AGLINK-COSIMO

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.

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. 

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.

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.