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-====== Introduction ======
+======Introduction======
 ===== Structure of the documentation =====
-The documentation is structured as follows. Sections 1.2-1.3 give an overview of CAPRI system and its main software, GAMS. Section 1.4 informs about the CAPRI network. Sections 1.5 and 1.6 describe historical development of the model and more recent examples of CAPRI studies. Chapter 2 provides with system requirements and the main installation instructions.
+The documentation is structured as follows. Sections [[what_is_capri|What is CAPRI]]-[[CAPRI_uses_the_GAMS_software|CAPRI uses the GAMS software]] give an overview of CAPRI system and its main software, GAMS. Section 1.4 informs about the CAPRI network. Sections 1.5 and 1.6 describe historical development of the model and more recent examples of CAPRI studies. Chapter "Getting started with CAPRI" provides with system requirements and the main installation instructions.
-The rest of the document largely follows the workflow of the model: the different steps of building up the national, regional and global data base provide the foundations on which the system rests (Chapter 3). Subsequently the procedure needed to establish a baseline (Chapter 4) is discussed. Chapter 5 deals with the scenario impact analysis, giving descriptions for the regional supply models as well as for the global market model and their interactions in scenario runs. Chapter 6 covers some elements of post model analysis, whereas Chapter 7 covers options for spatial downscaling of the NUTS2 results. At the very end (Chapter 8), some developer tools for stability analysis are described.
+The rest of the document largely follows the workflow of the model: the different steps of building up the national, regional and global data base provide the foundations on which the system rests ([[The_CAPRI_Data_Base|Chapter "The CAPRI Data Base"]]). Subsequently the procedure needed to establish a baseline (Chapter "Baseline Generation") is discussed. Chapter "Scenario simulation" deals with the scenario impact analysis, giving descriptions for the regional supply models as well as for the global market model and their interactions in scenario runs. Chapter "Post model analysis" covers some elements of post model analysis, whereas Chapter "Spatial dis-aggregation: CAPDIS module" covers options for spatial downscaling of the NUTS2 results. At the very end (Chapter "Stability testing tools for model tasks"), some developer tools for stability analysis are described.
 ===== What is CAPRI =====
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 The Common Agricultural Policy Regional Impact (CAPRI) model is a global partial equilibrium model for the agricultural sector, with a focus on the European Union. It has been designed for ex-ante impact assessment of agricultural, environmental and trade policies. It has a supply module covering the EU and some auxiliary European countries((EU-28 plus Turkey, Norway and the Western Balkan countries.)) (regional programming models for about 280 European regions, detailed coverage of agricultural policies), embedded in a market module also covering regions in the rest of the world (global market model representing bilateral trade between 44 trade regions((Countries or country aggregates.))). Thus it has global coverage but ignores potential interactions with non-agricultural sectors, except for land use.
-==== Figure 1. General structure of the CAPRI model ====
+**Figure 1: General structure of the CAPRI model**
-{{ capri_model_fig01.png | Figure 1. General structure of the CAPRI model  }}
+{{:fig01.png?nolink|Source: Own illustration}}
-Source: Own illustration
 The CAPRI modelling system itself consists of specific data bases, a methodology, its software implementation and the researchers involved in their development, maintenance and applications.
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 CAPRI allows for //modular applications// as e.g. regional supply models for a specific Member State may be run at fixed exogenous prices without any market module. In previous applications farm heterogeneity has been represented by a set of farm types for each NUTS2 region, each with its own supply model. The farm type model layer is currently being replaced with another solution such that it has been switched OFF in recent applications. Equally, the global market model can be run in stand-alone mode as well.
-//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 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. Among the post model analysis options there are some designed to disentangle various contributions to scenario effects as explained in Chapter 6. An important element of post model analysis is the option of //spatial down-scaling part// to clusters of 1x1 km grid cells, covering crop shares, crop yields, animal stocking densities, fertilizer application rates and derived environmental indicators. This is based on a statistical approach, handeled in file capdis.gms and covered in a separate Chapter of this documentation. 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((http://www.ilr.uni-bonn.de/em/staff/britz/ggig_e.htm)).
+//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 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. Among the post model analysis options there are some designed to disentangle various contributions to scenario effects as explained in Chapter "Post model analysis". An important element of post model analysis is the option of //spatial down-scaling part// to clusters of 1x1 km grid cells, covering crop shares, crop yields, animal stocking densities, fertilizer application rates and derived environmental indicators. This is based on a statistical approach, handeled in file capdis.gms and covered in a separate Chapter of this documentation. 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((http://www.ilr.uni-bonn.de/em/staff/britz/ggig_e.htm)).
