Factors Affecting Participation of Italian Farmers in Rural Development Policy

Transcription

1 Paper prepared for the 122nd EAAE Seminar "EVIDENCE-BASED AGRICULTURAL AND RURAL POLIC MAKING: METHODOLOGICAL AND EMPIRICAL CHALLENGES OF POLIC EVALUATION" Ancona, February 17-18, 2011 Factor Affecting Participation of Italian Farmer in Rural Development Policy Pacucci S. 1, Capitanio F. 2, Adinolfi F. 3 and De Magitri T. 4 1 Wageningen Univerity, Agricultural Economic and Rural Policy Group, Wageningen, Netherland 2 Univerity of Naple Federico II, Department of Agricultural Economic and Policy, Napoli, Italy 3 Univerity of Bologna, Department of Agricultural Economic, Bologna, Italy 4 Agro-Food Economic Unit Center for Agro-Food Reearch and Technology (CITA), Spain capitani@unina.it Copyright 2011 by Stefano Pacucci, Fabian Capitanio, Felice Adinolfi, Tiziana De Magitri. All right reerved. Reader may make verbatim copie of thi document for non-commercial purpoe by any mean, provided that thi copyright notice appear on all uch copie.

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3 Factor Affecting Participation of Italian Farmer in Rural Development Policy Pacucci S., Capitanio F., Adinolfi F. and De Magitri T. Abtract In thi paper a (micro)econometric approach i developed by conidering the farmer likelihood to participate in different policy program a linked to the obective of farmer to maximize their welfare. In thi way we model farmer participation in policy upport cheme by uing a new intitutional economic approach and conceptualizing the deciion to entry a a contractual choice between two rural development type of policy. Different dicrete choice modelling approache are ued to analyze the complementarity/ ubtitutability of different policy program uch a environmental-related meaure and farm invetment upport policy cheme and the main driving factor behind them. We ue an extenive cro-ectional databae related to the Italian FADN Reult indicate that ocial capital and intitutional factor hould be taken much more into account in order to undertand farmer likelihood to entry in policy upport cheme. Location and farm(er) ocio-economic feature are alo relevant factor. Moreover complementarity ha been found between different policy cheme. Keyword: Rural development policy, contract deign, dicrete choice modelling, Italy JEL claification: Q12, Q INTRODUCTION Rural Development Policy (RDP) i a coniderable ource of financial upport for European farmer and rural communitie (Dwyer et al., 2008). Still many farmer and rural actor are not benefiting adequately from RDP, mainly due to lack of capacitie to acce and ue thi financial upport. If, however, factor that contitute a barrier to participate could be better undertood and adequately addreed, a larger number of farmer and rural actor could benefit from RDP upport and increae their welfare. Unfortunately thi mechanim i till not completely clarified. Previou paper have tudied farmer motivation for participating in different RDP meaure. Thee paper have been focalized mainly on farmer participation in Agro- Environmental Scheme (AES) in different EU context 1. They have hown that deciion are driven by a plurality of potential factor uch a farm tructural feature, pecialization, nonfarm activitie, local context, policy network, intitution, farmer attitude (Beedell and Rehman, 2000; Wynn et al., 2001; Defranceco et al., 2008). The way thee factor interact and influence the farmer likelihood to enter or not in RDP meaure i crucial to undertand the capacity of a policy intervention to be ucceful but gap and puzzling iue till remain. 1 The lit of paper analyzing European farmer participation in agri-environmental cheme and meaure i extenive. Intereting overview have been recently provided by Defra (2006) and Defranceco et al. (2008). 3

