CAPRI Online Manual (update)

CAPRI aims at building up a Policy Information System of the EU’s agricultural sector, regionalised at NUTS 2 level or farm types inside NUTS 2 regions with an emphasis on the impact of the CAP. The core of the system consists of a regionalized or farm type agricultural sector model using an activity based non-linear programming approach. One feature of such a highly disaggregated, activity based agricultural sector model is the detailed information resulting from ex ante simulations of policy scenarios concerning the output and input of specific agricultural production activities and their relationships. This information is also a pre condition to judge possible impacts of agricultural production on the environment. However, these systems require as well this kind of information (data) ex-post, at least partially. It is especially necessary to define for each region in the model, at least for the basis year, the matrix of I/O-coefficients for the different production activities together with prices for these outputs and inputs. Moreover, for calibration and validation purposes information concerning land use and livestock numbers is necessary.

Already from the beginning of the development of the CAPRI model, the regional agricultural statistics (EUROSTAT table group reg_agr) was judged as the only harmonized data source available on regionalized agricultural data in the EU. Other regional Eurostat data are suplementing the regional agricultural statistics such that we are currently using the following:

• Land use from regional landuse statistics [agr_r_landuse, discontinued table]
• Land cover from LUCAS [lan_lcv_ovw, currently only used in COCO1]
• Crop production - harvested areas, production and yields [table agr_r_crops]
• Animal production - livestock numbers [table agr_r_animal]
• Milk production [agr_r_milkpr]
• Agricultural accounts on regional level [table agr_r_accts]
• Structure of agricultural holdings including labour force [ef_ls_ovlsureg, ef_olslsureg, ef_oluaareg, ef_oluaareg, ef_r_nuts]

Although the content of the regional datasets has remained in time, the naming and classification within EUROSTAT is undergoing continuous modifications. Tables considered of low interest are discontinued (and may be still used in CAPRI some time after this point, such as table agr_r_landuse). And new topics are covered providing useful data in some areas, for example from agri-environmental indicators (table reg_aei):

• Estimated soil erosion by water, by NUTS 3 regions (aei_pr_soiler)
• Manure storage facilities by NUTS 3 regions (aei_fm_ms)

The following table shows the availability of the different regional tables as they have been used in the current database (with series completed up to 2014). However, the current coverage concerning time and sub-regions differs dramatically between the tables and within the tables between the Member States. A second problem consists in the relatively high aggregation level especially in the field of crop production. Hence, additional sources, assumptions and econometric procedures must be applied to close data gaps and to break down aggregated data.

Table 6 Availability of regional datain current database after 1983

^{Source: capri\dat\capreg\regio_data_all.gdx}

In the last major update of 2015 the original data had been first stored in the TSV format designed by EUROSTAT:

• Unordered List ItemIn a first step, these files had been converted by an excel macro into csv format and an overall set with all items including their long text has been created to prepare further processing.
• In a second step these alredy GAMS readable files are stored in GDX format in folder “dat\capreg” and under version control. Meta data are added in the process as well.

The results of these two steps is a single large tables, which comprise time series of all data retrieved from Eurostat for all tables: land use, crop production, animal populations, cow’s milk collection and agricultural accounts.

The starting point of the methodological approach is the decision to use the consistent and complete national data base (COCO) as a frame or reference point for any regionalization. In other words, any aggregation of the main data items (areas, herd sizes, gross production and intermediate use, unit value prices and EAA-positions) of the regionalized data over regions must match the national values. This is the general rule with some exceptions.

Given that starting position, the following approaches are generally applied:

• Unordered List ItemData as loaded from the regional statistics are subject to some manual consistency checks (in gams\capreg\check_and_cor_regio.gms) as well as checks for regional consistency. The latter is mainly true for animal herd sizes where we have data at the same or even more disaggregated level as found in COCO.
• Gaps in regional data are completed and data only given at a higher aggregation level as required in CAPRI are broken down by using existing national information.
• Fall back and other rules for assignments are structurally and (often) numerically identical for all regional units and groups of activities and inputs/outputs.
• Econometric analysis or additional data sources are used to close gaps.

All the approaches described in the following sub sections are only thought as a first crude estimate. Wherever additional data sources are available, their content should be checked and is often used to overcome the list of these ‘easy to use’ estimates presented in here. Examples are (some) data for Norway, Sweden or Luxembourg that have been collected from national sources. The procedures described in here can be thought as a ‘safety net’ to ensure that regionalized data are technically available but not as an adequate substitute for collecting these data from additional sources.

The agricultural domain of REGIO does not cover regionalized prices. For simplicity, the regional prices are therefore assumed to be identical to sectoral ones¹⁾:

\begin{equation} UVAG_r=UVAG_s \end{equation}

Young animal prices are a special case since they are not included in the COCO data base (the current methodology of the EAA does not value intermediate use of animals) but are necessary to calculate income indicators for intermediate activities (e.g. raising calves). Only exported or imported live animals are implicitly accounted for by valuing the connected meat imports and exports.

Young animals are valued based on the ‘meat value’ and assumed relationships between live and carcass weights. Male calves (ICAM, YCAM) are assumed to have a final weight of 55 kg, of which 60 % are valued at veal prices. Female calves (ICAF, YCAF) are assumed to have a final weight of 60 kg, of which 60 % are valued at veal prices. Young heifers (IHEI, YHEI) are assumed to have a final weight of 300 kg, of which 54 % are valued at beef. Young bulls (IBUL, YBUL) are assumed to have a final weight of 335 kg, of which 54 % are valued at beef. Young cows (ICOW, YCOW) are assumed to have a final weight of 575 kg, of which 54 % are valued at beef. For piglets (IPIG, YPIG), price notations were regressed on pig meat prices and are assumed to have a final weight of 20 kg of which 78 % are valued at pig meat prices. Lambs (ILAM, YLAM) are assumed to weight 4 kg and are valued at 80 % of sheep and goat meat prices. Chicken (ICHI, YCHI) are assumed to weight 0.1 kg and are valued at 80 % of poultry prices.

Another special case are sugar beet prices. They are still determined in a program (‘sugar\price_est.gms’) inherited from the 2003 EuroCARE sugar study (Henrichsmeyer et al. 2003). It determines sugar beet prices according to the sugar prices, levies and partial survey results in the 90ies. The estimation results are subsequently used to determine the beet price differentiation also in subsequent years. It is noteworthy that the same program is applied in CAPREG (via quotasprices.gms) and in CAPMOD (via data_prep.gms) to determine base year beet prices.