-More information about the CAPRI model, including technical documentation, lists of peer-reviewed and other publications, and open access to the modelling system, is available at the model webpage: www.capri-model.org.
+More information about the CAPRI model, including technical documentation, lists of peer-reviewed and other publications, and open access to the modelling system, is available at the model webpage: ((http://www.capri-model.org)).
+===== CAPRI uses the GAMS software =====
+To solve the large-scale, non-linear optimization problems in the model, CAPRI uses a software called GAMS (General Algebraic Modelling System). GAMS is a programming language designed for solving optimization problems, widely used in economic modelling. Models in GAMS are defined by one or several text files (gms files) that contain definitions and solution methods for solving constrained optimization problems (such as the supply models of CAPRI) or systems of equations (such as the marked model of CAPRI), as well as commands for data handling and reporting.
+Data used or produced by GAMS is generally stored in a file format called GDX (GAMS Data Exchange). CAPRI database and results are stored in gdx files, which can be loaded into the CAPRI Result Viewer in the Graphical User Interface where you can analyse and export the results. Without GAMS, you can view and analyse scenario results from previous scenario runs, but not run new simulations with CAPRI.
+GAMS solves models using third-party solvers that are linked to GAMS. GAMS comes with a large library of such solvers, most of them specializing in particular types of problems or solution algorithms. CAPRI relies on a particular solver called CONOPT. While CAPRI itself is distributed free of charge for anyone to download and use, GAMS and the solvers such as CONOPT requires a license to work beyond demonstration mode.
+===== The network =====
+Methodological development, updating, maintenance and application of CAPRI are based on a //network approach//, in the first 15 years certainly dominated by the key developer Wolfgang Britz and a series of PhD projects supervised by Thomas Heckelei. In the meantime responsabilites have spread with main contributors in recent years being the Bonn team (U Bonn, EuroCARE), Thünen, SLU, JRC-Sevilla and JRC –Ispra. Over the years researchers from various universities and institutes (from Norway, Switzerland and Ireland) have contributed to CAPRI, which can be seen from the contributions to many publications.
+The CAPRI modelling network may be defined as a ‘club’: there are currently no fees attached to its use but the entry in the network is controlled by the current club members. The members have agreed on a distribution of tasks to maintain and update the system. They as well contribute by acquiring new projects, by quality control of data, new methodological approaches, model results and technical solutions, and by organising events such as training sessions and preparing this documentation. It is currently considered if the club constitution needs an update as well.
+===== CAPRI development and applications =====
+CAPRI – ‘Common Agricultural Policy Regionalised Impact analysis’ is both the acronym for an EU-wide quantitative agricultural sector modelling system and of the first project centred around it((http://www.ilr.uni-bonn.de/agpo/rsrch/capri/capri_e.htm)). The scope of the project has widened over time: the first phase (FAIR3-CT96-1849: CAPRI 1997-1999) provided the concept of the data base and the regional supply models, but linked these to a simple market model distinguishing the EU and rest-of-the-world. In parallel, a team at the FAL (now Thünen Institute, TI) in Braunschweig applied CAPRI to assess the consequences of an increased share of biological farming system (FAIR3-CT96-1794: Effects of the CAP-reform and possible further developments on organic farming in the EU). A further, relatively small project (ENV.B.2/ETU/2000/073: Development of models and tools for assessing the environmental impact of agricultural policies, 2001-2002, financed by DG-REGIO) added a dis-aggregation below administrative regions in form of farm type models, refined the existing environmental indicators and added new ones. A new EU research framework project with the original network (QLTR-2000-00394: CAP-STRAT 2001-2004) refined many of the approaches of the first phase, and linked a complex spatial global multi-commodity model into the system. The application of CAPRI for sugar market reform options in the context of another project improved the way the complex ABC sugar quota system is handled in the model.
+Later, a larger project (EU research FP VI, Nr. 501981: CAPRI-Dynaspat) was conducted under the co-ordination of the team in Bonn to render the system recursive-dynamic, dis-aggregate results in space, include the new Member States and add a labour module and an indicator for energy use.
+A PhD study (Pérez-Dominguez 2005) initiated (non-CO2) GHG accounting and modelling with CAPRI to analyse tradable permits for GHG emissions from agriculture. Subsequently several projects served to improve the representation of trade policies (FP VI, Nr. 502457: “EU MedAgPol”, also FP VI: “EU-MercoPol”) and extended the coverage the supply models to the New Member states including Bulgaria and Romania).
