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--- premium_module [2020/03/13 12:40] – [Pillar I] matsz
+++ premium_module [2022/11/07 10:23] (current) – external edit 127.0.0.1
@@ Line 138: / Line 138: @@
   *land receiving payments should be kept in good agricultural and environmental condition (G.A.E.C). “Good agricultural condition is generally interpreted to mean that the land will not be abandoned and environmental problems such as erosion will be avoided” this requirement could be interpreted as re-establishing the link between the payment and the factors of production employed (land management practices) and ultimately current production; some form of management of the land should be maintained;
   *entitlements are tradable within the EU member states (not among them) but certain limitations are imposed (Ciaian, Kancs and Swinnen, 2010). For example, in the Netherlands, entitlements can be transferred among farmers only when the farmer has land without entitlements;
-  *areas already under permanent pasture should must remain so; in practise, certain reductions at regional level were accepted before Member States would be forced to
+  *areas already under permanent pasture should must remain so; in practise, certain reductions at regional level were accepted before Member States would be forced to interact.
-  *interact.
   *a strengthened rural development policy based on expanded EU budget outlayswith more EU money, new measures to promote the environment, quality and animal welfare and to help farmers to meet EU production standards starting in 2005,
   *a reduction in direct payments ("modulation") for bigger farms to contribute to finance the new rural development policy,
@@ Line 203: / Line 202: @@
 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?600|}}
+  * And permanent grass land (PGGRAS) is eligble \\
+{{:code_p167_2.png?600|}}
+  * The historic implementation \\
+{{: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|}}
+There two other factors:
+  * A possible greening share according to the October 2011 proposal by the Commission, see the section on CAP 2014-2020 for more details
+  * A national ceiling cut factor which aligns the envelops calculated from the past payments with he total MTR ceiling as defined in the legal texts.
+The part which is not longer coupled goes into the decoupled schemes:
+{{:code_p168.png?600|}}
+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?400|}}
+After that, a possible share going into the greening payment (from 2014) is deducted:
+{{: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?400|}}
+That sum if then distributed to the relevant MTR implementation scheme according to the distribution keys defined above:
+{{:code_p168_5.png?600|}}
+These calculation require that first the total premiums received in the history period are calculated which is done in ‘//policy\calc_mtr_top.gms//’.
+===CAP 2014-2020===
+From 2014 onwards, a new agricultural policy entered into force. The key elements of the policy were (i) convergence of payment rates between member states and farmers within member states, (ii) the expansion of the option to use coupled support beyond the previous articles 68/69, and (iii) the introduction of three “greening requirements”. These elements were introduced into CAPRI, and their use can be inspected in the commonly used baseline policy file “gams\pol_input\cap_after_2014\ref.gms”, the entire content of which is shown below:
+{{:code_p169.png?600|}}
+Since the mechanisms behind each of the three elements is somewhat complex, the file relies on include files to define each of the three components. The include files are stored in the scenario directory (gams\scen) of the CAPRI system, and which particular include files to use is indicated by the string variables ($setGlobal) in the first three code lines. The actual logic of the policy file, also the inclusion of the indicated three files, takes place in the file included in the final line, referred to as the base scenario file.
+//Convergence// between member states is set by adjusting the total budget of the CAP first pillar. Regarding the convergence of payment values per entitlement (IUVs, for Individual Unit Values) inside countries, the regulation allows ample room for national customization. Countries define the regions within which convergence occurs, the end year by which convergence shall be achieved, any remaining maximum span for the IUVs after convergence, and the mathematical formula to use for reducing high IUVs and increasing low ones. The file gams\scen\premiums\bps_convergence.gms defines the options chosen by member states in 2014.
+{{:code_p169_2.png?600|}}
+Two different uses of the convergence mechanism are illustrated by Austria and Greece, which apply very different models. Austria applies the full convergence using a linear model over time, with the same target payment rate in all of Austria. The convergence should be complete in 2019. This is obtained by assigning all Austrian regions to one generic “BPS-region”, for convenience the first one, called “rbps1”. Since the convergence mechanism later on works per member state, it is no problem that rbps1 is also used for e.g. the Netherlands. Then, the convergence option is set to “bps_linear” and the target year to 2019. Finally, the two parameters defining the rate of the final convergence are set, or, if you like, the width at the end of the convergence funnel and the handling of payments outside of that funnel. For Austria, the parameters are both set to “1”, which means that all farms will get exactly the same payments per hectare after convergence is complete in 2019.
