Assessment cap reform 2014 2020 in Emilia-Romagna Region

Chapter 20Assessment of CAP Reform 2014–2020in the Emilia-Romagna Region

R. Gigante, F. Arfini and M. Donati

Abstract The aim of this contribution is to evaluate the impacts of the EuropeanCommission proposals on rural areas of the Emilia-Romagna Region in Italy. Themodel considers the three main characteristics of the CAP 2014–2020 reform, and inparticular measures the impact of greening criteria on land allocation in differentfarm systems and economic effects on rural areas. It will show which rural systemsand types of farm will be favored or penalized by the reform. The model willalso provide results on dynamics in land use. The assessment is made using an‘‘integrated’’ regional model based on Positive Mathematical Programming (PMP).

20.1 Introduction

The debate on the Common Agriculture Policy (CAP) for the years 2014–2020started in 2011, and at the time of writing is nearing conclusion. The reform wasapproved by the final European plenary session on 13th March 2013 by 25 of the 27Ministers of Agriculture. On April 11th, it was discussed by the Trilogue in informaltripartite meetings of representatives of the European Parliament, the Council andthe Commission. The goal was to reach a common political agreement by the end ofJune. But on the other hand, the European budget, including agriculture funding, isat present still undefined. In this uncertain context, what remains of the EuropeanCommission’s official proposal of 2011 (European Commission 2011a) is thatfuture CAP will continue its main focus on environmental measures directingEuropean farms toward a model of sustainable agriculture responsible for themanagement of environmental resources and attentive to public financial resourcesand well-being of consumers (Matthews 2013). The aim of this contribution is to

R. Gigante (&) � F. Arfini � M. DonatiDepartment of Economics, University of Parma, Parma, Italye-mail: [email protected]

C. Zopounidis et al. (eds.), Agricultural Cooperative Management and Policy,Cooperative Management, DOI: 10.1007/978-3-319-06635-6_20,� Springer International Publishing Switzerland 2014

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evaluate the impacts of the European Commission proposals (European Commis-sion 2011b) on rural areas in the Emilia-Romagna Region in terms of province,altitude, and farm type.

The study will consider the impact of greening criteria, capping and theregionalization scheme on land allocation, and the relative economic effects ondifferent regional farm systems. It will focus on the regional effect of the CAPreform, considering the nonhomogeneity of the Emilia-Romagna Region, andshow the main consequences in terms of land use and income distribution amongdifferent farm types and rural systems across one of the most important Italianfarming regions.

The evaluation will be made by a regional model based on the use of PositiveMathematical Programming (PMP). Data are extracted from an integrated regionaldatabase that matches FADN Data with IACS information for the year 2010. Thechapter is organized as follows; Sect. 20.1 describes the evolution of CAP inenvironmental measures, changes in distribution of aid, and the system of trans-ferring resources from Pillar 1 to Pillar 2; Sect. 20.2 focuses on the methodologyand describes the AGRISP model and its implications; Sect. 20.3 describes thenew measures taken into account by the model, detailing amounts and restrictionsimposed by the reform; Sect. 20.4 shows results from the model and theirimplications for changes in land use and economic indicators. Results are shown atregional and province level and also by altimetry. The last section discusses thenew agriculture policy and the possible effects on rural areas in Emilia-Romagna.

20.2 The Policy Setting

This section discusses the main innovations in the CAP 2014 reform, and how thesehave evolved from recent policy reforms. The new CAP in fact fulfills manymedium- and long-term expectations both within and outside the EU. The HealthCheck of 2008 enforced a series of provisions of the 2003 reform, and the newreform will continue to enhance intervention on environmental protection (Anania2008). The main concerns are the new greening measures, agricultural developmentand modulation methods, with new proposals oriented toward rural developmentand setting CAP as a more equal policy between Member States (MS) with a newsingle payment scheme. Reform paths can be viewed from either an economic pointof view or as a requirement to renew environmental strategies at a higher level.Economically, the necessity to reduce CAP expenditure and the eradication of theold system of direct support will cut the EU budget, bringing down both surplusproduction and international tensions (De Filippis and Frascarelli 2012). Envi-ronmentally, the measures reflect institutional concerns and widespread awarenessof limits to availability of natural resources, and are a prerequisite for acceptance ofexpenditure by European taxpayers (European Commission (a) and (b)).

