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- | $a^2 + b^2 = c^2$ | + | ====== 1. Introduction ====== |
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+ | ===== 1.1 Structure of the documentation ===== | ||
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+ | 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 | ||
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+ | 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. | ||
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+ | ===== 1.2 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, | ||
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+ | ==== Figure 1. General structure of the CAPRI model ==== | ||
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+ | {{ capri_model_fig01.png | Figure 1. General structure of the CAPRI model }} | ||
+ | Source: Own illustration | ||
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+ | The CAPRI modelling system itself consists of specific data bases, a methodology, | ||
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+ | The data bases exploit wherever possible // | ||
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+ | The economic model builds on a // | ||
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+ | CAPRI is designed for scenario analysis. It is a comparative static model, which technically means that the market equilibrium simulated for a given point in time does not involve lags or leads of endogenous variables. If several points in time are simulated, these simulatons may be perfomed therefore in any order or in parallel((This does not hold if land use transitions are simulated for environmental indicators but in a “basic” CAPRI run, these may be switched off.)). Comparative static results are best interpreted as the long run outcome of some scenario, after all adjustments to the new equilibrium are completed. By contrast, dynamic or recursive dynamic models also trace the adjustment path over time, while considering lagged relationships that are ususally critical in adjustment processes. CAPRI simulations start from a so-called baseline, which is a special applicaiton of the model as discussed in a separate chapter of this documention. The CAPRI baseline integrates projections from external sources, typically the Agricultural Outlook published annually by the European Commission' | ||
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+ | CAPRI contains two modules, market and supply, which interact (see Figure 1). | ||
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+ | 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 models optimize regional agricultural income, given the prices for inputs and outputs, subsidy levels and other policy measures. These models are a kind of hybrid approach, as they combine a Leontief-technology for variable costs covering a low and high yield variant((The two technological alternatives (for most activities), | ||
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+ | Around 55 agricultural inputs produced in about 60 activities are covered in the supply module. The activities include inputs to crop and livestock production from other sectors and intermediate inputs produced by the farms such as feed and young animals. 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. | ||
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+ | Main constraints outside the feed block are arable and grassland – which are treated as imperfect substitutes -, and potential policy restrictions (set-aside obligations, | ||
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+ | Market equilibria are calculated by iterations between the supply module and the market module. | ||
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+ | The market module for marketable agricultural outputs is a //spatial, non-stochastic global multi-commodity// | ||
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+ | Agricultural supply is modelled in a simpler way than in the supply module, with behavioural functions for supply and feed demand. These are supplemented with other functions for processing, biofuel use, and human consumption. These functions 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.Consumers and traders are represented by economic agents that follow neo-classical micro-economic theory regarding behaviour, which makes it possible to compute welfare effects. Bi lateral trade flows and attached prices are modelled based on the Armington assumptions (Armington 1969). Policy instruments cover (bi lateral) tariffs, the Tariff Rate Quota (TRQ) mechanism and, for the EU, intervention stocks and subsidized exports. This market module delivers prices used in the supply module and allows for market analysis at global, EU and national scale. | ||
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+ | 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 and crop yields may respond to changing market prices. | ||
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+ | Environmental indicators, primarily for nutrient surpluses and greenhouse gas (GHG) emissions, are calculated in CAPRI and may be directly addressed in some scenarios. Regarding nutrient surpluses, the supply module contains nutrient balance equations for nitrogen, phosphorous and potassium. It considers nutrient uptake by crops following a crop growth function, and supply of nutrients from mineral fertilizer, manure, crop residues, and, for nitrogen, atmospheric deposition and fixation. The balances also contain factors for over-fertilization, | ||
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+ | CAPRI allows for //modular applications// | ||
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+ | // | ||
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+ | More information about the CAPRI model, including technical documentation, | ||
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start.txt · Last modified: 2022/11/07 10:23 by 127.0.0.1