CAPRI

Common Agricultural Policy Regional Impact Analysis
Fact Sheet

Source: Commission modelling inventory and knowledge management system (MIDAS)

Date of Report Generation: Mon Apr 22 2024

Dissemination: Public

© European Union, 2024

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Overview

Acronym

CAPRI

Full title

Common Agricultural Policy Regional Impact Analysis

Main purpose

A global agro-economic model used to assess impacts of agricultural, trade and environmental policies on the agricultural sector. CAPRI provides results at a regional level and for economic and environmental variables.

Summary

The CAPRI modelling system is a global agro-economic model, operational since 1999, designed for assessing economic and environmental impacts on agriculture at regional level.

CAPRI is a partial equilibrium model, which iteratively links a supply module, focusing on the EU, Norway, Turkey and Western Balkans, with a global multi-commodity market module.  It consists of specific databases, generated among others from two major sources: EUROSTAT and FAOSTAT. Specific modules ensure that the data used in CAPRI are mutually compatible and complete in time and space. They cover about 50 agricultural primary and processed products for the EU, from regional level to global scale including input and output coefficients.

CAPRI offers projections and scenario work on economic and environmental outcomes for medium and long run perspectives, so far up to 2085. The focus is often on linkages of environmental issues, including emissions of greenhouse gases, ammonia, nutrient balances and biodiversity indicators to the EU's Common Agricultural Policy and trade policies.

The model is frequently used in various  Commission services (such as DG AGRI, DG ENV, DG CLIMA, and the JRC) reporting on agricultural, environmental and climate policies at the regional dimension in the EU. 

Model categories

Agriculture

Model keywords

partial equilibrium modelEnvironmentagricultureCAPimpact analysisclimate changegreenhouse gas

Model homepage

http://www.capri-model.org/dokuwiki/doku.php?id=start

Ownership and Licence

Ownership

Co-ownership (EU & third parties)

Ownership details

Licence type

Free Software licence

The license grants freedom to run the programme for any purpose; freedom to run the program for any purpose; freedom to study (by accessing the source code) how the program works, and change it so it does enable computing; freedom to redistribute copies; and freedom to distribute copies of modified versions to others.

Details

Structure and approach

The economic model builds on a philosophy of model templates which are structurally identical so that instances for products and regions are generated by populating the template with specific parameter sets. This approach ensures comparability of results across products, activities and regions, allows for low cost system maintenance and enables its integration within large modelling networks. At the same time, the approach opens up the chance for complementary approaches at different levels, which may shed light on different aspects not covered by CAPRI or help to learn about possible aggregation errors in the model.

The CAPRI economic model, comparative-static in nature, is split into two major modules: the supply module and the market module.

The supply module consists of independent aggregate non-linear programming models representing activities of all farmers at regional or farm type level captured by the Economic Accounts for Agriculture (EAA). The programming models are a kind of hybrid approach, as they combine a Leontief-technology for variable costs covering a low and high yield variant for the different production activities with a non-linear cost function which captures the effects of labour and capital on farmers’ decisions. The non-linear cost function allows for perfect calibration of the models and a smooth simulation response rooted in observed behaviour. The models capture in high detail the premiums paid under CAP, include NPK balances and a module with feeding activities covering nutrient requirements of animals. Main constraints outside the feed block are arable and grassland – which are treated as imperfect substitutes -, set-aside obligations and milk quotas. The complex sugar quota regime is captured by a component maximising expected utility from stochastic revenues. Prices are exogenous in the supply module and provided by the market module. Grass, silage and manure are assumed to be non-tradable and receive internal prices based on their substitution value and opportunity costs. A land supply curve let total area use shrink and expand depending on returns to land.

The market module consists in turn of two sub-modules. The sub-module for marketable agricultural outputs is a spatial, non-stochastic global multi-commodity model for about 50 primary and processed agricultural products, covering about 70 countries or country blocks in 40 trading blocks. Bi-lateral trade flows and attached prices are modelled based on the Armington assumptions (Armington, 1969). The behavioural functions for supply, feed, processing and human consumption apply flexible functional forms where calibration algorithms ensure full compliance with micro-economic theory including curvature. The parameters are synthetic, i.e. to a large extent taken from the literature and other modelling systems. Policy instruments cover (bi-lateral) tariffs, the Tariff Rate Quota (TRQ) mechanism and, for the EU, intervention stocks and subsidized exports. This sub-module delivers prices used in the supply module and allows for market analysis at global, EU and national scale, including a welfare analysis. A second sub-module deals with prices for young animals.