372 R. Gigante et al.

20.2.1 Evolution of Environmental Focus in the CAP

From the start, the CAP has been characterized by reforms that have tried to alignthe varying objectives of the Community in agriculture in European society. In thebeginning, at the time of the Treaty of Rome (1957), CAP focused on agriculturalpolicy with the priority of food security. In subsequent years, the emphasis movedto a new concept, linking agriculture to environmental issues. The first concreteattempt at this was in the MacSharry reform (1992) which gave EU farm policy anew role in an attempt to re-establish a proper relationship between agriculture andthe environment and also to revise CAP expenditure limits. The MacSharry reformintroduced the concept of ‘‘green’’ to the CAP, and its ‘‘accompanying measures’’(Reg. EC no. 2078/92) contained predominantly agri-environment schemes, suchas the adoption of environmentally friendly farming methods (e.g., organicfarming), reducing the use of chemical products and processes and the extensifi-cation of farming. This led to the 1999 reform, Agenda 2000, which aimed tostrengthen public intervention in agriculture for sustainability, especially envi-ronmental sustainability, and then to the Fischler Reform of 2003 (Reg. EC no.1782/2003). The Fischler Reform introduced the principle of decoupling aid andthe cross-compliance mechanism: the farmer is obliged to comply with minimumenvironmental standards in order to obtain agricultural support (Sorrentino et.al.2011).

In 2008, a further review of the CAP (Health Check or Fisher-Boel Reform)completed the decoupling process and amended specific additional intervention,reinforcing its environmental objectives. Among other measures, the controversialArticle 68 of EC Regulation No. 73/2009 provides annual additional payments forforms of agricultural management of the environment, such as extensive animalfarming. The last step in this evolution on environmental issues will be imple-mented in programming period 2014–2020 with the new greening measures.Although at the time of writing, the European Commission has yet to take finaldecisions on the new CAP, this contribution attempts to make a preliminaryevaluation of the effects on the agriculture sector in the Emilia-Romagna region.

20.2.2 A More Equal CAP

Since the early 1990s, CAP policy has been gradually reformed toward marketorientation in the two reform packages of 2003 and 2007. These replaced a largeshare of the price support by direct payments per hectare of land and per head oflivestock. These direct payments were only paid to certain crops and certain typesof livestock. In 2003, the Fischler reform substantially changed European policiesfor supporting farmers with decoupling of direct payments. The new ‘‘SinglePayment Scheme’’ introduced payment per hectare of agricultural land, indepen-dently of the individual farmer’s output. It is paid regardless of whether the farmer

20 Assessment of CAP Reform 2014–2020 373

produces or not, as long as the land is kept in good agricultural and environmentalcondition. However, there are exceptions to the general principle of decoupling,since individual member states are currently allowed to keep limited coupledpayments for some products (partial decoupling). The reform was intended to makeEuropean agriculture more competitive and market-oriented as required by WTO,and at the same time to provide support to farmers with less distortion of productionand trade. Decoupled payments allow farmers to respond better to signals from themarket, to supply the food sector, and to create a basis for providing public goods.The scheme was amended slightly in 2007 and has been in force until today. CAP2014–2020 is expected to provide for a fully direct payment system for all MS andby the beginning of 2019, all MS will move to a uniform payment per hectarescheme, applied at the national or regional level. In Italy as in some other MS, andconsequently in Emilia-Romagna, this reform will be a big challenge for farmersaccustomed to the concept of acquired rights. The change is to be accompanied byother measures; cross-compliance is maintained and greater modulation is intro-duced to the new coupled scheme. It could also lead to redistribution betweenagrarian regions and farms, and between production sectors, which could affect thecompetitiveness of different farm activities and sectors. There will very likelybe variations in the competitiveness of farms and sectors.

An example of the effect of aid redistribution at the local level is shown inFig. 20.1. Using administrative regional boundaries, it shows the present situationand the effects of the new regionalization, with the future single payment schemein the different provinces of Emilia-Romagna (Gigante 2013). The shrinkage offinancial resources and decoupled payments reduce the average aid level in mostprovinces. Because of the type of production (cereal, tomato, milk), many prov-inces lose resources in favor of areas producing fruits and wine, which were noteligible for payments in the past.

