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--- market_module_for_agricultural_outputs [2020/03/25 08:53] – [Endogenous policy instruments in the market model] matsz
+++ market_module_for_agricultural_outputs [2022/11/07 10:23] (current) – external edit 127.0.0.1
@@ Line 168: / Line 168: @@
 The processing margins are replaced by producer prices times -1 for all products besides oilseed. For the latter, the processing margin is defined from the producer prices //v_prodPrice// for the cakes and oils time the respective crushing coefficients minus the buying prices (average of domestically sold and imported quantities) //v_arm1Price//:
+FIXME
 \begin{align}
@@ Line 173: / Line 175: @@
 v\_prodMarg_{seed,r} = &-v\_arm1Price_{seed,r} \\
 & +v\_prodPrice_{seed \rightarrow cak,r} v\_procYield_{cak,r} \\
-& +v\_prodPrice_{seed \rightarrow oil,r} v\_procYield_{oil,r} \\
+& +v\_prodPrice_{seed \rightarrow oil,r} v\_procYield_{oild,r} \\
 \end{split}
 \end{align}
 Finally, output of oils and cakes //supply// depends on the processed quantities //proc// of the oilseeds and the crushing coefficients:
+FIXME
 \begin{align}
 \begin{split}
-supply_{cak,r} = proc_{seed,r} v\_procYield_{cak,r} \\
+supply_{cake,r} = proc_{seed,r} v\_procYield_{cak,r} \\
 supply_{oil,r} = proc_{seed,r} v\_procYield_{oil,r} \\
 \end{split}
@@ Line 233: / Line 236: @@
 The following table shows the substitution elasticities used for the different product groups. Compared to most other studies, we opted for a rather elastic substitution between products from different origins, as agricultural products are generally more uniform then aggregated product groups, as they can be found e.g. in CGE models.
-**Table 28: Substitution elasticities for the Armington CES utility aggregators((A sensitivity analysis on those elasticities is given in section 5.7 FIXME ))**
+**Table 28: Substitution elasticities for the Armington CES utility aggregators((A sensitivity analysis on those elasticities is given in section [[Sensitivity analysis]]))**
 ^Product (group)	^Substitution elasticity between domestic sales and imports  ^Substitution elasticity between import flows ^
@@ Line 248: / Line 251: @@
 {{::figure_19.png?600|}} \\ Soruce: Capri Modelling System
-The above “primal” formulation of the Armington approach in terms of quantity aggregators turned out numerically less stable in the implementaiotn than the dual representation in terms of price aggregators. The Armington approach suffers from two important shortcomings. First of all, a calibration to a zero flow is impossible so that only observed import flows react to policy changes while all others are fixed at zero level. For most simulation runs, that shortcoming should not be serious. If it is relevant, it may be overcome using the modified Armington approach as explained in Section 5.4.8 FIXME .
+The above “primal” formulation of the Armington approach in terms of quantity aggregators turned out numerically less stable in the implementaiotn than the dual representation in terms of price aggregators. The Armington approach suffers from two important shortcomings. First of all, a calibration to a zero flow is impossible so that only observed import flows react to policy changes while all others are fixed at zero level. For most simulation runs, that shortcoming should not be serious. If it is relevant, it may be overcome using the modified Armington approach as explained in Section [[Market module for agricultural outputs#Price linkages]].
 Secondly, the Armington aggregator defines a utility aggregate and not a physical quantity. That second problem is healed by re-correcting in the post model part to physical quantities. Little empirical work can be found regarding the estimation of the functional parameters of Armington systems. Hence, substitution elasticities were chosen as to reflect product properties as shown above.
@@ Line 348: / 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 357: / 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 419: / 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 450: / 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 556: / 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
@@ Line 803: / Line 806: @@
 Generally, tariff cuts have to be defined in a specific format in the CAPRI scenario file. A simple example is illustrated in hte following, where ad-valorem and specific tariffs are cut relative to their initial level and TRQ thresholds are increased.
+{{::code_p220.png?600|}}
+{{::code_p220_2.png?600|}}
+**Reporting (GUI tables)**
+The GUI has been extended with tables under 'Trade|Advanced tariff aggregators' that collect the results of the tariff aggregation module:
+{{:gui_p220.png?600|}} \\ Source: CAPRI Modelling System
+The MacMap-type aggregators are calculated both with respect to bilateral trade relations and with respect to a total ('from World') measure of tariff/TRQ restrictions. In the above calculation of total aggregate measures, imports from other countries are neglected; an assumption that can be easily relaxed if relevant policy and trade data will be available in future applications. MacMap-type trade weighted aggregators give the following results.
+{{:gui_p221.png?600|}}
+TRI estimates are also reported in a specific GUI table. By definition the TRI indicies are defined for all trade relations only (not a bilateral index):
+{{:gui_p221_2.png?600|}}
+The Anderson tariff combination is presented next. The current implementation is an extension of the original approach, including correction factors for TRQs (Himics and Britz, 2014):
+{{:gui_p221_3.png?600|}}
+The Bach and Martin (2001) approach, i.e. a combination of an aggregator for the expenditures and another one for the tariff revenues, is also implemented and reported in a designated GUI table:
+{{:gui_p222.png?600|}}
+====Overview on a regional module inside the market model====
+The resulting layout of a market for a country (aggregate) in the market module is shown in the following diagram. Due to the Armington assumption, product markets for different regions are linked by import flows and import prices if observed in the base year. Accordingly, no uniform world market price is found in the system.
+**Figure 37: Graphical presentation for one region of a spatial market system **
+{{:figure_37.png?600|}} \\ Source: CAPRI modelling system
+====Basic interaction inside the market module during simulations====
+As with the supply module, the main difficulty in understanding model reactions is based on the simultaneity of changes occurring after a shock to the model. Cross-price effects and trade relations interlink basically all product markets for all regions. Whereas in the supply model, interactions between products are mostly based on explicit representation of technology (land balances, feed restrictions), such interactions are captured in multi-commodity models in the parameters of the behavioural functions.
+Even if the following narrative is simplifying and describing reactions as if they would appear in a kind of natural sequence where they are appear simultaneously in the model, we will nevertheless ‘analyse’ the effect of an increased supply at given prices for one product and one region. Such a shift could e.g. result from the introduction of a subsidy for production of that product. The increased supply will lead to imbalances in the market clearing equation for that product and that region. These imbalances can only be equilibrated again if supply and demand adjust, which requires price changes. In our example, the price in that region will have to drop to reduce supply. That drop will stimulate feed demand, and to a lesser extent, human consumption. The smaller effect on human consumption has two reasons: firstly, price elasticities for feed demand are typically higher, and secondly, consumer prices are linked with rather high margins to farm gate prices.
+The resulting lower price at farm gate increases international competitiveness. Due to the Armington mechanism, consumers around the world will now increase the share of that region in their consumption of that product, and lower their demand from other origins. That will put price pressure in all other regional markets. The pressure will be the higher, the higher the import share of the region with the exogenous increase of supply on the demand of that product. The resulting price pressure will in turn reduce supply and stimulate demand and feed everywhere, and, with reduced prices, offset partially the increased competitiveness of the region where the shock was introduced.
+Simultaneously, impacts on market for others products will occur. Depending on the size of the cross price elasticities, demand for other products will drop with falling prices for a substitute. At the same time, reduced prices will stimulate supply of other products. The resulting imbalances will hence force downwards price adjustments in other markets as well.