The reference run or baseline serves as a reference point for ex-ante impact analysis with CAPRI. It reflects the most probable development in agricultural markets from global to regional scale for 8-10 year time horizon, at the current legislation. It integrates agricultural market projections from other institutions as OECD, FAPRI, FAO and DG-AGRI. Unique for CAPRI is the regional resolution below the national level for EU27 at the level of NUTS 2 regions and farm types inside NUTS 2 region, and the Bayesian methodology applied.

The supply and market module are calibrated to results of the reference run.

In opposite to many other reference run approaches, CAPRI employs a Bayesian estimation framework to define a mutually consistent set of projection values for activity levels, yields, production, feed and processing demand, human consumption, trade etc. Basically, all major equations from the supply and market modules are defined as in an optimization framework which maximizes the joint posterior density for given a priori distribution of the different elements. The a priori distribution is whereever possible derived to from exogenous forecasts or expert information.

The a priori distributions are derived from two different sources. For all elements, long term trends are projected. Using "no change" as the zero hypothesis, a weighted average between the base year value and the trend estimate is calculated, using R squared as weight for the trend estimate. The resulting estimates along with the estimation error of the trend deliver a priori distributions for all items in the estimation framework.

In a first step, the estimation is solved for these trend support, indepedently for each country. Afterwards, results are aggregated to EU. The projections of other instutions are then added, and replace where available the supports based on trends. If the projections are only reporting values for the EU and not for individual countries, the country results from the first steps are used to distributed the EU estimate. The standard errors for the there projections, especially for those provided by DG-AGRI, is set rather narrow, ensuring that the values are recovered as long as they do not violate the consistency restrictions.

The estimation is then repeated in a second step based on the updated supports. The country results are then taken is given, and broken down in a similar framework to NUTS 2 level, and from there to farm type groups.