The effect of aid redistribution can also be differentiated by altimetry(Fig. 20.2). The effect is much stronger on plain areas, where resources are cut forthe benefit of mountain areas. At altimetry levels too, the type of production isimportant: plain areas used to receive aid for almost all hectares, so the redistri-bution operates a linear reduction. Mountain and some hill areas gain advantagethanks to smaller cultivated surface area and because most farms specialize in milkproduction. In fact, despite the milk quota system, mountain areas have until nowbeen less favored.

20.2.3 New Resources to Pillar 2

The new capping mechanism appears to be very different from the schemeintroduced by the Health Check in 2007 and in force today. The current schemeapplies the mechanism of modulation only to beneficiaries receiving more than€300,000 in direct payments, which are subject to an additional cut of 14 %. Butunder the new scheme, the upper limit of direct payments to farmers will be


€300,000. However, in order to preserve and stimulate the application of envi-ronmental measures and practices, the cost of greening will not be considered inthe budget. In order to maintain employment in the sector, the capping mechanismwill be mitigated for farms employing waged labor. The EU Commission draftstates that the direct payments scheme will take into account the employment levelon farms, and the amount of wages actually paid and declared by farmers for theprevious year, including social security contributions and employment taxes, willbe added to the total amount of direct payments due.

As the result of capping, more resources will be available for transfer to Pillar 2(Rural Development). Moreover, given that each MS has a different agriculturesystem, each MS is given the option of transferring up to 10 % of nationalfinancial resources assigned for direct payments (Pillar 1) to Rural Development(Pillar 2). In addition, MS which receive less than 90 % of the EU average directpayments can now transfer up to 5 % of the funds assigned for Rural Developmentto the Direct Payment System.

Fig. 20.1 Redistribution of aid in Emilia-Romagna provinces

Fig. 20.2 Redistribution of aid in Emilia-Romagna provinces by altimetry


20.3 Description of the Model: PMP and Database

Positive Mathematical Programming (PMP) included in the Agricultural RegionalIntegrated Simulation Package (AGRISP) model (Arfini et al. 2005) was used toassess the impact of CAP 2014–2020 on Emilia-Romagna. This model is one ofthe possible applications of the PMP across Europe (Heckelei et al. 2012). In thisresearch, AGRISP was used to reproduce the effects of the regionalized singlepayment system, greening measures, and the new capping mechanism on farmbehavior and farm economic performance. As noted in the introduction, thesimulations are based on the draft by the European Commission, so rather thancertain consequences they indicate possible potential consequences. The simula-tions demonstrate a capability differential of farms in reacting to new policy andmarket scenarios, and show how the reform will affect the production and eco-nomic levels of the farms investigated.

20.3.1 Evolution of PMP Methodology

As is well known, PMP has a long history (Heckelei and Britz 2005; Heckelei et al.2012). After early Linear Programming models, which showed the optimumcombination for production according to the technological matrix, the next stepwas positive models where the optimum is considered at the observed productionlevel, which reveals farm cost structures. The main aim here is to give as true apicture as possible of the current situation, then simulate the behavior of farmproducers as agricultural policy intervention is shifted (Arfini and Donati 2013).The versatility of PMP means it can be fitted to valuation models with differentlevels of detail, so it can be applied to a single farm (business model) or forsimulations of the dynamics of a territory (regional model) or a production sector(sectorial model). It is also possible to structure a mixed model using an integrateddatabase including regional and sector aspects. Despite their differences, thesemodels have a common matrix deriving from their microeconomic formulationand embodied in the use of information collected at the enterprise level, regardlessof the ‘‘scale’’ (corporate, regional, or sectorial) of the simulation. In businessmodels the scope is limited to the single firm, but the models used here provideregional or sectorial results for aggregate geographical areas or entire productivesectors. Sectorial models are usually used by decision-makers in assessing agri-cultural policy for a single and specific production. But although their primaryobjective is to analyze supply changes of products subject to intervention, themodels can also have a regional significance to the extent they quantify the impactof the policy at the regional, national, or international level (Arfini and Donati2011). The element that distinguishes the sectorial from the regional model is theaggregation criteria of the farms; for sectorial models, the aggregation criteria isthe farm type.