4 For example whether or not participating in AES alo increae the farmer likelihood to participate in other type of RDP meaure uch a invetment and marketing-related one. If uch correlation and interrelation do exit, thee factor might be ued to better predict farmer behavior. We propoe to take a firt tep in developing a predicting model. Therefore the aim of thi paper i to analyze the likelihood of Italian farmer to participate in different policy program. More pecifically we aim at anwering the following reearch quetion: (i) what combination of factor correlate ignificantly with the occurrence of participation in RDP meaure? (ii) To what extent do the factor explain the variance of participation in RDP meaure by different type of farmer? (iii) What i the pecific role of intitutional factor? To addre thee reearch quetion we decide to model farmer participation in RDP meaure by uing a new intitutional economic approach and conceptualizing the deciion to participate a a choice between different contractual olution (Maten and Sauier, 2002). A (micro)econometric approach ha been developed by conidering the farmer likelihood to participate in different Rural Development Policy related contract (RDP contract) a linked to the obective of farmer to maximize their welfare. Our hypothei i that different RDP contract could be implemented at farm level to reach thi goal imultaneouly. Accordingly we model the choice etting a contitute by two main type of RDP contract: a firt type which related to cheme upporting economic competitivene of the farm, uch a invetment and marketing (SCS); a econd type which relate to cheme upporting the proviion of environmental ervice, uch a AES, afforetation and extenification (SAS). The contractual deign perpective ha been applied in everal context and it i in line with other paper approach which trie to model farmer participation in AES and RDP meaure (Jongeneel et al., 2008; Polman and Slangen, 2008; Peerling and Polman, 2004; 2008; 2009). In thi approach the role of intitutional factor, uch a ocial capital, local network, formal rule of a given ocio-economic context can be emphaized and pecifically addreed. Moreover in thi approach both contractual deign and aociated tranaction cot aume a central role to define the explanatory variable involved in the farmer deciion making. To empirically tet our reearch quetion we ue an extenive cro-ectional databae related to the Italian FADN The econometric trategy i reflected in the application of two different dicrete choice modelling approache, uch a a bivariate probit (BVP) model (model 1) and a multinomial logit (MNL) model (model 2). The BVP i ued to analyze the complementarity/ubtitutability of different policy program uch a SCS and SAS contract (Polman and Slangen, 2008); the MNL model follow the uual econometric approach to analyze thi type of farmer behavior and it i alo ued a benchmark (Defranceco et al., 2008; Peerling and Polman, 2009). To our knowledge thi i the firt paper which trie to approach farmer participation in different type of RDP contract and to quantify the interconnection between them uing thi econometric trategy. The reult are compared with other concluion provided in other paper in order to ue our Italian cae tudy in the overall dicuion around participation of 4

5 the European farmer in RDP contract. Thee reult are rather new for the Italian context and they can contribute to improve policy-making debate at the EU level. 2. THEORETICAL MODEL In thi paper we ue a model originally introduced by Peerling and Polman (2009)2 by extending it to all type of RDP contract. In the PP model it i aumed that farmer maximie the expected value derived from the individual contract elected. Therefore by chooing a contract farmer allocate (part of) their reource (i.e. land and capital) to that contract. Typically in AES contract reource allocation involve farmland while in other type of RDP contract, uch a invetment upport cheme, it mainly involve capital good (building, machinerie, financial capital). In thi model if an unit of reource i ued for contract A (i.e. one hectare i enrolled in biodiverity protection contract) it cannot be ued for contract B (i.e. land improvement). However, a in the original PP model it will be aumed that more than one contract can be elected by one farmer (Peerling and Polman, 2009). So the model can be perceived a a reource allocation model. Farmer deciion pace relate to the optimal allocation of reource ( θ ) in order to maximie her expected value () deriving from contracting deciion 3 : ubect to: S ( ) = max E θ = 1 (1) = p θ C ( θ, γ ) S (2) S γ = γ ( X ); γ 0 γ 1 S (3) = 1 S θ = θ = 1 (4) θ 0 S (5) where E i expectation operator; total value from contracting for farmer ; i the value of chooing contract by farmer ; the allocation of one unit of reource to contract by farmer ; p i the payment/upport received by farm due to C i the total cot of contract 2 Later on we refer to Peerling and Polman (2009) model a PP model 3 To model thi etting of contractual deciion making we follow argument from Peerling and Polman (2009) and Maten and Sauier (2002) and we adapted them to the pecific purpoe of thi paper. 5

