CAPRI
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capri:concept:refrun [2014/06/03 16:15]
mihalyh
capri:concept:refrun [2014/06/25 11:17]
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-      <​H2>​Reference run</​H2>​ 
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-      <​H3>​Overview</​H3>​ 
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-      <​P>​The reference run or baseline serves as a reference point for ex-ante impact analysis 
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-      with CAPRI. It reflects the most probable development in agricultural markets 
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-      from global to regional scale for 8-10 year time horizon, at the current legislation. 
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-      It integrates agricultural market projections from other institutions as OECD, FAPRI, FAO and DG-AGRI. 
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-      Unique for CAPRI is the regional resolution below the national level for EU27 at the level of 
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-      NUTS 2 regions and farm types inside NUTS 2 region, and the Bayesian methodology applied.</​P>​ 
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-      <​P>​The <A HREF="​supply.htm">​supply</​A>​ and <A HREF="​market.htm">​market</​A>​ module 
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-      are calibrated to results of the reference run.</​P>​ 
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-      <P>In opposite to many other reference run approaches, CAPRI employs a Bayesian estimation 
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-      framework to define a mutually consistent set of projection values for activity levels, 
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-      yields, production, feed and processing demand, human consumption,​ trade etc. Basically, 
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-      all major equations from the supply and market modules are defined as in an optimization 
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-      framework which maximizes the joint posterior density for given a priori distribution 
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-      of the different elements. The a priori distribution is whereever possible derived to from exogenous forecasts or expert information.</​P>​ 
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-      <​TD><​P><​a href="​images\refrun.gif"><​img style="​text-decoration:​ none;​border:​ none;color: white" src="​images\refrun.gif"​ width="​500px"/></​a></​P>​ 
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-      <​H3>​Methodology</​H3>​ 
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-      <​TD><​P><​a href="​images\support.jpg"><​img style="​text-decoration:​ none;​border:​ none;color: white;​padding:​20px;​margin:​20px;"​ src="​images\support.jpg"​ width="​500px"/></​a></​P>​ 
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-      <​P>​The a priori distributions are derived from two different sources. For all elements, 
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-      long term trends are projected. Using "no change"​ as the zero hypothesis, a weighted average 
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-      between the base year value and the trend estimate is calculated, using R squared 
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-      as weight for the trend estimate. The 
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-      resulting estimates along with the estimation error of the trend deliver a priori distributions 
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-      for all items in the estimation framework.</​P>​ 
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-      <P>In a first step, the estimation is solved for these trend support, indepedently for each country. Afterwards, results are aggregated to 
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-      EU. The projections of other instutions are then added, and replace where available the supports based on trends. 
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-      If the projections are only reporting values for the EU and not for individual countries, 
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-      the country results from the first steps are used to distributed the EU estimate. The standard errors for the there projections,​ 
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-      especially for those provided by DG-AGRI, is set rather narrow, ensuring that the values are recovered as long as they do not violate 
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-      the consistency restrictions.</​P>​ 
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-     <​P>​The estimation is then repeated in a second step based on the updated supports. The country results are then taken is given, and broken 
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-     down in a similar framework to NUTS 2 level, and from there to farm type groups.</​P>​ 
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-     <​H3>​Quality control</​H3>​ 
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-     <​P>​Due to the NUTS 2 resolution with its 280 regions, and the high number of activities, outputs and inputs covered by the CAPRI modelling 
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-     ​system,​ the references comprises several Mio numbers. Therefore, aggregates over activities (single cereals aggregated to all cereals) 
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-     and products, and over countries to EU15, EU10 etc. are defined and reported in tables accessible via the Graphical user interface. 
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-     Those tables compare systematically the different inputs (trend estimate, policy shift, estimation results from the different steps).</​P>​ 
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-     <​P>​Nevertheless,​ checking results for plausibility remains a challenge. An interested comparison of the methdology between the reference 
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-     run exercise for the OECD/FAO AGLINK-COSIMO model with an estimated input of 20 person months and the CAPRI reference run 
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-     with an estimated inputs of about 2 person months is reported by <A HREF=http://​purl.umn.edu/​44120>​Adenauer 2008</​A>​.</​P>​ 
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- <​H3>​Calibration to the EC mid-term market outlook</​H3>​ 
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- The CAPRI baseline is regularly calibrated to the mid-term commodity outlook of the European Commission. More on the technical and institutional aspects can be found in the following JRC reports: <br> 
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- <​I><​a HREF="​https://​ec.europa.eu/​jrc/​en/​publication/​calibrating-capri-and-esim-models"​ class="​intext">​Calibrating CAPRI to the mid-term commodity outlook of the EC</​a></​I> ​ 
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- <​I><​a HREF="​http://​ipts.jrc.ec.europa.eu/​publications/​pub.cfm?​id=4879"​ class="​intext">​Background information on the baseline construction process</​a></​I> ​ 
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-<​H3>​More information</​H3>​ 
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-<P class="​pubparagraph"><​span class="​pubAuthor">​Witzke H.P. and Adenaeuer M.</​span>:<​BR>​ 
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-<​I><​a HREF="​..\docs\capri_baseline.pdf"​ class="​intext">​Capri Baseline (pdf, 13 slides)</​a></​I></​p>​ 
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-<font size=1>​Last Updated:​Tuesday,​ October 28, 2008 
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