The application of mathematical programming to agricultural policy entailsdefining from the outset a reference to a regional area (in the case of a regionalmodel) or to a specific productive sector (sectorial model). Regional and sectorialmodels are not necessarily alternatives; in general, a single productive segment isanalyzed individually with reference to a territorial area, in contemporaneousregional and sectorial studies. However, the variables of interest and the PMPmodel need to be defined a priori.

So in a complex scenario like local rural development the model needs to coverdifferent farm types and truthfully represent land use and productivity levels of thefarmers in the area. It is useful to minimize the amount of data, although thereneeds to be enough detail to describe both individual farmer behavior and tech-nologies and production decisions at the farm level. AGRISP (Arfini et al. 2005),which shows in detail the use of land, farm specialization, and different farmclasses by size, is an appropriate compromise. AGRISP in fact represents a fusionof two databases: the AGEA database on land use of each farm, and the FADNdatabase of the profitability of each production process activated. So rather than a‘‘model,’’ AGRISP is a tool of analysis that overcomes limitations of other similartools used to simulate agricultural policies at the regional level. The combined useof AGRISP data and PMP methodology means that all output models can becalculated precisely.

In Europe as in Italy, at present, the main source of statistical data on structuralcharacteristics of farm production and economics is the Agricultural AccountancyData Network (FADN). Data are obtained by survey and the database is structuredas a statistical sample of all farms. It can be considered ‘‘ideal’’ for coefficients onfarm production techniques and farm economic characteristics. FADN has, how-ever, three major limitations: (i) a lack of technical information on the amount ofinput used for each process; (ii) the representativeness of data is based on thestandard gross margin, while the presence of a specific process reflects the landuse; (iii) the level of representativeness of farms decreases significantly fromregional level to provincial level.

In particular, the first aspect (the lack of quantitative data on inputs) is anessential element to allow simulation models (especially those based on mathe-matical programming) in order to define the technology used by that of singlefarms. Consequently, the lack of such data excludes the use of FADN for thepurposes of analysis of agricultural policy through the use of mathematical pro-gramming. The limits on the representativeness of FADN data also make it difficultto represent production systems in areas smaller than NUTS3 and perform statis-tical inferences to the statistical universe. To overcome this limitation, AGRISPintegrates FADN with the Italian administrative database AGEA.1 The integrationof FADN and AGEA thus makes it possible to measure the exact dimension ofagricultural production systems, gross marketable output, subsidies distributed, the

1 AGEA is the Italian official body entitled to pay farmers eligible for CAP payments. Farmershave to provide AGEA with all the information related to agricultural activities including land use.


volume of variable costs attributable to each process, and the gross income for eachtype of activity.

The two databases combined in a single database FADN-AGEA give a com-plete dataset of land use and technical and economic parameters for productionprocesses of all the farms included in the analysis. The aggregation of informationis performed at the level of macro-farm (farms in the AGEA database grouped bysize) and farm specialization by each agricultural area (a homogeneous altitudearea belonging to the same province). More precisely, in each province threealtitude levels, seven size classes (0–10 ha, 10–20 ha, 20–30 ha, 30–50 ha,50–100 ha, 100–300 ha, [300 ha) and three economic sectors (Fruit and vegeta-bles, Animal production, and Others) were considered, where each class representsthe minimum farm type reference. Naturally each macro-farm considers all agri-cultural activity present in the territory as they are registered in the AGEA data-base. The integration of the two databases was effected by specific software able toperform statistical analysis and yield information on farmer choices on productionand economic indicators.