6 by farmer ; X i a vector of farm and farmer characteritic and feature related to farm location uch a geographical, ocio-economic and intitutional factor. γ i the probability that contract i choen by farmer ; θ repreent the farmer reource allocated to contract ; θ reource availability of farm. Equation (1) indicate that the total expect value i the um of the value from the elected contract. Non participation in policy-related contract lead to zero profit while profit from other activitie are ignored a in the original PP model etting (Peerling and Polman, 2009). In other word profit from other than policy-related contract are not relevant in the deciion making proce we are analying here. Equation (2) how that value from policy-related contract equal benefit minu cot, where revenue refer to payment per unit of reource time the total amount of reource allocated to the contract for the farmer. Benefit from RDP contract can be of variou type. For example in cae of meaure related to Support Competivene Scheme (SCS), uch a an invetment-related proect linked to the modernization of agricultural holding. Thi type of RDP meaure aume the form of a tranfer of financial reource. Thi tranfer i proportional to the overall amount of (private) financial reource which will be dedicated by the farmer to the proect. In cae of Support Agri-environmental Service (SAS) benefit aume the form of a per hectare payment, a a compenation of reduced revenue (Polman and Slangen, 2008: Peerling and Polman, 2008; 2009). Cot of contract include the tranaction and opportunity cot (forgone profit) deriving from the contract commitment. Tranaction and opportunity cot are generated by the nature of the contractual relation between the public agency and the farmer. Thi i often decribed a a principal-agent relationhip (Ozanne et al., 2001; White, 2002; Ferraro, 2008). A a conequence farmer experience both ex-ante and ex-pot tranaction cot when they have to decide whether or not to participate to an RDP contract. Search and information cot are typical ex-ante tranaction cot experienced by farmer to get information about funding opportunitie. Farmer are concerned with information related to the contractual etting, therefore the level of upport, the type of penaltie and the additional production contrain due to contract commitment. Negotiation cot are the cot of carrying out the tranaction and may include adminitrative and legal cot, uch a the cot of negotiating the term of the agreement, and the cot of formally deign the contract (Hobb, 1997). Ex-pot tranaction cot are for example monitoring cot which occur to the farmer in order to enure that the term of the RDP contract are adequately fulfilled (i.e. he ha provided the requeted amount and quality of environmental ervice). The pecific benefit and cot of equation (2) are unknown in the context of thi paper. Therefore we aumed that they are dependent on explanatory variable which are known and meaurable uch a farm reource allocated in the contract and farmer probabilitie to participate (Maten and Sauier, 2002; Peerling and Polman, 2009). Equation (3) give the probabilitie for entering into a contract a a function of farm and farmer characteritic, intitutional factor and location. Equation (4) indicate that the 6

