Differences

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--- premium_module [2020/03/13 13:52] – [Pillar I] matsz
+++ premium_module [2020/03/13 14:11] – [Pillar I] matsz
@@ Line 204: / Line 204: @@
 The amount of payments which is not kept coupled is then paid out to different implementations of the MTR:
   * Regional implementation where all arable crops (PGARAB) \\
-{{::code_p167.png?400|}}
+{{::code_p167.png600|}}
   * And permanent grass land (PGGRAS) is eligble \\
-{{:code_p167_2.png?400|}}
+{{:code_p167_2.png?600|}}
   * The historic implementation \\
-{{:code_p167_3.png?400|}}
+{{:code_p167_3.png?600|}}
 The exact set member ship depends on the year. The distribution shares which map the decoupled part of the premiums received under the Agenda package (see above) to these implementation schemes are edited on the Table “p_premToDDTarget_E”
 {{:code_p167_4.png?600|}}
 That information is the basis to define regional premium envelops (= CEILVAL) for the different Member states. That is a rather complex program (‘//policy\calc_mtr.gms//’).
 A first key statement defines the //remaining budget envelops for the still coupled payments//. It takes the minimum of the existing ceiling values for that scheme (CEILVAL) or the total payments paid out times the modulation factors and multiplies it with the coupling degree.
 {{:code_p167_5.png?600|}}
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 The total budget for the new MTR schemes is derived from the summation of all the old Agenda premiums. The total payments under a scheme such as the Grandes Cultures schemes are corrected for any possible remaining coupled payments:
-{{:code_p168_2.png?600|}}
+{{:code_p168_2.png?400|}}
 After that, a possible share going into the greening payment (from 2014) is deducted:
-{{:code_p168_3.png?600|}}
+{{:code_p168_3.png?400|}}
 And, finally, a factor is applied which lines up the total historic payments as defined from the CAPRI data and premium schemes in that Member State with the total MTR envelop:
-{{:code_p168_4.png?600|}}
+{{:code_p168_4.png?400|}}
 That sum if then distributed to the relevant MTR implementation scheme according to the distribution keys defined above:
@@ Line 292: / Line 294: @@
 In CAPRI, the assumption in the baseline is that all hectares used by agriculture are able to claim the SFP and that any unused entitlements had been removed so that the SFP becomes fully capitalized into land. Subsequent changes in the premiums including the SFP, prices or other policy instruments in a counterfactual run could decrease the marginal returns to agricultural land. Based on the land supply curve implemented in CAPRI, agricultural land use would shrink and some entitlements become unused. Vice versa, if changes let the marginal return to land increase, the entitlements become the limiting factor to claim the subsidy. The increase is thus mapped into an economic rent to the entitlement. If changes generate rents on entitlements in some farm types and not in others, one would assume that trade in entitlements will occur. A simple algorithm to trade the entitlement is now included in CAPRI and described below.
+//Switching on the entitlement trade//
+The trade module is implemented in the file ‘//policy\prem_entl_trade.gms//’ which is included on demand in capmod and called in each iteration
+{{::code_p173.png?600|}}
+By default, the entitlement trade is switched OFF in the general settings file of CAPMOD, called gams\capmod\set_global_variables.gms
+{{:code_p173_2.png?600|}}
+The basic idea of the module is very simple: shift entitlements from farm type or regions which unused entitlements to other farm types or regions which have an economic rent on their entitlements. The trading entities should receive the very same premium on the entitlement for the current implementation in the code. One should hence set the trade level according to the regional level for which flat rate premiums are implemented as shown below in an example:
+{{:code_p173_3.png?600|}}
+//How the entitlement trade works//
+The following code pieces are taken from ‘//policy\prem_entl_trade.gms//’. In a first step, the demand of entitlements is determined. The dual value does only provide an indication that entitlements are scarce, but not how many additional entitlements are needed. Accordingly, first, the average marginal value of the different type of entitlements is determined:
+{{:code_p173_4.png?600|}}
+From these a maximum of 10% is defined as the demand in each iteration:
+{{:code_p173_5.png?600|}}
+In order to take differences in the marginal returns into account, an indicator based on the squared value is used:
+{{:code_173_6.png?600|}}
+It serves as the distribution key of unused entitlements, which are determined as follows:
+{{:code_173_7.png?600|}}
+Next, the number of unused entitlements is stored:
+{{:code_p174.png?600|}}
+As seen, only 50% of the unused entitlements are released in any iteration. We next determine the size of the markets, i.e. total demand and supply:
+{{:code_174_2.png?600|}}
+The supply is then distributed according to the squared value of the individual demanders
+{{:code_p174_3.png?600|}}
+//An example printout//
+The following code snippet shows an example for a NUTS2 regions and the related farm types for a test run for Greece without the market module:
+{{:code_p174_4.png?600|}}
+As seen from above, we have two farm types in the starting situation which acts as demanders, i.e. have a marginal value on their entitlements (016 and 999). Their marginal value on the entitlement is quite high in the starting situation with > 125 € / entitlement. We have also a total of 3639 ha after the first round of unused entitlements which can be sold to the demanders. Distributing half of them (ca. 1800 ha) to the two demanders reduces the marginal value of the entitlements already below 95€, the next round distributed ca. 900 ha and brings the price down to 50€ until in the last round almost nothing is left for distribution and the value of the entitlements has dropped below 10€. The reader should note the trade is not yet taking into account in the income calculation of the farm types.
+Finally, we come to the main point which motivated the introduction of that module. As indicated above, we interpret the SFP as a subsidy to agricultural land use which at the margin is capitalized in the land rent. It thus increases the marginal returns to land use in agriculture. In our baseline, we start with a situation with an assumed equilibrium in land markets, i.e. marginal returns in agriculture including any subsidies are equal to marginal returns of alternative uses.
+Reducing the SFP will render agricultural land use less competitive so that land owner will rent out less to agriculture and put the land into other uses. That effect can be clearly seen below in the first iteration: in the farm types where the SFP drops due to uniform SFP at NUTS2 in Greece, land use is reduced. Total land use in Greece drops by 1.2%. But if we re-distribute the subsidy between farm types, farms which were competing before with below average subsidies against alternative land use possibilities now would like to expand land use. Without additional entitlements, they cannot: the marginal return on the next ha drops by the SFP rate. But once they buy entitlements, they offset a larger part of the land loss: in step twp, the reduction is only about 0.6%. And towards the end, the basically a no-change in land use, as we would have assumed at the aggregated level if the same type of subsidy is paid on average with the same rate.
+====Pillar II====
+===Overview===