20.3.2 AGRISP Model Overview

The AGRISP model is able to estimate for each province and at the overallregional level the effects of CAP measures on farmer production plans and farmerincome. It gives insight into production decisions for the current observed situation(baseline) and into future decisions after the CAP reform, and thus models farmerstrategy. The AGRISP model consists of three main phases: (i) Extraction of dataon farms in the sample; (ii) PMP estimation of cost functions at macro-farms level,calibration to observe reality and simulations; and (iii) Analysis of results.AGRISP can be defined as a regional tool, because in a single resolution it cansimulate the effects of agricultural policies on different homogeneous areas(agricultural regions) constituting the administrative regions (provinces). It canalso be defined as ‘‘integrated’’ because it includes modules that manage the flowof information for the functional analysis of agricultural policy. The process oforganizing information is probably the most innovative element. AGRISP providesinformation on the production choices made by individual farmers, capturing theirstrategies in the prereform situation and in projected results organized by agrarianregions and at the regional level. The use of a single database covering land use(from AGEA) and the profitability of single processes (from FADN) combinedwith PMP methodology allows analysis of the impact of agricultural policies bothat the micro- and macro-level. It is useful for both setting rural policies andestimating changes in supply at the regional level. In simulating the effects ofagricultural policy at the regional level, AGRISP aggregates cost functions into asingle regional model, and constructs a set of constraints able to simulate thepolicies for the whole region (Fig. 20.3).


20.4 The Policy Scenario

In this evaluation of the CAP reform, three main aspects have been consideredbased on the regulation proposal of the European Commission n. 625-COM2011.These are basic payments, greening measures, and capping.

Direct Payments will follow the new Basic Payment Scheme. Until today, theEU-15 was covered by a Single Payments Scheme allowing for historical refer-ences, or a payment per hectare, or a ‘‘hybrid’’ combination of the two, and most ofthe EU-12 was covered by the Single Area Payments Scheme (SAPS). From 2013,a single new ‘‘Basic Payment Scheme’’ applies. The aim is to significantly reducediscrepancies between the levels of payments between farmers, between regions(internally) and between MS through full implementation of current legislation.All MS will be obliged to move toward a uniform payment per hectare at thenational or regional level by the start of 2019. In line with the Commissionproposals in the Multi-Annual Financial Framework, the national envelopes fordirect payments will be adjusted so that those who receive less than 90 % of theEU-27 average payment per hectare will receive more. The gap between currentpayments and 90 % of the EU-27 average is reduced by one-third. The Com-mission is committed to discussing a longer term objective of achieving ‘‘completeconvergence’’ through equal distribution of direct support across the EuropeanUnion in the next Financial Perspectives after 2020.

In addition to the Basic Payment, each farm will receive a payment per hectarefor following farm practices beneficial for the climate and the environment. MSwill use 30 % of the national envelope in order to pay for this. The draft proposal

Fig. 20.3 Data structure in the AGRISP model


of the European Commission states that this payment will be mandatory, and willnot be subject to capping. The three practices eligible for payment are: (i) main-taining permanent pasture, (ii) implementing crop diversification (at least 3 cropson arable land, none of which account for more than 70 % of the land, and thethird crop at least 5 % of the arable area); and (iii) maintaining an ‘‘ecologicalfocus area’’ of at least 7 % of farmland (excluding permanent grassland). This areamay include field margins, hedges, trees, fallow land, landscape features, biotopes,buffer strips, and wooded areas.

The capping mechanism will define the amount of support that any individualfarm can receive from the Basic Payment Scheme. The sum will be limited to€300,000 per year. Current payment levels will be reduced by 70 % for the partfrom €250,000–300,000; by 40 % for the part from €200,000–250,000, and by20 % for the part from €150,000–200,000. However, in order to take employmentinto account, the farm can deduct the costs of salaries, including taxes and socialsecurity contributions, declared the previous year, before these reductions areapplied.

The AGRISP model is now applied to Emilia-Romagna to evaluate the effectsof the new EU support measures in the agricultural sector. Results are detailed atthe regional and provincial level, and by altimetry. The following scenarios areidentified:

1. Baseline The base scenario on which the comparison is carried out is thesituation recorded in 2010, obtained by updating the 2007 calibrated solutionwith the market price variation for 2007–2010.

2. Greening This scenario simulates full application of the CAP reform. Allconstraints and the new policy aids are activated (new Basic Payment Schemewith distribution to all Utilized Agricultural Areas (UAA), mandatory greeningscheme, and new capping mechanism).

For the value of aid per hectare for the Emilia-Romagna region, the amountcalculated by the National Institute of Agricultural Economics is a basic region-alized payment of 148.4€/ha, while for the greening component they calculate89.4€/ha. These figures are used in our simulations, which also consider thereduction of total aid under the mechanism of gradual reduction according to thescale described above.

