capri:concept:supply []

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    <H1>Supply module</H1>

   <H3>Overview</H3>

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     <a href="images\nuts2.jpg"><img style="text-decoration: none;border: none;color: white" src="images\nuts2.jpg" width="300px"/></a></div>

   <P>The supply module comprises about <A HREF="/dokuwiki/doku.php?id=capri:concept:activities">50 crop and animal

   activities</A> for each of the around 280 regions (at the so-called NUTS-2

   level covering EU27, Norway, Western Balkans and Turkey) or about 2500 farm type models for EU27 (the remaining regions

   continue to operate at regional level), and includes about <A HREF=/dokuwiki/doku.php?id=capri:concept:outputs>50 inputs and outputs</A>.

   Each independent model maximises regional agricultural income

   at given prices and subsidies, subject to constraints on land, policy

   variables and feed und plant nutrient requirements in each region.</P>

   <P><I>Income</I> is defined as the gross value added (GVA) at producer prices plus

   direct subsidies (premiums).  Costs neither included in the GVA nor

   covered by the restrictions in the NLP models are captured by a

   quadratic cost function.</P>

   <P><I>Feed requirements</I> for each animal comprise energy and crude protein

   as equality constraints, and a corridor for a dry matter. For ruminants,

   different fibre restrictions are added. The requirement are met

   by chosing a cost minimal feed mix based on 10 types of feedingstuff,

   which comprise 5 types of non-marketable fodder and 5 types of concentrates.

   The mix is further steered by minimum and maximum bounds for the feedingstuff

   and a quadratic cost function depending on the feed input coefficients

   which allows for interior solutions and a smooth response to price changes.</P>

   <P>Most crop activities features a higher and lower intensive variant to allow

   for endogenous yield adjustments. Yields and yield depending inpust are also

   updated based on price elasticities</P>

   <P>Since winter 2009/2010, CAPRI comprises a <B>land supply curve</B> which

   depends on the marginal return to land from the agricultural sector in each

   region respectively farm type. Further on, substitution between permanent grass land

   and arable land was added. Before, grass land and arable land were two fixed endowment.</P>

   <P>The module ist based on a <I>template approach</I>: the models for each region

   are structurally identically, i.e. the comprise the same equations and variables,

   and differences between the regions are expressed in parameters. That allows

   an efficient uniform handling of the models and their results.</P>

   <H3>Model calibration and simulation response</H3>

   <P>The simulation response of the models depends on the interplay of the contraints

   and the objective function. Given the relatively small number of contraints

   directly impacting on the allocation of the production activities, the

   simulation response is too a large extent depending on the parametrization of

   the quadratic terms of the cost function.</P>

   <P>The slope terms of the cost function are either estimated from

   time series analysis (<A HREF=http://hss.ulb.uni-bonn.de/2007/1157/1157.pdf>Jansson 2007</A>)

   or derived from exogenous elasticities.  The models may hence be seen

   as a kind of hybrid approach combining features from traditional

   programming models with dual econometric estimation (see also <A HREF=http://www.ilr1.uni-bonn.de/agpo/staff/heckelei/heckelei_hab.pdf>Heckelei 2002</A>).

   The cost functions' constant terms let the models

   calibrate to a given vector of technical coefficients, levels of the

   production activities, prices and subsidies. One set of parameters

   is generated to let the regional models calibrate to a three-year

   average around the base year, another to ensure calibration to the

   reference run.</P>

   <H3>Environmental indicators and restrictions</H3>

   <P>From the input coefficients and activity levels, different

   <A HREF=/dokuwiki/doku.php?id=capri:concept:envind>environmental

   indicators</A> can be derived such as nutrient balances or gaseous emissions. Part of

   the these indicators had been also embedded in constraints

   to e.g. allow for modeling a trading scheme for agricultural Green House Gas emissions.</P>

   <H3>Integration in overall modelling system</H3>

   <P>The regional programming models steer the supply response and too a large extent the feed

   demand for the countries covered by them in the overall modelling system, whereas the prices are determined

   in the <A HREF=/dokuwiki/doku.php?id=capri:concept:market>market module</A>. A point estimate of the Jacobian matrix of the frist order

   activity level equations from the regional models is used to parametrize the supply response for the

   countries covered by the regional models, ensuring a similar supply response.</P>

   <P>In each iteration between the supply and market modules, the supply and

   feed demand equations in the market module are shifted as to match at prices

   in the current simulation the response from the regional models. The price

   changes from the market are used to update yields and related input coefficients.</P>

   <P>The results of the regional models are input a post-model analysis to determine

   different economic and environmental indicators. They are also <A HREF="/dokuwiki/doku.php?id=capri:concept:spatialdownscaling">

   spatially downscaled</A> to 1x1 km grid cell clusters for EU27 to allow for spatially

   explicite environmental analysis.</P>

   <H3>Data</H3>

   <P>The ex-post data for the supply part (hectares of crops, animal herds,

   yields) are taken mainly from EUROSTAT's REGIO domain. Data are consolidated

   to match national statistics, and missing ones are estimated from time series

   and/or national ones. The national data are maintained and updated together

   with the CAPSIM model by a module called CoCo (Completeness and Consistentency).<P>

   <P><I>Input coefficients</I>

   per activity and region are estimated as to exhaust the national sectoral

   costs shown in the Economic Account for Agriculture, while coming close to

   the Standard Gross Margins published by European Commission. The estimates

   are differently derived for feed input coefficients, fertilizer input

   coefficients and the remaining inputs. The set of requirement constraints

   discussed above is simulaneouly adjusted during the estimation of the feed input coefficients

   to define a plausible mix in the base year which exhaust both regional

   fodder availability and the feed quantities for marketable products found

   in national market balances. Crop specific regional fertilizer application rates

   draw on national expert survey on typical fertilization doses, regional organic

   nutrient availability and crop retention estimated from crop yields. For the

   remaining input coefficients, econometrically derived estimates from FADN

   are used.</P>

   <H3>Technical realisation</H3>

   <P>As the rest of the CAPRI modelling system, the supply model is realised in

   <A HREF=http://WWW.GAMS.COM>GAMS</A> and solved with the non-linear solver <A HREF=http://www.conopt.com>CONOPT</A>

   developed by Arne Drud.

   Several GAMS processes are spawned in parallel to regional models in parallel, which allows to solve all 280 regions on

   a powerful eight-processor machiune in about 8 seconds and the close to 1900 farm type models in 45 seconds.</P>

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