As the supply models are solved independently at fixed prices, the link between the supply and market modules is based on an iterative procedure. After each iteration, during which the supply module works with fixed prices, the constant terms of the behavioural functions for supply and feed demand are calibrated to the results of the regional aggregate programming models aggregated to Member State level. Solving the market modules then delivers new prices. A weighted average of the prices from past iterations then defines the prices used in the next iteration of the supply module. Equally, in between iterations, CAP premiums are re-calculated to ensure compliance with national ceilings.

Post-model analysis includes the calculation of different income indicators as variable costs, revenues, gross margins, etc., both for individual production activities as for regions, according to the methodology of the Economic Accounts for Agriculture (EAA). A welfare analysis at Member State level, or globally, at country or country block level, covers agricultural profits, tariff revenues, outlays for domestic supports and the money metric measure to capture welfare effects on consumers. Outlays under the first pillar of the CAP are modelled in very high detail. Environmental indicators cover NPK balances including nitrogen leaching, and carbon balances including carbon sequestration, and output of climate and air pollution relevant gases according the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and the EEA/EMEP  (European Monitoring and Evaluation Programme of the European Environment Agency) air pollutant emission inventory guidebook. Model results are presented as interactive maps and as thematic interactive drill-down tables. The CAPRI graphical user interface including the exploitation tools are documented in a separate user manual.

Furthermore, regional data are disaggregated to clusters of 1x1 km grid cells, covering crop shares, crop yields, animal stocking densities, and nitrogen balance term; these data are used to calculate other environmental indicators such as soil erosion.

Input and parametrization

The key inputs used for the model:

  • prices
  • agricultural land allocation
  • supply and use balances of agro-food commodities
  • productivity indicators (yields, processing ratios, slaughter weights, fat and protein content of milk)
  • macroeconomic indicators (GDP, exchange rate, number of population)
  • policy indicators (CAP and trade policy)

CAPRI constructs is own database (COCO – complete and consistent) at the global, national and regional level. The databases exploit wherever possible well-documented, official and harmonised data sources, especially data from EUROSTAT, EAA, FAOSTAT, OECD and extractions from the Farm Accounting Data Network (FADN). This allows for the possibility of annual updates. In case of gaps in the database, suitable algorithms were developed and applied to fill them. The database is constructed in a manner that assures consistency between the different data (i.e. closed market balances, perfect aggregations from lower to higher spatial levels, match of physical and monetary data).

Specific inputs from other sources or models are used as well (EDGAR, IMPACT, GLOBIOM, EBB, ... ) to complete specific parts of the CAPRI database.

 

Main output

  • agricultural production
  • crop yields
  • production areas
  • agricultural commodity trade
  • farmer’s income
  • prices and subsidies for commodities and regions
  • Greenhouse gas and air pollutant emissions including carbon sequestration from land use change and land management change
  • Nutrient and carbon balances including nitrogen leaching
  • Water use by agricultural crop

The results generated from CAPRI are stored in a GDX format. A Java based graphical user interface allows the steering of different working steps (data base updates, baseline generation, model calibration, scenario runs).

Spatial & Temporal extent

The output has the following spatial-temporal resolution and extent:

ParameterDescription
Spatial extent / country coverageALL countries of the WORLD
CAPRI is a global model and covers 77 countries or 40 country blocks.
Spatial resolutionWorld-regions (supranational)Sub-national (NUTS2)
for EU NUTS2, for rest a set of world region
Temporal extentShort-term (from 1 to 5 years)Medium-term (5 to 15 years)Long-term (more than 15 years)
Typically 10-30 years (currently operational with runs to 2030 and 2050).
Temporal resolutionYears
One specific simulation year, comparative static approach without any intermediate steps.

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?

no
The model is deterministic. Uncertainties in parameters are covered by targeted sensitivity analysis on a few key parameters. The large model size does not permit full-fledged uncertainty analyses.

    Sensitivity analysis

    Sensitivity analysis helps identifying the uncertain inputs mostly responsible for the uncertainty in the model responses. Has the model undergone sensitivity analysis?

    yes
    When carrying out analysis key variables (i.e. yield trends, exchange rate, etc.) are changed to see the relative impact of assumptions on final results.

      Have model results been published in peer-reviewed articles?

      yes
      The model has been extensively published in peer-reviewed journals and is widely regarded as the gold-standard for regional level analysis of agricultural and climate policy.

        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.

        no
        There has been no formal evaluation of the model by an external panel

          Model validation

          Has model validation been done? Have model predictions been confronted with observed data (ex-post)?

          no
          Projections are not the main objective of the model, the model's strength lays in analysing deviations from the baseline (i.e. projections) due to external shocks (policy or other).

