Modelling Pillar II in CAPRI Wolfgang Britz Institute for Food and Resource Economics, University Bonn

Content  Data  General approach  Implementation  Running a scenario  Result analysis Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Underlying data  Assembled by team of Janet Dwyer, from DG-AGRI sources, huge investment especially ex-post  Different definitions: Planned spend  planned allocation of budget to different measures Actual spend  Spenders (“matching funds”, co-financing with fixed shares depending on region and measure) EU budget National co-financing Private (e.g. in case of investment aid) Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Underlying data  Data on € spend on certain measures by year and NUTS2 Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Underlying data  Data now in GDX after final cleansing by Torbjoern: Britz: CAP post 2013 – Quantitative Analysis with CAPRI

General idea  Existing data only provide a very rough idea how the money was spent  Impossible (at least for us) to get detailed information how the measures are exactly implemented in the different MS and regions  CGEs are rather aggregated (only one agricultural sector), detailed modeling is thus not possible => Develop a list of “shocks” which can be seen as archetypical for Pillar II interventions: Britz: CAP post 2013 – Quantitative Analysis with CAPRI

General idea  Janet, Ben Allen, Peter, Kazia and other have assigned the RD measures to these shocks ( rd/docs/d3.1.2.pdf) Britz: CAP post 2013 – Quantitative Analysis with CAPRI ….  Shocks will change parameters in the model:  behavioral parameters of government or parameters in the production function  tax rates  Size of shock is proportional to the money spent and relative to what is shocked (e.g. amount of land subsidies related to return to land)

Human capital agriculture  Good example for the overall logic: 1.Where does the money end? Britz: CAP post 2013 – Quantitative Analysis with CAPRI 2.What is the effect of spending the money?

Human capital rest  Exercise: Make a small flow chart showing how that type of shock affects the different elements of the CGE  Similar: Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Investment in agriculture  Increase capital stock in agriculture …. and assume that new capital is more productive … Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Human capital rest  Exercise: As before: make a small flow chart showing how that type of shock affects the different elements of the CGE Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Increase gov demand for construction  … and the implementation of the shock Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Land subsidies for agriculture  And the shock implementation Britz: CAP post 2013 – Quantitative Analysis with CAPRI Note: these measures are modeled in CAPMOD, so if the PE_LINK is used, no shock in CGE …

Land subsidies for agriculture  But the story is more complex …. If the shocks becomes to large, the model might freak out … Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Land subsidies for forestry  Shock implementation is identical to agriculture Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Subsidies to service sector  Straightforward: reduction of production taxes … Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Downstream subsidies  Expand capital stock: Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Downstream subsidies  and/or decrease tax rate Britz: CAP post 2013 – Quantitative Analysis with CAPRI  Plus some vintage effect (more productive new capital)

Capital subsidies agriculture and forestry  Same story as for downstream industries: Part expands capital stocks Remaining part subsidizes investments Vintage effects Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Income subsidies  Effect not clear … and only one household type Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Shock logic  Beware, normally, in a CGE, there are only two ways to make society better off Technical progress => produce more from given endowments Remove distortions which reduce allocational inefficiencies  Our shock logic links certain government actions (= which require taxes to be financed and thus are distortive) directly to a TFP change  depending on the size of the TFP multiplier, government intervention can be beneficial => some leeway for wishful thinking, welfare analysis can be dubious Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Reporting and shock logic  The SAM does already comprise the measures …. e.g.: land taxes / subsidies for agriculture as reported in the SAM comprise the single farm payment, LFA, land taxes … That is different from the CAPMOD logic where we define all the premiums  That means for the CGE, a no change in policy means no shock … and we simulate the effect of Pillar II by removing it … Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Running a scenario Britz: CAP post 2013 – Quantitative Analysis with CAPRI An existing scenario Selection of MS

Running a scenario Britz: CAP post 2013 – Quantitative Analysis with CAPRI Definition of the baseline of CAPRI used

Running a scenario Britz: CAP post 2013 – Quantitative Analysis with CAPRI Closure rules and other settings

Reporting Britz: CAP post 2013 – Quantitative Analysis with CAPRI

Own analysis  Run for DK: cge_no_shock (= baseline calibration shock) Cge_rd_minus100 (= remove pillar II)  Load the results in the interface  Report the key changes in policies (budget, main measures)  What happens to the agriculture sector (factor use, output, price)?  Welfare analysis Britz: CAP post 2013 – Quantitative Analysis with CAPRI