7 total amount of farm reource equal thoe allocated under the different contract while equation (5) i the non-negativity contrain for allocated reource. 3. ECONOMETRIC STRATEG A pointed out by Peerling and Polman (2009) it i traightforward that in the theoretical model we are uing we aume that where cot increae then the probability of participation in a RDP contract decreae (and vice-vera). A high probability i aumed to be correlated to low (expected) cot aociated with RDP contract, whilt a low probability i linked to high (expected) cot (Peerling and Polman, 2009). Farm and farmer characteritic that increae the probability are likely to correlate with low cot. The ame applie for both intitutional iue and location. A widely ued approach to etimate the probabilitie of chooing different contractual olution i to implement a dicrete-choice model (Maten and Sauier, 2002). In thi cae the oberved contractual choice i conidered a an expreion of a continuou latent variable reflecting the propenity to chooe a pecific option among different alternative (Defranceco et al., 2008). The generic empirical model related to farm to chooe a RDP contract can be written a follow: * = X β + ε S (6) = 1 = 0 if * otherwie > 0 S (7) where * i the unobervable value of the contract for farmer (latent variable), i the obervable contract choice, defined in equation (3), X i the vector of explanatory variable for farmer a β a vector of coefficient for contract and ε a vector of unobervable characteritic related to farmer and contract. Re-arranging equation (3), (6) and (7) we can derive the probability that contract i choen by farmer ( γ ) a a function of the potential explanatory variable: * γ = P( = 1) = P( > 0) = P( X β + ε > 0) = P( ε > X β ) = F( X β ) (8) where F denote the ditribution function of the unobervable characteritic ε. Different econometric trategie can be implemented accordingly to the nature of the contractual choice analyed and the ditributional form it i aumed for F (Verbeek, 2004). For example a relatively common approach i to ue eparate logit/probit model to depict the baic binary choice of participation or non-participation in a given RDP contract (Dupraz et 7

8 al., 2002; Damiano and Giannakopoulo, 2002; Woink and van Wenum, 2003; Vanlembrouck et al., 2002). In thi cae the deciion etting i about (1) chooing a SCS type of contract (or not chooing thi type of contract) and (2) chooing SAS (or not chooing thi type of contract). Thi would lead to a ytem of (two) equation. The implicit aumption i that the probability of chooing SCS i independent from the probability to chooe SAS type of contract. But there i a good chance that the farmer likelihood to chooe SCS i conditional to the deciion whether or not to chooe SAS type of contract. In other word thee deciion are likely to be interrelated. The uual alternative would be to etimate a multivariate probit model (Polman and Slangen, 2008). With the multivariate probit model again there are everal deciion, each between two alternative. However, for each choice a probit model i etimated it i aumed that the error term for the equation are correlated. In the logit, probit and multivariate probit model the explanatory variable can be identical between equation (choice made), but are not necearily o. Therefore each choice can have it own explanatory variable. A pointed out by Peerling and Polman (2009) the main diadvantage of both eparate logit/probit and multivariate probit approache i that probabilitie are difficult to interpret becaue a normalization of probabilitie i miing (Verbeek, 2004). Each RDP contract i compared to all other choice. In other word, the probability of chooing a SCS contract cannot be explicitly linked to the probability of chooing an AES contract. Another often ued approach i to et a multiple-choice deciion-making proce uing multinomial model to invetigate both participation deciion and participation in different RDP contract (Wynn et al., 2001; Dupraz et al.,2002; Epinoa-Goded, 2010). In a multinomial logit model uch a normaliation take place becaue the probability of electing a RDP contract i determined relative to the probabilitie of other poible contractual choice (Verbeek, 2004; Greene 2008). A diadvantage of the multinomial logit i that it aume that either one contract or no contract i elected (ut a in a normal logit or probit) not conidering that a farmer can participate more than one RDP contract (ee Peerling and Polman, 2009). Given the opportunitie and limitation of each of the above dicued approache and given the purpoe of thi paper our econometric trategy i to implement both a BVP model (model 1) and a MNL model (model 2) Model 1: the Bivariate Probit (BVP) With a bivariate probit model approach the empirical model related to farm to chooe a RDP contract can be written a follow: * = X β + ε S (8) = 1 = 0 if * otherwie > 0 S (9) 8