            Transparency

            To what extent do input data come from publicly available sources?

            This may include sources accessible upon subscription and/or payment

            Entirely based on publicly available sources

            Is the full model database as such available to external users?

            Whether or not it implies a specific procedure or a fee

            yes
            The potential user has access to the full database (COCO) as part of the model files which are made available following the procedure described in the CAPRI website.

            Have model results been presented in publicly available reports?

            Note this excludes IA reports.

            yes

            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.

            yes
            Model results are available as a gdx file together with a graphic user interface. Some specific model runs might not be public if carried out by a partner for a specific client. Those undertaken (or funded) by the JRC can be made publicly available unless confidentiality requested by the partner DG (i.e. preliminary IA work).

            Is there any user friendly interface presenting model results that is accessible to the public?

            For instance: Dashboard, interactive interfaces...

            yes
            Model results are available as a gdx file together with a graphic user interface.

            Has the model been documented in a publicly available dedicated report or a manual?

            Note this excludes IA reports.

            yes
            There is methodology and documentation section in the model's web site where all modules are documented. Wiki format and a collection of pdf documents are both available.

            Is there a dedicated public website where information about the model is provided?

            yes

            Is the model code open-source?

            yes

            Can the code be accessed upon request?

            not applicable

            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
            • Climate action
            • Environment
            • Regional policy

            The model is designed to contribute to the following phases of the policy cycle

            • Anticipation – such as foresight and horizon scanning
            • Formulation – such as ex-ante Impact Assessments

            The model’s potential

            The CAPRI model is well suited to evaluate the impact of the Common Agricultural Policy, trade and environmental policies on agricultural production, income, markets, trade and the environment, on global and regional (NUTS2) scale.

            The CAPRI model is often used to evaluate changes to the CAP and the potential impact of free trade agreements on the agricultural sector. It is also used to evaluate impacts on the agricultural sector of other sectoral policies such as environment and climate change.

             

            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.

            2024
            SWD/2024/63 final

            Impact Assessment Report Part 1 Accompanying the document Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions Securing our future Europe's 2040 climate target and path to climate neutrality by 2050 building a sustainable, just and prosperous society

            Lead by
            CLIMA
            Run by
            European Centre for Agricultural, Regional and Environmental Policy Research
            Contribution role
            baseline and assessment of policy options
            Contribution details

            The CAPRI model was used to assess impacts from agricultural, trade and environmental policies on agriculture as well as biodiversity aspects linked to agriculture.

            2023
            SWD/2023/412 final

            Impact Assessment accompanying the document Proposal for a Regulation of the European Parliament and of the Council on plants obtained by certain new genomic techniques and their food and feed, and amending Regulation (EU) 2017/625

            Lead by
            SANTE
            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
            • Cost of doing business
            • Emission of greenhouse gases
            • Productivity
            • Prices, quality, availability or choice of consumer goods and services
            • Sustainable production and consumption
            • Polution by businesses

            2022
            SWD/2022/377 final

            Impact Assessment Accompanying the document Proposal for a Regulation of the European Parliament and of the Council establishing a Union certification framework for carbon removals

            Lead by
            CLIMA
            Run by
            Rheinische Friedrich-Wilhelms-Universität Bonn
            Contribution role
            baseline and assessment of policy options
            Contribution details

            This impact assessment used the results from the model run for impact assessment SWD/2021/609 final regarding 'Land use, land use change & forestry – review of EU rules' (LULUCF)

            2021
            SWD/2021/609 final

            Impact assessment accompanying the document Proposal for a Regulation of the European Parliament and the Council: amending Regulations (EU) 2018/841 as regards the scope, simplifying the compliance rules, setting out the targets of the Member States for 2030 and committing to the collective achievement of climate neutrality by 2035 in the land use, forestry and agriculture sector, and (EU) 2018/1999 as regards improvement in monitoring, reporting, tracking of progress and review

            Lead by
            CLIMA
            Run by
            Rheinische Friedrich-Wilhelms-Universität Bonn
            Contribution role
            baseline and assessment of policy options
            Contribution details

            The model helped to assess the following impacts:

            • Cost/availability of essential inputs (raw materials, machinery, labour, energy, ..)
            • Affects on individual Member States
            • EU Exports & imports
            • Non-trade barriers
            • Market share & advantages in international context
            • Competition
            • Prices, quality, availability or choice of consumer goods and services
            • Safety or sustainability of consumer goods and services
            • International legal commitments
            • Goods traded with developing countries
            • Economic growth and employment
            • Significant effects on sectors
            • Impact on regions
            • Disproportionately affected region or sector
            • Indirect effects on employment levels
            • Lifestyle-related determinants of health
            • Emission of greenhouse gases
            • Ability to adapt to climate change
            • Waste production, treatment, disposal or recycling
            • Use of renewable resources
            • Demand for transport
            • Fuel mix used in energy production
            • Vehicle emissions
            • Change in land use

            2018
            SWD/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
            evaluation of existing policy (indirect)
            Contribution details
            Documented in study :

            The model helped to evaluate the existing policy, further detailed also in the impact assessment SWD/2018/301 itself.

