CAPRI Connecting supply and demand Torbjörn Jansson* *Corresponding author Department for Economic and Agricultural Policy Bonn University Nussallee Bonn, Germany CAPRI Training Session in Warzaw, June 26-30, 2006 CAPRI Common Agricultural Policy Regional Impact
CAPRI CAPRI Training Session at JRC-IPTS, Sevilla, May Supply Supply Regional optimisation models Perennial sub-module Markets Markets Multi-commodity spatial market model Prices Reminder – General Model Layout Quantities Iterations Comparative Static Equilibrium
CAPRI CAPRI Training Session at JRC-IPTS, Sevilla, May On convergence d s q p p0p0 p0p0 q p s d s
CAPRI CAPRI Training Session at JRC-IPTS, Sevilla, May Conclusions If “demand elasticity” > “supply elasticity”, it will converge, otherwise not CAPRI has to be solved iteratively Elasticities are chosen bases on economic criteria not to obtain convergence We will likely need some mechanism promote convergence in CAPRI
CAPRI CAPRI Training Session at JRC-IPTS, Sevilla, May Different ways of promoting convergence Adjustment cost: Additional production cost for deviating from the supply in the previous step Price expectation: Supply uses weighted average of prices in several previous step. Used in CAPRI Partial adjustment: Supply only moves a fraction of the way towards the optimum in each step Approximate supply functions used in market instead of fixed supply. Used in CAPRI
CAPRI CAPRI Training Session at JRC-IPTS, Sevilla, May Approximation of supply functions The implicit supply function is unknown –Difficult to derive for CAPRI –Has non-differential points (corners) difficult to solve together with market model Assume “any” simple supply function that approximates the supply model Calibrate the parameters in each step so that the supply response of last step is reproduced
CAPRI CAPRI Training Session at JRC-IPTS, Sevilla, May Approximating supply p0p0 q p s d s Assume the “explosive situation”…
CAPRI CAPRI Training Session at JRC-IPTS, Sevilla, May Approximating supply p0p0 q p s d s s’ q0q0 Supply function is unknown (supply is a black box) Assume any supply function Starting with some price, compute supply Calibrate the assumed supply function to that point Solve supply + demand simultaneously for new price Iterate…