+In 2006-2008 a first biofuel coverage in CAPRI has been achieved during an interim stay of Wolfgang Britz at JRC-Ispra which has been expanded in later years leading to follow up studies on bioenergy policies (Blanco et al. 2010, Britz and Delzeit 2013). In 2006-2007 CAPRI made contributions to study “Integrated measures in Agriculture to reduce Ammonia emission” together with MITERRA-Europe (Alterra, Wageningen) and GAINS (IASSA, Laxenburg) which led to an update of the N-cycle description in CAPRI.
+From 2006-2012 CAPRI participated in the LIFE funded EC4MACS((See http://www.ec4macs.eu/home/index.html)), the “European Consortium for Modelling of Air Pollution and Climate Strategies” which basically triggered a series of projects focussing on and improving long run projections in a modeling cluster with the PRIMES, GAINS and GLOBIOM models((This group of projects combines, for example, the FP7 project CC-TAME (Climate Change - Terrestrial Adaptation and Mitigation in Europe) and several projects commissioned by DG CLIMA (just starting is “EUCLIMIT 5”).)).
+In line with the shift of the CAP focus towards sustainability, CAPRI contributed to CCAT – EU Cross compliance tool((See https://cordis.europa.eu/project/rcn/84125/factsheet/en )), an FP6 project coordinated by Wageningen University, for an integrated assessment of cross compliance impacts, and entered (also in 2007) CAPRI FARM((See http://agrilife.jrc.ec.europa.eu/s_study3.html)) aiming at an analysis of farming sustainability.
+GHG abatement options have also been investigated in two studies by the JRC (IES, Ispra((See https://ec.europa.eu/agriculture/sites/agriculture/files/external-studies/2010/livestock-gas/full_text_en.pdf)), and IPTS, Seville((See http://ftp.jrc.es/EURdoc/JRC69817.pdf))) that may be considered the initialisation of mitigation modelling with CAPRI, a research focus that has gained in importance up from 2009 to the present((The Ecampa studies (EcAMPA2 (EcAMPA3 report is still under preparation): https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/economic-assessment-ghg-mitigation-policy-options-eu-agriculture-ecampa-2 ) are prominent examples of this tradition with a focus on EU mitigation, while a more global long run orientation is pursued in the AGCLIM50 studies (e.g. https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/challenges-global-agriculture-climate-change-context-2050-agclim50).)). Recent applications cover the challenges of including agriculture in climate change mitigation strategies (Fellmann et al. 2018) and trade liberalisation impacts on GHG emissions abatement in the agricultural sector (Himics et al. 2018).
+The current two level version of land supply derives from a study on agricultural and trade policy reform impacts on land-use across the EU, with a particular focus on land abandonment (Renwick et al. 2012).
+Until summer 2013, again a EU framework project co-ordinated by the team in Bonn called “CAPRI-RD” ensured various updates, and added a layer of regional CGEs, while working on the integration of CAP pillar 2 measures into the system. While the latter have become an essential element of CAP representation in the system, the regional CGEs have not been applied since that time (Schroeder et al. 2015, but this might be also considered the starting point of Wolfgang Britz, the main developper of CAPRI up to 2013, to move more into CGE modelling((See https://www.ilr.uni-bonn.de/em/rsrch/cgebox/cgebox_e.htm))).
+Sustainability in its various facets has been the topic driving model developments and extensions that are likely to be pursued in the next years.
+  * Beginning with a small explorative study in 2011 several studies led to the development and improvement of a “CAPRI water version” used in various projects((See, for example https://ec.europa.eu/jrc/en/publication/capri-water-20-upgraded-and-updated-capri-water-module and https://www.sim4nexus.eu/)) and studies on water-food linkages (Blanco et al. 2018).
+  * GHG accounting and modelling beyond non-CO2 required to address LULUCF effects in projects aiming at a complete coverage of the country area in the UNFCCC classification as well as transitions between those land categories and a closed carbon balance for agricultural areas((This started with an ERA NET project TRUSTEE in 2013 (https://www.trustee-project.eu/), was picked up in EcAMPA3 (beginning in 2017, technical report under preparation) and is pursued under SUPREMA as off 2018 (https://www.suprema-project.eu/))).
+  * Several efforts have been undetaken by JRC-Ispra, partly in house, partly in specific projects to achieve a more accurate representation of various environmental indicators. The detailed nutrient flow in CAPRI has been exploited to measure nitrogen footprint of food products in the EU (Leip et al. 2014) and to assess the impacts of European livestock production (Leip et al. 2015). The representation of environmental constraints, involving restrictions for fertiliser applications, for ammonia emissions, lifestock density, is currently being improved and also led to a representation of manure trade between regions.