            2018
            SWD/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:

            • Competition
            • Prices, quality, availability or choice of consumer goods and services
            • Significant effects on sectors
            • Impact on regions
            • Disproportionately affected region or sector
            • International legal commitments
            • Goods traded with developing countries
            • Emission of greenhouse gases
            • Ability to adapt to climate change
            • Change in land use

            Bibliographic references

            Studies that uses the model or its results

            Climate change impacts and adaptation in Europe 

            Published in 2020
            Feyen, L., Ciscar Martinez, J., Gosling, S., Ibarreta Ruiz, D., Soria Ramirez, A., Dosio, A., Naumann, G., Russo, S., Formetta, G., Forzieri, G., Girardello, M., Spinoni, J., Mentaschi, L., Bisselink, B., Bernhard, J., Gelati, E., Adamovic, M., Guenther, S., De Roo, A., Cammalleri, C., Dottori, F., Bianchi, A., Alfieri, L., Vousdoukas, M., Mongelli, I., Hinkel, J., Ward, P., Gomes Da Costa, H., De Rigo, D., Liberta`, G., Durrant, T., San-Miguel-Ayanz, J., Barredo Cano, J., Mauri, A., Caudullo, G., Ceccherini, G., Beck, P., Cescatti, A., Hristov, J., Toreti, A., Perez Dominguez, I., Dentener, F., Fellmann, T., Elleby, C., Ceglar, A., Fumagalli, D., Niemeyer, S., Cerrani, I., Panarello, L., Bratu, M., Després, J., Szewczyk, W., Matei, N., Mulholland, E. and Olariaga-Guardiola, M., Climate change impacts and adaptation in Europe, EUR 30180 EN, Publications Office of the European Union, Luxembourg, 2020, ISBN 978-92-76-18123-1 (online), doi:10.2760/171121 (online), JRC119178.

            Economic assessment of GHG mitigation policy options for EU agriculture 

            Published in 2020
            Perez Dominguez, I., Fellmann, T., Witzke, H., Weiss, F., Hristov, J., Himics, M., Barreiro Hurle, J., Gomez Barbero, M. and Leip, A., Economic assessment of GHG mitigation policy options for EU agriculture, EUR 30164 EN, Publications Office of the European Union, Luxembourg, 2020, ISBN 978-92-76-17854-5 (online),978-92-76-17855-2 (print), doi:10.2760/4668 (online),10.2760/552529 (print), JRC120355.

            Greenhouse gas emissions from the EU livestock sector: A life cycle assessment carried out with the CAPRI model 

            Published in 2012
            Weiss F, Leip A. Greenhouse gas emissions from the EU livestock sector: A life cycle assessment carried out with the CAPRI model. AGRICULTURE ECOSYSTEMS and ENVIRONMENT 149; 2012. p. 124-134. JRC68859

            Peer review for model validation

            Short- and long-term warming effects of methane may affect the cost-effectiveness of mitigation policies and benefits of low-meat diets 

            Published in 2021
            Pérez-Domínguez, I., del Prado, A., Mittenzwei, K., Hristov, J., Frank, S., Tabeau, A., Witzke, P., Havlik, P., van Meijl, H., Lynch, J., Stehfest, E., Pardo, G., Barreiro-Hurle, J., Koopman, J. F. L., & Sanz-Sánchez, M. J. (2021). Short- and long-term warming effects of methane may affect the cost-effectiveness of mitigation policies and benefits of low-meat diets. Nature Food, 2(12), 970–980. https://doi.org/10.1038/s43016-021-00385-8

            Greenhouse gas mitigation technologies in agriculture: Regional circumstances and interactions determine cost-effectiveness 

            Published in 2021
            Fellmann, T., Domínguez, I. P., Witzke, P., Weiss, F., Hristov, J., Barreiro-Hurle, J., Leip, A., & Himics, M. (2021). Greenhouse gas mitigation technologies in agriculture: Regional circumstances and interactions determine cost-effectiveness. Journal of Cleaner Production, 317, 128406. https://doi.org/10.1016/j.jclepro.2021.128406