20.5 The Impact of Policy

20.5.1 Variation in Land Use

Results of land use by single process simulations show changes between thecurrent baseline scenario and after reform in the greening scenario. Figure 20.4reports the results in hectares, and Table 20.1 reports the results in percentages.


The results show that at the regional level, greening will lead to a big reduction ofalmost 38,000 ha in cultivated areas. There will be different impacts on variouscrops as farmers adjust production choices to market prices.

Basically there will be a decrease in almost all crops, except for certain cereals(barley, oats, etc.) which show a big increase (+18 %). But there will be bigdecreases in surface areas of wheat (-4.3 %) from the current 114,000 ha to about

Fig. 20.4 Variation inagricultural land use


110,000 ha, maize (-6.0 %) by about 75,500 ha, other seed crops (e.g., sunflower)by 1,000 ha (-10.5 %), and the biggest decrease will be in fodder (-10.6 %),which decreases from the current 264,000 ha to about 236,000 ha.

As noted, the decrease in fodder by about 30,000 ha is the largest. It is probablydue to two main factors; the steady increase in profits on cereal crops especially inrecent years, and low market profits on fodder crops excluding crops used forbreeding. These changes are extremely significant for Emilia-Romagna becausefodder tends to take place prior to abandonment of the land. Greening measureswould further bring down farm profits. The lowering of fodder crop is justified alsoby the choice of entrepreneur to use this type of crop for environmental purposes asrequired by greening measures. This type of adjustment entailed by the CAP reformillustrates how the market will now drive production choices for farmers, who willno longer focus on maximizing payments but will have to maximize farming profitsinstead. Table 20.2 shows the variation in land use by altimetry bands.

20.5.2 Variation in Economic Values

Table 20.3 shows the changes in economic components per hectare at regional andaltitude levels. Gross Salable Production (GSP) falls by 7.4 % from the current3,276€/ha to 3,033€/ha. This is mainly because part of the land is taken out ofproduction to meet greening requirements. The values of GSP by altimetry bandspresent a heterogeneous distribution: contraction on plains is about -5.2 %, whilehills and mountains decrease by -10.8 and -20.5 %, respectively. The reductionin variable costs (-7.7 %) is in line with the changes in GSP as farms make themandatory adjustments required by greening and halt production of certain crops.

Table 20.1 Detailed variation in agriculture land use

Processes Baseline (ha) Green (ha) Base/green(Variation in %)

Wheat 113,935 109,008 -4.3Corn 80,476 75,665 -6.0Other cereals 21,665 25,639 +18.3Rice 7,865 7,576 -3.7Soybean 21,608 20,732 -4.1Other oil seeds 9,180 8,214 -10.5Sugar beet 72,711 71.863 -1.2Tomato 28,518 27,837 -2.4Fodder 263,784 235,802 -10.6Permanent meadows and pastures 11,073 11,473 +3.6Other crops 39,020 38,397 -1.6Surface greening 0 37,630 –Total 669,835 669,835 –


These dynamics appear mainly in plain and hill areas, while in mountain areas thestructural rigidity of production does not permit a reduction in variable costsproportional to the fall in GSP. The gross margin at the 1st level, calculated bysubtracting variable costs from GSP, which is an indicator of business efficiency, is

Table 20.2 Variation of agriculture land use by altimetry

Plain Hill Mountain

Processes Greening (ha) VAR(%)(ha)

Greening (ha) VAR(%)(ha)

Greening (ha) VAR(%)(ha)

Wheat 91,274 82167 -9.9 21,867 22,473 2.8 795 4,367 449.5Corn 72,678 67.456 -7.2 7,744 8,072 4.2 54 137 154.1Other cereals 11,556 10,745 -7.0 9,278 10,558 13.8 831 4,336 422.0Rice 7,865 7,576 -3.7 – – – – – –Soybean 21,354 20,495 -4.0 254 237 -6.9 – – –Other oilseeds 8,882 7,946 -10.5 298 268 -10.1 – – –Sugar beet 70,629 69,759 -1.2 2,082 2,104 1.1 – – –Tomato 23,558 22,837 -3.1 4,928 4,965 0.8 32 34 6.2Fodder 122,733 115737 -5.7 93,720 83,484 -10.9 47,331 36,580 -22.7Pastures 1,916 1,966 2.6 5,291 5,485 3.7 3,866 4,022 4.0Other crops 36,110 35,485 -1.7 2,882 2,852 -1.0 28 60 114.9Surface

greening– 26,385 – – 7,844 – – 3,401 –

Table 20.3 Variation of economic indicators at regional and altimetry levels

Baseline (€/Ha)