+  * Diet shifts of food consumers offer a great potential to achieve environmental relief (as well as health benefits), such that their representation in CAPRI has been improved in the context of various partly ongoing projects((See e.g. https://www.susfans.eu/. Diet shifts were already explored in CAPRI in earlier years (e.g. under the JRC –IPTS project AgCLIM50-2) but the effort devoted to demand modelling, data and analysis has increased.)) and studies.
+Apart from the wide area of sustainability aspects of trade modelling have also been repeatedly at the heart of targeted model improvements, mostly commissioned by JRC-IPTS((We may mention the Engage specific contract on “Detailed trade policy modelling with the CAPRI model” (2014, No 154208.X1), the running Engage2 specific contract on "Update of CAPRI tariff and trade database and split of Australia-New Zealand regional block" (2019, No 935680.X7), and pending H2020 proposals.)) and thereby pursuing the CAPRI tradition of bilateral trade modelling.
+Two areas of technical developments are also likely to be continued in the future. The first one is the improvement of linkages to the in house JRC model IFM CAP that permits to represent the diversity of CAP restrictions only amenable to modelling at the farm level. As IFM-CAP operates with exogenous prices, it requires prices as model inputs that may be provided by CAPRI. The ongoing SUPREMA project (mentioned in the context of LULUCF modelling already) pursues these linkages while trying to also watch for computational feasibility, given that IFM-CAP covers each FADM farm individually. The second strand of technical improvements is the initialisation of a “stable release cycle” for CAPRI, based on two JRC-IPTS projects that are currently pursued under SUPREMA.
+The historical review has so far focussed on those studies and projects, that left clear marks in the current system as a heritage. In addition, the system was applied to a wide range of numerous different scenarios that often left smaller “traces” in the system but illustrate its capabilities and contributed to improvement in many details that are critical for serious impact assessments. The very first application in 1999 analysed the so called ‘Agenda 2000’ reform package of the CAP. Shortly afterwards, a team at SLI, Lund, Sweden applied CAPRI to analyse CAP reform option for milk and dairy. FAL, Braunschweig looked into the effects of an increase of organic production systems. WTO scenarios as well as scenarios on specific trade agreements were frequnetly untertaken. Moreover, CAPRI was applied to analyse sugar market reform options at regional level, linked to results of the WATSIM and CAPSIM models. In 2003, scenarios dealing with the CAP reform package titled ‘Mid Term Review’ were performed by the team in Bonn (Britz et al. 2003). In the wake of the sugar market reforms various reform options have been investigated (Adenaeuer et al. 2004).
+In 2004 CAPRI was used to generate a baseline in close co-operation with DG Agri match DG Agri’s outlook projections which has become a regular activity. Several studies have been launched in 2007 on particular aspects of the ongoing CAP reform (decoupling project for DEFRA, UK, modulation study by LEI for DG Agri and a milk quota expiry for JRC, IPTS, Seville). The Farm Type version of CAPRI has been used frequently to look at intrasectoral distribution of CAP reform impacts((See e.g. https://www.sciencedirect.com/science/article/pii/S0161893816300011)), direct payment harmonisation (Gocht et al. 2013), CAP greening (Gocht et al. 2017), and an EU-wide policy to extend grassland areas in order to increase carbon sink capacity (Gocht et al. 2016). A recent important application, also involving the Farm Type layer, was the impact assessment of the proposals on the post-2020 CAP, involving CAPRI in a multi-model approach to determine effects on production, prices, trade, GHG emissions and the nitrogen balance (European Commission 2018).
+Several analyses have investigated potential impact of climate change in EU agriculture by introducing changes in crop yields from biophysical models as exogenous shifts. This enables to analyse regional changes in production within the EU while considering market feedback, as well as the role of trade to counterbalance uneven effects of climate change across the world (Delincé et al 2015, Blanco et al. 2017, Pérez Dominguez and Fellmann, 2018).
+As will be clear from this review the CAPRI system strongly benefitted from EU Commission support in various forms. Most of the initial developments were co financed by DG RSRCH through the series of past FP and H2020 projects and. Furthermore the DG-JRC (IPTS, Seville and IES Ispra) has actively contributed to improvements and extensions in various components of the system and also stimulated system development with a continuous flow of new research questions and matching projects. Since a number of years recurring demand for up-to-date and long run projections on the part of DG CLIMA is contributing to some regularity in the updating process for data base and projections. Nonetheless the CAPRI network faces the common problem of the commons such that the update process for documentation is in risk to lag behind the moving target of the current code. Readers identifying missing or obsolete sections are therefore invited to contact any of the authors.