            Reuse of treated water in European agriculture: Potential to address water scarcity under climate change 

            Published in 2021
            Hristov, J., Barreiro-Hurle, J., Salputra, G., Blanco, M., & Witzke, P. (2021). Reuse of treated water in European agriculture: Potential to address water scarcity under climate change. Agricultural Water Management, 251, 106872. https://doi.org/10.1016/j.agwat.2021.106872

            Setting Climate Action as the Priority for the Common Agricultural Policy: A Simulation Experiment 

            Published in 2019
            Himics, M., Fellmann, T., & Barreiro‐Hurle, J. (2019). Setting Climate Action as the Priority for the Common Agricultural Policy: A Simulation Experiment. Journal of Agricultural Economics, 71(1), 50–69. Portico. https://doi.org/10.1111/1477-9552.12339

            Does the current trade liberalization agenda contribute to greenhouse gas emission mitigation in agriculture? 

            Published in 2018
            Himics, M., Fellmann, T., Barreiro Hurle, J., Witzke, H., Perez Dominguez, I., Jansson, T. and Weiss, F., Does the current trade liberalization agenda contribute to greenhouse gas emission mitigation in agriculture, FOOD POLICY, ISSN 0306-9192, 76, 2018, p. 120-129, JRC110846.

            Risk of increased food insecurity under stringent global climate change mitigation policy 

            Published in 2018
            Hasegawa, T., Fujimori, S., Havlik, P., Valin, H., Bodirsky, B., Doelman, J., Fellmann, T., Kyle, P., Koopman, J., Lotze-Campen, H., Mason-D`croz, D., Ochi, Y., Perez Dominguez, I., Stehfest, E., Sulser, T., Tabeau, A., Takahashi, K., Takakura, J., Van Meijl, H., Van Zeist, W., Wiebe, K. and Witzke, H., Risk of increased food insecurity under stringent global climate change mitigation policy, NATURE CLIMATE CHANGE, ISSN 1758-678X, 8, 2018, p. 699-703, JRC110841.

            Comparing impacts of climate change and mitigation on global agriculture by 2050 

            Published in 2018
            Van Meijl, H., Havlik, P., Lotze-Campen, H., Stehfest, E., Witzke, H., Perez Dominguez, I., Bodirsky, B., Van Dijk, M., Doelman, J., Fellmann, T., Humpenoeder, F., Levin-Koopman, J., Müller, C., Popp, A., Tabeau, A., Valin, H. and Van Zeist, W., Comparing impacts of climate change and mitigation on global agriculture by 2050, ENVIRONMENTAL RESEARCH LETTERS, ISSN 1748-9326, 13, 2018, p. 060421, JRC110838.

            Agricultural non-CO2 emission reduction potential in the context of the 1.5 °C target 

            Published in 2018
            Frank, S., Havlík, P., Stehfest, E., van Meijl, H., Witzke, P., Pérez-Domínguez, I., … Valin, H. (2018). Agricultural non-CO2 emission reduction potential in the context of the 1.5 °C target. Nature Climate Change, 9(1), 66–72. doi:10.1038/s41558-018-0358-8

            Major challenges of integrating agriculture into climate change mitigation policy frameworks 

            Published in 2017
            Fellmann, T., Witzke, P., Weiss, F., Van Doorslaer, B., Drabik, D., Huck, I., Salputra, G., Jansson, T., & Leip, A. (2017). Major challenges of integrating agriculture into climate change mitigation policy frameworks. Mitigation and Adaptation Strategies for Global Change, 23(3), 451–468. https://doi.org/10.1007/s11027-017-9743-2

            Model documentation

            CAPRI model documentation

            Published in 2022

            Other related documents

            Policy reform and agricultural land abandonment in the EU 

            Published in 2013
            Renwick, A., Jansson, T., Verburg, P. H., Revoredo-Giha, C., Britz, W., Gocht, A., & McCracken, D. (2013). Policy reform and agricultural land abandonment in the EU. Land Use Policy, 30(1), 446–457. doi:10.1016/j.landusepol.2012.04.005

            Exploring the feasibility of integrating water issues into the CAPRI model 

            Published in 2012
            Blanco Fonseca M, Van Doorslaer B, Britz W, Witzke H. Exploring the feasibility of integrating water issues into the CAPRI model. EUR 25649. Luxembourg (Luxembourg): Publications Office of the European Union; 2012. JRC77058