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--- market_module_for_agricultural_outputs [2020/04/07 09:39] – [Behavioural equations for the processing industry] matsz
+++ market_module_for_agricultural_outputs [2022/11/07 10:23] (current) – external edit 127.0.0.1
@@ Line 351: / Line 351: @@
 The Armington aggregator functions are already shown in the diagram above. The compositions inside of the Armington composite goods can be derived from first order conditions of utility maximisation under budget constraints and lead to the following conditions:
+FIXME
 \begin{equation}
-\frac{v\_arm2Quant_{i,r}}{v\_domSales_{i,r}}= \left( \frac{dp_{i,rw,r}}{dp_{i,r,r}} \frac {pmrk_{i,r}}{arm2pricep_{i,r}} \right )^{1/(1+\phi_1)}
+\frac{v\_arm2Quant_{i,r}}{v\_domSales_{i,r}}= \left( \frac{dp_{i,rw,r}}{dp_{i,r,r}} \frac {pmrk_{i,r}}{arm2pricep_{i,r}} \right )^{\frac{1}{1+\phi_1}}
 \end{equation}
@@ Line 360: / Line 360: @@
 \begin{equation}
-\frac{v\_tradeFlows_{i,r,r1}}{v\_tradeFlows_{i,r,r2}}= \left( \frac{dp_{i,r,r1}}{dp_{i,r,r2}} \frac {impp_{i,r,r2}}{impp_{i,r,r1}} \right )^{1/(1+\phi_2)}
+\frac{v\_tradeFlows_{i,r,r1}}{v\_tradeFlows_{i,r,r2}}= \left( \frac{dp_{i,r,r1}}{dp_{i,r,r2}} \frac {impp_{i,r,r2}}{impp_{i,r,r1}} \right )^{\frac{1}{1+\phi_2}}
 \end{equation}
@@ Line 422: / Line 422: @@
 An achievement of the CAPRI biofuel module is that biofuel supply and feedstock demand react flexibly to the price ratio of biofuel and feedstock prices as well as biofuel demand and bilateral trade flows react flexibly to biofuel prices and further relevant drivers.
-**Figure 22: Construction of the ethanol market implemented in CAPRI**
+**Figure 22: Construction of the ethanol market implemented in CAPRI** FIXME
 {{::figure_22.png?600|}} \\ Soruce: Capri Modelling System
@@ Line 453: / Line 453: @@
 \end{equation}
-The index r contains all regions in the market module that have biofuel production. All feedstocks that can be used to produce first generation biofuels are stored in the index xf and the by products Glycerine, DDGs and Vinasses in xbp. Prices are denoted by p. One speciality exists in the case of sugar prices in the EU, where a specific ethanol sugar price is assumed in case of the existence of production quotas. This is due to the fact that ethanol beet in the EU purchased at a lower price than beets processed to sugar. These single feedstock costs then form a CES aggregate to give the average cost for the respective biofuel:
+The index r contains all regions in the market module that have biofuel production. All feedstocks that can be used to produce first generation biofuels are stored in the index xf and the by products Glycerine, DDGs and Vinasses in xbp. Prices are denoted by p. One speciality exists in the case of sugar prices in the EU, where a specific ethanol sugar price is assumed in case of the existence of production quotas. This is due to the fact that ethanol beet in the EU purchased at a lower price than beets processed to sugar. These single feedstock costs then form a [[https://en.wikipedia.org/wiki/Constant_elasticity_of_substitution|CES]] aggregate to give the average cost for the respective biofuel:
 The index r contains all regions in the market module that have biofuel production. All feedstocks that can be used to produce first generation biofuels are stored in the index xf and the by products Glycerine, DDGs and Vinasses in xbp. Prices are denoted by p. One speciality exists in the case of sugar prices in the EU, where a specific ethanol sugar price is assumed in case of the existence of production quotas. This is due to the fact that ethanol beet in the EU purchased at a lower price than beets processed to sugar. These single feedstock costs then form a CES aggregate to give the average cost for the respective biofuel:
+FIXME
 \begin{equation}
 \mu_{r,xb} = \mu_{r,xb}^c-\left [ \sum_{xf} \phi_{r,xf} \left [ \frac{\mu_{r,xf}}{\mu_{r,xb}^c}\right]^{(1-\rho_{r,xb})}\right]^{\frac{1}{(1-\rho_{r,xb})}}
@@ Line 559: / Line 559: @@
 Assumed elasticities for total fuel demand after filling with average values are demonstrated in the table below.
-**Table 29: Overview of pillar II measures modelled in CAPRI**
+**Table 29: Overview of pillar II measures modelled in CAPRI** FIXME
 {{::table_29.png?350|}} \\ Source: Own calculation based on PRIMES 2009