+{{:code_p169_3.png?600|}}
+Greece applies different models for different types of regions, depending on the character of agriculture in the region. We approximate this in CAPRI by classifying the NUTS2-regions according to the shares of arable land, grass land and permanent crops in a historical year (2008). Based on those shares, three BPS-regions are created, within each of which the same convergence model is applied. The convergence is linear, but with the additional 30-percent-rule applied, defining that no farm (supply model region) should get more than 30 percent higher payments per hectare than the average of the BPS-region. Convergence proceeds up to the year 2019, and in each year, the lower limit for convergence, expressed as a share of the averge of the BPS-region, is set to 90%. The lower limit defines whether a farm needs convergence or not. Farms above the lower limit will get the same payments per unit as before, but for farms below the limit, the final option “p_bps_tunnel_gap_closure” kicks in, and defines what share of the gap to the lower convergence limit should be closed. For Greece, this value is set to 1/3, implying that for a farm receiving less than 90% of the average payment in the BPS-region, 1/3 of the gap shall be closed. The increased premiums are financed by a linear reduction of the payments to all farms with payments above the average payment, while also capping the highest premiums to be no more than 30% higher than the regional average.
+{{:code_p170.png?600|}}
+The code implementing the logic behind these various settings is generic and found in the file “gams\policy\implement_bps.gms”. The result is a payment per region, defined using the general premium mechanism of CAPRI, that is called “dp_bps” and with the eligible activity list “pgsaps”. The application type is “perLevl” and the budget is set on national level in the base scenario file “gams\scen\base_scenarios\cap_2014_2020.gms”.
+//Voluntary Coupled Support// is defined using the standard premium mechanisms of CAPRI, based on notifications received from the European Commission. We have interpreted the notified target activities in terms of CAPRI activities, and set budget ceilings and nominal amounts in the file “gams\scen\premiums\coupling\cap_2013_2020_vcs.gms”.
+The //Greening Measures// can be steered by the modeller. Even though the greening in itself is complex in implementation, the choices open to the CAPRI modeller are limited. The standard greening policy switches can be inspected in the file “gams\scen\premiums\greening\cap_2013_2020_greening.gms”:
+{{:code_p171.png?600|}}
+The first statement defines the share of the national pillar 1 envelope that is dedicated to the “greening top-up”. By default, this is 30%. Then, a set of active greening measures is populated. There are three options available, and by default, they are all active:
+  * The share of permanent grass land to arable land cannot decline relative to the base year.
+  * A minimum measure of crop-diversity must be maintained.
+  * A share of land must be allocated to certain activities counting as “ecological set-aside”.
+The shares of activities eligible as ecological set-aside is then defined in the concluding parameter definition in the file. The set-aside rate itself is defined as a string variable “$setglobal greening_setasiderate 5”, defining it to be 5% by default. The three greening restrictions are implemented as constraints in the supply models. The greening top-up is implemented as a standard CAPRI premium called DPGREEN. The logic behind the greening restrictions is activated in the include file “//policy\define_greening_limits.gms//”.
+The CAP 2014-2020 also contains three more payment schemes: Support to young farmers, support to smaller farms (first hectares) and support to areas with natural constraints (ANC). These payment schemes, with their associated budgets, are defined in the base scenario file.
+The following figure summarizes the logic of the CAP 2014-2020 reference policy as implemented in the CAPRI policy module in the policy file //pol_input\cap_after_2014\ref.gms//.
+**Figure 17: The logic of the CAP 2014-2020 reference policy as implemented in the CAPRI policy module**
+{{:figure17.png?600|}} \\ Source: own illustration
+===Tradable Single Premium Scheme entitlements===
+With the so-called Mid Term Review of the Common Agricultural Policy, the so-called Single Farm Premium (SFP) as a decoupled payment was introduced which is implemented as a subsidy which does not require production, is subject to cross-compliance and paid per ha up to a number of entitlements. The original entitlements, defined on a hectare basis, had been distributed to farmers operating the land and not the land owners. Both land and entitlements can be traded independently from each other. After a sequence of reform steps, basically all crop production sectors are now included in the subsidy program, so that farmers can be assumed to have received entitlements for all hectares they cropped historically. The same was true from the beginning for the so-called regional implementation. If the land available to agriculture decreases, e.g. by urbanization, some entitlements cannot not longer be matched with a hectare of eligible land. Such unused entitlements are removed from the markets after a number of years.