9 where * i the unobervable value of the contract for farmer (latent variable), i the obervable contract choice, for = 1 in cae of SCS type of contract and = 2 in cae of SAS type of contract. A defined in equation (3) farmer, X i the vector of explanatory variable for β a vector of coefficient for contract and ε a vector of unobervable characteritic related to farmer and contract. The BVP model enable u to model farmer deciion to chooe more than one contract imultaneouly (Greene, 2003; Capellari and Jenkin, 2003). Since the outcome are treated a binary variable any combination of contract i poible. The contract can be complement rather that ubtitute only (Polman and Slangen, 2008). The two equation model (one for = 1 and the other for = 2) i featured by correlated diturbance, which (due to identification reaon) are aumed to follow a normal ditribution (variance i normalized to unity). That i for each th farmer: E [ ε 1 ] = E[ ε 2 ] = 0 [ ε ε ] = ρ = { ρ } cov, (10) 1 ] = var[ ε ] = 1 var[ ε 2 where ρ i a vector of correlation parameter denoting the extent to which the error term co-vary. Should thi be the cae, we would need to etimate the two equation ointly, following a bivariate normal ditribution: { ε ε } φ ( 0,0,1,1, ρ), =. Becaue in thi model we are intereted in imultaneou contractual deciion we have to define the oint probability. For example, the probability of farmer of chooing the two type of RDP contract at the ame time ( 1) γ 1 = 2 = β, X would be: = P( 1 = 1, 2 = 1) = φ2 ( 1 β1, 2 X X β 2, ρ) dε1 dε 2 (11) = Φ ( X β ) 2 ε 1 ε 2 In thi model the log-likelihood i then a um acro the four poible contracting and non- variable (that i, four poible combination of participation ( 1 = 2 = 1) participation ( 0) 1 = 2 = time their aociated probabilitie (Greene, 2003). Thee probabilitie may be drawn from (11) a well. The mot relevant coefficient etimated in the model are β 1, β 2 and ρ ( ρ 12 ). The latter, if ignificantly different from zero, will evaluate to which extent each pair of deciion are interrelated. 9

10 3.2. Model 2: the Multinomial Logit (MNL) In the MNL approach the empirical model related to farm to chooe a RDP contract can be written a follow: * = X β + ε S (12) = 1 = 0 if * otherwie > 0 S (13) where * i the unobervable value of the contract for farmer (latent variable), i the obervable contract choice, for = { 0,1,2,3 } repreenting the four different RDP contractual combination uch a non-participation (=0), participation in SCS (=1) only, participation in SAS (=2) or both SCS and SAS (=3). X i the vector of explanatory variable for farmer a defined in equation (3), β a vector of coefficient for contract and ε a vector of unobervable characteritic related to farmer and contract. With a multinomial logit function the probability that a farm elect a contract (or doe not participate) i given by: exp( X β ) γ = P( = 1) = 3 S (14) exp( X β ) = 0 4. DATA The empirical analyi on Italian farmer participation in RDP meaure i baed on the information from the 2006 Farm Accountancy Data Network (FADN). Thi dataet contain detailed information on more than 15,000 farm buinee. The Italian National Intitute of Agricultural Economic (INEA) i reponible for collecting and organizing the FADN on a yearly bai. The data i repreentative for the population of farmer in Italy and it i in line with the formal procedure of the European Commiion. Data i counter-checked by the National Intitute of Statitic (ISTAT). The ample i tratified on three key variable, i.e. location (21 NUTS2 region), economic ize (6 clae) and farm type (19 typologie) (INEA, 2006). We ue the information related to farm location to attach ite pecific variable to each obervation. In 2006 FADN recorded farmer participation in RDP meaure related to the different Regional Rural Development Plan a defined by the Council Regulation (EC) 1259/99. Accordingly we define the two type of RDP contract (SCS, SAS) a decribed in table A1 in the Appendix. 10

