldwide. It has been extended to simulate the economic impacts of market uncertainties and climate extremes.
Summary
AGLINK-COSIMO is a global simulation model developed jointly by the Organization for Economic Cooperation and Development (OECD) and the Food and Agriculture Organization of the United Nations (FAO) Secretariats in collaboration with some OECD member countries. It is a partial-equilibrium, multi-commodity, recursive-dynamic model of global agricultural markets. It is used to simulate medium-term developments in annual supply, demand and prices of the main agricultural commodities produced, consumed and traded worldwide. Those projections are published annually in an extensive report (EC 2019) and also serve as a baseline reference for simulating counterfactual policy scenarios for in-house or scientific purposes, with this and other large-scale simulation models maintained in the European Commission. The 2020 version of the model has over 43,000 equations, covers more than 100 commodities (cereals, oilseeds, sugar, meats, dairy products, biofuels, cotton) in all OECD and FAO countries, and includes 43 domestic market-clearing prices that are linked with 36 international reference prices. The EU is treated as a single market.
At the EU level, the AGLINK-COSIMO model is used to produce the report ‘EU Agricultural Outlook for Markets and Income’ (EC 2019). The aim of this yearly exercise is to provide a detailed overview of EU agricultural markets over the next ten years (‘medium term’). It incorporates information from policy makers and market experts in the European Commission, as well as from stakeholders, researchers and modellers, thus culminating into a consensus regarding the likely evolution of European agriculture and related markets. The resulting projections serve also as a baseline reference for simulating counterfactual scenarios of policy relevance with AGLINK-COSIMO or even other large-scale simulation models used in the European Commission. Apart from its standard deterministic version, the model has a stochastic component where market uncertainty stemming from variability in crop yields and macroeconomic factors is examined. Recent extensions pertain to post-model calculations regarding nutrition (calories, undernourishment, obesity) and agricultural greenhouse gas emissions as well as to the quantification of market outcomes due to concurrent and recurrent extreme-climate events.
Model categories
Agriculture
Model keywords
multi-commodity modelbaselineOECDFAOSimulationagricultural markets
Model homepage
Ownership and Licence
Ownership
Third-party ownership (commercial companies, Member States, other organisations, …)
Ownership details
Licence type
Non-Free Software licence
The license has one or more of the following restrictions: it prohibits creation of derivative works; it prohibits commercial use; it obliges to share the licensed or derivative works on the same conditions.
Details
Structure and approach
The overall design of the AGLINK-COSIMO model focuses on the potential influence of agricultural and trade policies on agricultural commodity markets in the medium-term, typically 10 years ahead. Development on the basis of the (agricultural) economics literature, existing country-level models, and formal bilateral reviews has resulted in a modelling system that reflects the views of participating countries. To remain tractable, the model specification imposes some degree of uniformity across country modules. Taking this constraint into account, agricultural markets are modelled to best capture relevant settings and policies that are country- and commodity-specific. In undertaking projection work with the AGLINK-COSIMO model, individual country modules are calibrated on baseline projections that participating countries submit annually to the OECD and FAO in the form of structured questionnaires.
Input and parametrization
Main inputs to the European Commission’s version of the model are:
- The latest OECD-FAO Agricultural Outlook (issued every June), which is updated with
- the short-term outlook for EU commodity balances: crops (wheat, maize, coarse grains, sugar beet, oilseeds etc.), meat (dairy cattle, suckler cows, sheep, pigs, poultry etc.), dairy, sugar production and biofuel production.
- the latest macroeconomic and policy assumptions, and
- new model developments in terms of equations and data to better represent EU agricultural markets and policies.
Variables in the model can be endogenous (i.e., determined within the system) or exogenous (i.e., determined outside the system and simply inserted). Most behavioural equations are "double-log" which are popular in the estimation of supply and demand functions. In those functions, explained variables (on the left-hand side) and explanatory variables (right-hand side) are expressed in logarithmic terms; that is Y experiences diminishing marginal returns with respect to increases in X:
log(Y)= a + b*log(X) + log(r)
where a is the intercept, b is the Y-to-X elasticity (constant), and r is the residual (so-called ‘r-factor’). Numerous variations of this general form exist to represent real-world movements, such as technological change and cobweb-like market adjustments. Intercepts, which are time-invariant, and r-factors, which are time-variant, are interdependent and equation-specific calibration terms. These terms are endogenous during model calibration but remain exogenous in simulation mode (e.g., for scenario analysis). Year-specific shocks are implemented by changing the corresponding r-factors of endogenous variables or the actual values of exogenous variables. Oil prices and macroeconomic factors, such as GDP growth, inflation, exchange rates, energy prices, and population are exogenous.
Main output
AGLINK-COSIMO generates projections on annual market balances for the next 10 years.