+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===
+Modelling of Pillar II for an EU-wide assessment provides a specific challenge given data availability regarding measures which are programmed and implemented at Member State or even regional level. Official reporting of measures under Pillar II in standardized data bases uses a rather rough categorisation, so are e.g. all agri-environmental measures grouped into one category. But even at that rather aggregated level, there is no ready to use data base available to researchers, especially with a regional resolution. A first task therefore consisted in building up a suitable data base on funds for Rural Development measures, a task undertaken by a team which had already compiled such data in the past (BALDOCK et.al. 2002).
+The most important measures from a budgetary view point are the Agri-Environmental Schemes and the Less Favourite Area Payments. Therefore some care must be taken to model these measures accurately. The project draws here on the work of a study by LEI and IEEP (LEI and IEEP 2009) for DG-AGRI, which use in the case of the agri-environmental payments analysis based on FADN and for LFA based on FADN and CLUE (Verburg et.al. 2010) results.
+**Table 26: Overview of pillar II measures modelled in CAPRI**
+|Measure type	|Measure codes EU| Modelling approach in CAPRI|
+|LFAs	|211-212	|Regional direct support. Distribution over sectors and regions based on FADN data and CLUE results.|
+|Natura 2000|213,224	|Regional direct support. Distribution over sectors and regions based on FADN data and CLUE results. Conditional on extensive technology being used.|
+|Agri-environment|214-215| Regional direct support. Distribution over sectors and regions based on FADN data. 50% of the support directed towards TF8 farm types 1, 2, 3, 4 and 8 is conditional on extensive technology being used, for remaining amounts extensive as well as intensive technology is eligible.| \\ Source: Capri Modelling System
+===Modelling of LFA===
+The LFA measure was implemented as a direct payment to cropping and grassland, with the same amount for all cropping activities except for fallow land. The first challenge encountered when implementing the LFA premiums is that the regions do not coincide with the administrative regions used in CAPRI. – Recall that CAPRI only has one single representative firm in each nuts 2 region (or up to nine farm types). In reality, thus, only a share, generally much less than 100%, of the land in a nuts region is eligible for LFA payments, and it may very well be the case that the agricultural production on that land is different from the regional average. For example, one may expect that a mountainous LFA area contains more grass land than the surrounding flat land agricultural areas in the same nuts 2 region. In order to capture a possible bias of this nature, a GIS tool (CLUE-model) was used to compute the shares \(S_{ij}\) of LFA in different broad land use classes //j// \(\in\) {non-irrigated arable land, irrigated arable land, pasture, permanent crops} in each region //i//. Those shares were used to compute a (potentially) different nominal premium amount for crops belonging to each class //j//. The so computed different amounts were taken to reflect the biased distribution of crops inside and outside of LFA regions. Since CLUE does not distinguish “Mountainous” and “Other” LFA, the nominal amount //A// to which the shares //S// were applied was assumed the same everywhere: 250 euro, the maximum amount in mountainous LFA regions.
+\begin{equation}
+P_{ij} =AS_{ij}
+\end{equation}
+where \\
+//P// = Premium per hectare	\\
+//i// = Region	\\
+//j// = Group of crops \\
+//A// = Maximum amount per hectare, 250 euro \\
+//S// = Share of LFA in all land of class //j// \\
+A value ceiling for the premium was computed by adding the budgets for the component measures. Recall that the premium module of CAPRI will apply a cut factor to the amount P such that the ceiling is not overshot.
+In economic terms, the potentially different premium rates for different groups of crops has a production effect, so that the type of production in CAPRI that receives the higher rates may expand on the expense of other activities. The interpretation would be that more farmers in the LFA areas comply with the LFA eligibility rules and modify their production plans to comply with the criteria there. Nevertheless, this is a simplification, because in CAPRI, no special technical restrictions are required in order to comply with the payment.
+=== Modelling of N2k ===
+Each production activity in CAPRI is split into a low and high yield variant with adjusted input coefficients, and thus own costs and revenues, such that their weighted average recovers regional resp. farm type means. The N2k premiums are modelled in pretty much the same way as the LFA premiums, but now with the additional assumption that the payments are conditional on extensification. This was implemented using the two alternative technologies. Thus, only the technological alternative with yield 20% below nuts2 average and lower input requirements (following a yield function) was made eligible for the payment. This is based on no empirical investigation, but is a pure assumption based on the frequently stated fact that the N2k payments are conditional on extensive management practices.
+The interpretation is the following: If more money is spent on the measure, more farmers within the designated areas may switch to extensive agriculture. Then the average payment per hectare of the nuts 2 region would increase, reflecting that a larger share of the farmers now participate in the measure. It is today indeed the case that not all farms within an N2k area receive support.
