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capri:concept:refrun [2011/04/11 08:37] – 131.220.212.14capri:concept:refrun [2014/06/25 08:17] – mihalyh
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       from global to regional scale for 8-10 year time horizon, at the current legislation.       from global to regional scale for 8-10 year time horizon, at the current legislation.
  
-      It integrates agricultural market projections from other insitutions as FAPRI, FAO and DG-AGRI.+      It integrates agricultural market projections from other institutions as OECD, FAPRI, FAO and DG-AGRI.
  
-      Unique for CAPRI are regional resolution below the national level for EU27 at the level of+      Unique for CAPRI is the regional resolution below the national level for EU27 at the level of
  
-      NUTS 2 regions, and the Bayesian methodology applied.</P>+      NUTS 2 regions and farm types inside NUTS 2 region, and the Bayesian methodology applied.</P>
  
  
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- +      <P> 
- +      In opposite to many other reference run approaches, CAPRI employs a Bayesian estimation
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-      <P>In opposite to many other reference run approaches, CAPRI employs a Bayesian estimation+
  
       framework to define a mutually consistent set of projection values for activity levels,       framework to define a mutually consistent set of projection values for activity levels,
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       framework which maximizes the joint posterior density for given a priori distribution       framework which maximizes the joint posterior density for given a priori distribution
  
-      of the different elements.</P>+      of the different elements. The a priori distribution is wherever possible derived to from exogenous forecasts or expert information.</P>
  
  
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       <P>The a priori distributions are derived from two different sources. For all elements,       <P>The a priori distributions are derived from two different sources. For all elements,
  
-      long terms are projected. Using "no change" as the zero hypothesis, a weighted average+      long term trends are projected. Using "no change" as the zero hypothesis, a weighted average
  
       between the base year value and the trend estimate is calculated, using R squared       between the base year value and the trend estimate is calculated, using R squared
  
-      as weight for the trend estimate.</P> +      as weight for the trend estimate. The
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-      <P>The resulting independent projections are then corrected +
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-      by the relative effect of implementing already decided upon changes in agricultural policies in the base +
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-      year - so-called "policy shifts". These effects are derived from a simulation with the full modelling system. The+
  
       resulting estimates along with the estimation error of the trend deliver a priori distributions       resulting estimates along with the estimation error of the trend deliver a priori distributions
  
       for all items in the estimation framework.</P>       for all items in the estimation framework.</P>
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-     <H3>Quality control</H3>+     <H3>Quality control (validation)</H3>
  
-     <P>Due to the NUTS 2 resolution with its 250 regions, and the high number of activities, outputs and inputs covered by the CAPRI modelling+     <P>The reference run can easily comprise several million data points, due to the detailed geographical resolution and to the rich set of agricultural activities and food commodities covered by the CAPRI modelling 
 +system. In order to ease the validation, results of the reference run are accessible via the Graphical User Interface, where several reporting tables aggregate over activities, commodities and countries.
  
-     system, the references comprises several Mio numbers. Therefore, aggregates over activities (single cereals aggregated to all cereals)+     With the help of the GUI, analysts can compare systematically the subsequent steps of the baseline procedure.</P>
  
-     and products, and over countries to EU15, EU10 etc. are defined and reported in tables accessible via the Graphical user interface. 
  
-     Those tables compare systematically the different inputs (trend estimate, policy shift, estimation results from the different steps).</P> 
  
 +     <P>Nevertheless, checking results for plausibility remains a challenge. An interesting comparison of the methdology between the reference
  
 +     run exercise for the OECD/FAO AGLINK-COSIMO model with an estimated input of 20 person months and the CAPRI reference run
  
-     <P>Nevertheless, checking results for plausibility remains a challenge. An interested comparison of the methdology between the reference+     with an estimated inputs of about 2 person months is reported by <A HREF=http://purl.umn.edu/44120>Adenauer 2008</A>.</P>
  
-     run exercise for the OECD/FAO AGLINK-COSIMA model with an estimated input of 20 person months and the CAPRI reference run 
  
-     with an estimated inputs of about 2 person months is reported by <A HREF=http://purl.umn.edu/44120>Adenauer 2008</A>.</P>+ <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> 
 + 
 + <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> 
  
 +  <br>
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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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