Key variables include production (e.g., crops, livestock), consumption (food, feed, biofuel, other industrial uses), trade (imports, exports), stocks (public, private), and prices (domestic producer, domestic consumer, domestic feed, global) of major agricultural commodities. The model covers over 100 commodities ranging from crops, such as wheat or maize, to processed goods and by-products, such as protein meals and distiller dried grains.
Spatial & Temporal extent
The output has the following spatial-temporal resolution and extent:
Parameter | Description |
---|---|
Spatial extent / country coverage | ALL countries of the WORLD |
Spatial resolution | World-regions (supranational) |
Country/world regional level for domestic markets; world for global trade | |
Temporal extent | Very short-term (less than 1 year)Short-term (from 1 to 5 years)Medium-term (5 to 15 years) |
Temporal resolution | Years |
Market year for crops, calendar year for processed products and meats. |
Quality & Transparency
Quality
Model uncertainties
Models are by definition affected by uncertainties (in input data, input parameters, scenario definitions, etc.). Have the model uncertainties been quantified? Are uncertainties accounted for in your simulations?
- response
- yes
- details
- Uncertainties in input data and simulations are quantified every year with the partial stochastics module (Araujo-Enciso et al. 2017). Uncertainties in parameters are dealt with on a case-by-case basis using deterministic shocks.
- url
Sensitivity analysis
Sensitivity analysis helps identifying the uncertain inputs mostly responsible for the uncertainty in the model responses. Has the model undergone sensitivity analysis?
- response
- yes
- details
- Sensitivity analysis is performed every year with the partial stochastics module (Araujo-Enciso et al. 2017).
- url
Have model results been published in peer-reviewed articles?
- response
- yes
- details
- url
Has the model formally undergone scientific review by a panel of international experts?
Please note that this does not refer to the cases when model results were validated by stakeholders.
- response
- yes
- details
- Done formally by the OECD in 2009-10
- url
Model validation
Has model validation been done? Have model predictions been confronted with observed data (ex-post)?
- response
- yes
- details
- Informally, on a case-by-case basis. An ex-post exercise can be found in the OECD library (2013 version, Box 1.1).
- url
Transparency
To what extent do input data come from publicly available sources?
This may include sources accessible upon subscription and/or payment
- response
- Based on both publicly available and restricted-access sources
Is the full model database as such available to external users?
Whether or not it implies a specific procedure or a fee
- response
- no
- details
- Property of the model consortium
- url
Have model results been presented in publicly available reports?
Note this excludes IA reports.
- response
- yes
- details
- documents
For details please refer to the 'peer review for model validation' documents in the bibliographic references
Have output datasets been made publicly available?
Note this could also imply a specific procedure or a fee.
- response
- yes
Is there any user friendly interface presenting model results that is accessible to the public?
For instance: Dashboard, interactive interfaces...
- response
- no
- details
- url
Has the model been documented in a publicly available dedicated report or a manual?
Note this excludes IA reports.
- response
- yes
- details
Is there a dedicated public website where information about the model is provided?
- response
- no
- details
- url
Is the model code open-source?
- response
- no
- details
Can the code be accessed upon request?
- response
- no
- details
The model’s policy relevance and intended role in the policy cycle
The model is designed to contribute to the following policy areas
- Agriculture and rural development
The model is designed to contribute to the following phases of the policy cycle
- Formulation – such as ex-ante Impact Assessments
The model’s potential
The AGLINK-COSIMO model provides a yearly updated medium-term baseline to other market models used in the Commission, such as CAPRI, MAGNET and AGMEMOD. It is therefore used indirectly for ex-ante impact assessment (e.g., biofuels, climate negotiations, CAP reform, trade agreements). The partial stochastic analysis based on AGLINK-COSIMO is also used to analyze ex-ante the impacts of specific policy reforms.
An important activity of the European Commission is the annual production of medium-term (10 years) baseline projections for EU agricultural commodity markets (EC 2019), published annually by the Directorate General for Agriculture and Rural Development (DG AGRI) in the second half of the year. AGLINK-COSIMO, which is maintained at the JRC, is the key tool for building those baseline projections as well as for performing uncertainty and sensitivity analyses due to alternative macroeconomic environments and crop yields.
Previous use of the model in ex-ante impact assessments of the European Commission
Use of the model in ex-ante impact assessments since July 2017.
2018SWD/2018/301 final
Impact assessment accompanying the document Proposal for a Communication: on modernising and simplifying the common agricultural policy
- Lead by
- AGRI
- Run by
- European Commission
- Contribution role
- baseline and assessment of policy options
- Contribution details
The model helped to assess the following impacts:
- EU Exports & imports
- Market share & advantages in international context
- Prices, quality, availability or choice of consumer goods and services
- Goods traded with developing countries
- Emission of greenhouse gases