Green (€/Ha)

VAR(%)

Region level GSP 3,276 3,033 -7.4– Total variable costs 2,356 2,176 -7.7= Gross margin (1� level) 920 857 -6.9+ Total AID 307 237,8 -22.5= Gross margin (2� level) 1,227 1,095 -10.8

Plain areas GSP 3,416 3,238 -5.2– Total variable costs 2,494 2,354 -5.6= Gross margin (1� level) 922 884 -4.1+ Total AID 339 237 -29.9= Gross margin (2� level) 1,261 1,122 -11.1

Hills areas GSP 2,922 2,606 -10.8– Total variable costs 2,051 1,801 -12.2= Gross margin (1� level) 871 804 -7.6+ Total AID 246 237,8 -3.4= Gross margin (2� level) 1,117 1,042 -6.7

Mountainareas

GSP 3,029 2,409 -20.5– Total variable costs 1,989 1,646 -17.2= Gross margin (1� level) 1,041 763 -26.7+ Total AID 186 237 27.6= Gross margin (2� level) 1,227 1,001 -18.4


thus affected in different ways. Overall in the region it falls by 6.9 %; but while inplain areas it falls -4.1 %, and in hill areas it falls -7.6 %, in mountain areas itfalls by -26.7 %.

As noted above, total payments, now consisting of regionalized basic pay-ment + greening payments, are reduced across the region by 22.5 %, from €307/hato €237.8/ha on average. Taking this decrease into account, the new distribution ofaid over plain and hill areas leads to a contraction which poorly affects what wemight call the 2nd level gross margin or 1st level gross margin + aid. In mountainareas, the new distribution of payments is advantageous given that currentlyaverage aid per hectare stands are only 190€/ha. Overall, however, across theregion, the reduction of 2nd level gross margin falls by nearly 11 %. The reorga-nization imposed by regionalization and greening measures will clearly have anegative impact on the overall agricultural sector of the Emilia-Romagna region.

Data disaggregated by province shows differing situations across the region. Atthe province level, without considering altimetry: GSP/ha decreases by -11 % inthe provinces of Bologna (BO), Modena (MO), Parma (PR), and by -14.3 %in Reggio-Emilia (RE), but there is a smaller contraction of between 5 and 7 %in the remaining provinces. The bigger reduction in the first group of provinces isclosely linked to the decline in livestock at each altimetry.

Figures 20.5, 20.6, 20.7, and 20.8 report a more detailed analysis of reformeffects, and show values specified for different altitude levels and provinces. TheGSP (Fig. 20.5) is affected by a big reduction in the mountainous areas of Parma,Reggio-Emilia, Modena and Bologna, with decreases in values that range from-15 to -25 %, while in hill areas (except for Bologna) show decreases ranging

Fig. 20.5 Variation in GSP


from -15 to -20 % approximately. The second graph (Fig. 20.6) reports dis-similarity in total variable costs. In general these are aligned with the decreases inGSP as processes are adjusted. But in some areas, such as mountain areas of Parmaand Modena, where farms show more structural rigidity, the realignment is less

Fig. 20.6 Variation invariable costs

Fig. 20.7 Variation in 1stlevel gross margin


proportional. For this reason, 1st level gross margin (Fig. 20.8) downsizes inmountainous areas: Parma -45 %, Reggio-Emilia -25 %, Modena -30 %.

Finally, Fig. 20.8 shows the changes in the 2nd level gross margin. This marginincludes the effect of aid redistribution where mountain areas receive the mostadvantage. But mountain areas and some hilly areas confirm the biggest falls:Parma (-33.4 %), Reggio-Emilia (-21.1 %) and Modena (-23.4 %), and allshow values well below the regional average of 11.9 %.

