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--- calibrating_the_global_trade_model [2020/03/01 07:45] – created matsz
+++ calibrating_the_global_trade_model [2020/03/01 07:45] – [Stage I: Data preparation and balancing] matsz
@@ Line 50: / Line 50: @@
 where SSQ is an artificial variable to be minimized, indices RMS, XXX, BAS and i indicate, respectively, regions, commodities, base year and activities (e.g., production, processing, imports etc.), and p_weight is a parameter of weights between 1 and 100 assigned to regions and activities. These weights are necessary to achieve plausible calibrated values and their specification is the outcome of a trial and error process, inspecting results from data calibration and retrying. They depend on the results of global database and trends generation. On the right hand-side of the equation v stands for a variable to be estimated and DATA – for base year data already adjusted at the data preparation and balancing stage. Hence with this equation squared sum over regions and commodities of differences between estimated and observed values (and or quantities), these differences being scaled by the observed data times the weight parameters, is minimized. Respectively, calibrated base year data fits the system of the market equations, given certain parameter values, and resembles the observed data as closely as possible. The activities implied under the I index include quantities of production, human consumption, feed, processing, processed to biofuels, import and export, producer, consumer and market prices, difference between market prices and import prices to reduce differences between physical and Armington aggregation, consolidated gap between producer and market prices, processing margin, trade flows and transport costs.
-The process of model solving is navigated with C:\...\CAPRI\gams\arm\data_fit.gms file. Its main function is to assure model solving by keeping the market balances closed and price system consistent. Because of the very large number of equations with the exact similar number of variables (36 thsds) that makes the system of equations square, as well as non-linear formulation of some of the equations, it is very likely that infeasibilities will occur during the model solving. To ensure the feasibility as far as possible, code elements such as widening of variable bounds, once they become binding, reducing non-smoothness of the functional forms and introduction of slack variables are introduced. More detailed information on this process can be found in a technical document by Wolfgang Britz and Heinz-Peter Witzke I//nfeasibilities in the market model of CAPRI – how they are dealt with// at [[https://www.capri-model.org/docs/infes.pdf]].
+The process of model solving is navigated with C:\...\CAPRI\gams\arm\data_fit.gms file. Its main function is to assure model solving by keeping the market balances closed and price system consistent. Because of the very large number of equations with the exact similar number of variables (36 thsds) that makes the system of equations square, as well as non-linear formulation of some of the equations, it is very likely that infeasibilities will occur during the model solving. To ensure the feasibility as far as possible, code elements such as widening of variable bounds, once they become binding, reducing non-smoothness of the functional forms and introduction of slack variables are introduced. More detailed information on this process can be found in a technical document by Wolfgang Britz and Heinz-Peter Witzke //Infeasibilities in the market model of CAPRI – how they are dealt with// at [[https://www.capri-model.org/docs/infes.pdf]].
 After solving the MODEL m_calMarketBas, the calibrated data are stored, new producer prices for agricultural outputs are set, sugar beet prices as a function of – sugar market price – sugar export price (pre-reform) or ethanol market price (post-reform) – processing yield (specific to CUR to calibrate to any set of projected beet prices) – levying model for A- and B- sugar (pre-reform) are calculated, share and shift parameters of CES-functions used in the Armington approach to determine import shares as a function of import prices are defined (file C:\...\CAPRI\gams\arm\cal_armington.gms). Furthermore, energy conversion factors for animal products are defined with MODEL m_fitFeedConv (in file C:\...\CAPRI\ gams\arm\feed_conv_decl.gms).