+===Modelling agri-environmental payments===
+The agri-environmental payments is a very diverse set of measures, which accounts for the largest share of the second pillar. In the modelling approach opted for here, with one aggregated measure “05 agri-environment”, a uniform implementation across member states cannot be used, which is in contrast to the LFA and N2k measures. Instead, a way of capturing the national or even regional preferences within the agri-environmental schemes must be sought.
+The method for “nationalization” of the AE scheme employed here is to use the distribution of the sum of the AE measures, i.e. the measure allocated to class 05, to agricultural sectors using the receipts by farm types according to FADN in 2005 as key. This implies linking the support to production. Whether this corresponds to reality is an empirical question. It is doubtless the case for some measures in some regions, but certainly not so for all AE measures in all regions. Refining the implementation would thus involve conditioning the support on technical constraints. Nevertheless, the implementation described above has the merit that it allocates the correct budget, resulting from the LEI budget model, to approximately the right group of farmers.
+**Table 27: Mapping from aggregated farm types in FADN (TF8) to activity groups in CAPRI**
+|TF8 type|Group of activities in CAPRI|
+|1|Grandes Cultures|
+|2|Vegetables|
+|3|Wine|
+|4|Permanent crops|
+|5|Dairy cows including pastures|
+|6|Suckler cows, sheep and goats, including pastures|
+|7|Pigs and poultry|
+|8|All agricultural activities| \\Source: Capri Modelling System
+The agri-environmental (AE) payments are implemented as extensification subsidies, and they are distributed to regions based on the distribution of less-favoured areas across regions. However, the distribution is modulated by the national level shares of farms in or out of LFA receiving AE support. We needed the following two probabilities:
+p_landPartition(ru,lcAgri,”LFA”): The share of land of each land class that is LFA (computed based on extrations from the DYNA-CLUE database).
+p_aeLfa(ms,tf8): The probability of a farm of type tf8 having agri-environmental support conditional on the farm being in an LFA region or not, computed based on the FADN sample.
+Then, the payment rate for each region is set in proportion to the weighted share of farms likely to have some AE support, predicted by the regional share of each land class (grass, arable) being classified as LFA in each region times the share of farms in/out of LFA having AE-support in the national FADN sample. The computation takes place in policy\rd_logic.gms:
+{{::code_p179.png?600|}}
+Note that the code does not know how high the absolute level of payments shall be for each region, but allocates the relative levels. Then, the national ceiling for AE payments are applied to adjust all regional payments until the ceiling is respected.
+Finally, an extensification effect to the AE payments is introduced using the possibility to make technological variants differently eligible.
+{{:code_p179_2.png?600|}} \\
+{{:code_p180.png?600|}}
+====Co-financing rates, assignment of premiums to pillars, WTO boxes and PSE-types====
+**EU and national budget contribution**
+The reporting part of the system was expanded to account for (co-)financing rates of the different schemes, so that contributions from EU and national budgets can be differentiated. The underlying factors are currently defined in //‘policy\policy_sets.gms’//:
+{{:code_p180_2.png?600|}}
+**PSEs**
+The mapping to the PSE-types is defined in //‘policy\policy_sets.gms’//:
+{{:code_p180_3.png?600|}}
+**WTO boxes**
+In a similar fashion, the premiums are allocated to the WTO boxes. The following payments are allocated to the green box (‘//policy\policy_sets.gms’//):
+{{:code_p181.png?600|}}
+The blue box, i.e.g payments under supply control or only paid up to certain upper limits, is defined as along with remaining amber box payments in Norway:
+{{:code_p182.png?600|}}
+Currently, the following budget categories are supported (see ‘//sets.gms//’ and ‘//policy\policy_sets.gms//’):
+{{:code_p182_2.png?600|}}
+In ‘//reports\feoga.gms//’, these categories are first aggregated for each activities from actual schemes (“PRME” = actual payment rate, p_budToPsdpay: distribution key):
+{{:code_p182_3.png?600|}}
+In order to come to a product based accounting scheme as used by the PSEs and WTO, these payments are assigned to the main outputs of the activities. Payments to obligatory set-aside are allocated to the activities according to set-aside rates:
+{{:code_p183.png?600|}}
+For a discussion about the WTO and PSE Boxes and their implementation in CAPRI see: Mittenzwei, K., Britz, W. und Wieck, C. (2012): Studying the effects of domestic support provisions on global agricultural trade: WTO and OECD policy indicators in the CAPRI model, selected paper presented at the 15th Annual Conference on Global Economic Analysis, "New Challenges for Global Trade and Sustainable Development", June 27-29,2012, Geneva (Switzerland).