20.6 Conclusion and Policy Recommendations

The model shows that greening measures combined with the regionalized distri-bution of basic payments will lead to substantial reductions in terms of GSP andfarm income in Emilia-Romagna, assuming constant prices. The biggest conse-quences at farm level will be covering fixed investment costs. Greening generatesa double effect: a contraction of harvested surfaces (e.g., forage, wheat, and maize)and a big shift in land use and resources toward higher price crops (e.g., cerealsand tomatoes). The extension of regionalized aid to almost all UAAs with a singlepayment level in all regions, accompanied by a reduction in the amount of aid, willlower average aid per hectare for the plain areas, where at present farmers areaccustomed to higher levels of support, in favor of mountain areas. But despite theincrease in direct payments for mountain areas, these are the most badly hit by thereform. Ongoing discussion between the DG-AGRI Committee and the Trilogue iscurrently focusing on adjusting some of the greening criteria, both in terms of

Fig. 20.8 Variation in 2ndlevel gross margin


practical application and access to specific aid. As noted previously, this analysiswas made on the basis of the European Commission draft proposal, so numericalmeasurements may be taken as provisional and attention should be focused moreon the structural and territorial weaknesses.

But the potential impacts of the CAP reform require discussion and debate. Ascurrently formulated, the proposal offers fewer guarantees to specific local andterritorial farmers in that it delegates to an individual MS the decision to apply foraid as ‘‘less-favored areas,’’ or to maintain coupled aid for ‘‘productions with alocal relevance.’’ This entails direct intervention by MS policy makers in order toactivate specific and voluntary schemes. Given that ‘‘the market’’ will be the newdriver for production choices by farmers, the strategic choices of European agri-culture will have to take account of the need to protect local farms and entireproduction sectors in disadvantaged areas, such as diary or livestock farming inhill and mountain areas. A new mindset will be necessary; the lack of competi-tiveness of farms in regional mountain areas is due in most cases to territorialcharacteristics and economic environment rather the competitiveness of the farmitself.

References

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Arfini F., & Donati M. (2011). Impact of the Health Check on structural change and farmefficiency: A comparative assessment of three European agricultural regions—in Disaggre-gated Impacts of CAP Reforms Proceedings of an OECD Workshop OECD Publishing.

Arfini, F., & Donati, M. (2013). Organic production and the capacity to respond to market signalsand policies: An empirical analysis of a sample of FADN farms. Agroecology and SustainableFood Systems, 37(2), 149–171.

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De Filippis, F., & Frascarelli, A. (2012). Il nuovo regime dei Pagamenti diretti in agricolturaIn F. De Filippis (Ed.) (A cura di), La nuova Pac 2014–2020-Un’analisi delle proposte dellaCommissione, Quaderni gruppo 2013, Edizioni Tellus.

European Commission. (2011a). Proposal for a Regulation of the European Parliament and ofthe Council establishing rules for direct payments to farmers under support schemes withinthe framework of the common agricultural policy. Brussels, 19.10.2011 COM(2011) 625 final/2 2011/0280 (COD).

European Commission. (2011b). Impact Assessment. Common Agricultural Policy towards 2020.Annex 2: Greening the CAP, Commission Staff Working Paper, Brussels, February.

Gigante R. (2013). Assessment of Cap reform post 2013 in rural areas of Emilia-Romagnaregion. Ph.D. thesis.

Heckelei, T., Britz, W., & Zhang, Y. (2012). Positive mathematical programming approaches—recent developments in literature and applied modelling. Bio-based and Applied Economics,1, 109–124.


Heckelei, T. & Britz, W. (2005), Models based on positive mathematical programming: State ofthe art and further extensions In F. Arfini (Eds.), Modelling agricultural policies: state of theart and new challenges. Proceedings of the 89th European seminar of the EuropeanAssociation of Agricultural Economics, (pp. 48–73). Monte Università Parma.

Matthews, A. (2013). Greening agricultural payments in the EU’s Common Agricultural Policy.Bio Based and Applied Economics, 2(1), 1–27.

Sorrentino, A., Henke, R., & Severini, S. (2011). The common agricultural police after thefischler reform, national implementation, impact assessment and the agenda for futurereforms. Burlington: Ashgate.


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Assessment cap reform 2014 2020 in Emilia-Romagna Region