11 Table 1 how that a relatively mall hare of Italian farm i engaged in RDP contract. Table 1: RDP contract in Italian farm, 2006 Share of farm Type of RDP contract Non-convergence region Convergence region 4 Italy 1. Supporting Competitivene Scheme (SCS) Supporting Agri-Environmental Service (SAS) Source: own calculation baed on FADN (2006) Table 2 decribe the explanatory variable that are ued to explain the choice of RDP contract. Accordingly to the theoretical model we elect four group of explanatory variable and namely farm and farmer characteritic, intitutional characteritic and location. Table 2. Decription of variable Farm characteritic Variable Explanation Mean Internal factor (farm/farmer) Standard deviation Farm ize mall (a) 1 if farm < 16 ESU Farm tructure fixaet (a) Total fixed aet 8,710 23,531 arable (a) 1 if pecialized in arable crop production Farm pecialization horticult (a) 1 if pecialized in horticulture perm_crop (a) 1 if pecialized in permanent crop Labour ue livetock (a) 1 if pecialized in livetock lu_uaa (a) Labour intenity meaured in Annual Working Unit (AWU) per hectare of Utilized Agricultural Area (UAA) fam_labor (a) % AWU provided by family member offfarm 1 if family off-farm labour i preent Land tenancy uaa_rent (a) % UAA rented dev_plan (a) 1 if farm followed a buine plan for Farm management development acc_erv (a) 1 if farm ued an accountancy ervice Farmer characteritic Type of land manager manager (a) 1 if manager alo provide farm labour Farmer age age (a) Number of year Preence of ucceor ucce (a) 1 if a ucceor i preent Social capital External factor Social ecurity (trut) crim (d) % of houehold with high perception of A defined by the EU regulation on Structural Fund in the period the Italian region belonging to the Obective 1 Convergence were Campania, Bailicata, Apulia, Molie, Calabria, Sardinia and Sicily. 11

12 Network Farm location Variable Explanation Mean criminality Standard deviation coop (a) 1 if member of agriculture-related cooperative aoc (a) 1 if member of an aociation South outh (b) 1 if located in outh Italy Population denity pop_den (c) Population denity per quare km Mountain mount (b) 1 if located in a mountainou area Source: (a) INEA, 2006; (b) MIPAAF, 2007; (c) ISTAT, 2001 (d) ISTAT, 2006 Among farm characteritic firm ize, pecialization and tructure are conidered of primarily importance to explain farmer participation for example in different agrienvironmental contract (Wynn et al., 2001; Damiano and Giannakopoulo, 2002; Vanlembrouck et al., 2002; Polman and Slangen, 2008; Defranceco et al., 2008; Peerling and Polman, 2009). Previou finding confirm that the type of AES contract ued by farmer i different depending on the type of farming ytem (Wynn et al, 2001; Vanlembrouck et al., 2002; Polman and Slangen, 2008). For example participating in an agri-environmental cheme in an intenive and pecialized dairy farm will be different from implementing the ame contract on a pecialized arable farm (Polman and Slangen, 2008). We alo include variable related to farm management, family labour and off-farm income. For example Jongeneel et al. (2008) indicate that income from non-farming activitie ha an important and poitive role in conditioning farmer likelihood to participate in AES. We alo included farmer-pecific characteritic in the model uch a farmer age and preence of ucceor (Defranceco et al., 2008; Polman and Slangen, 2008). Factor related to external condition uch a ocial capital and farm location are alo taken into account. Baed on Polman and Slangen (2008) we introduced indicator related to ocial capital related to: (1) trut in ociety (criminal); (2) participation in profeional network; (3) participation in ocial network. Higher level of trut in ociety are expected to increae the likelihood of participation. The ocial network are more general network not related to agriculture but for example to involvement in port club. Agricultural network focu on improving agricultural practice. Accordingly to Polman and Slangen (2008) participation in more general network increae the probability of choice for agrienvironmental contract becaue thee farmer feel a large ocial reponibility. On contrary participation in agricultural network i expected to poitively influence participation in invetment upporting cheme becaue the farmer are more oriented toward improving on agricultural operation (Polman and Slangen, 2008). External condition relate alo to farm location. It include for example the degree of rurality (in term of population denity). Other apect relate to being located in one of the region of South Italy and in a mountainou area. The relevance of the location of farmer in different ocio-economic and geographical context ha been highlighted in other paper (ee Vanlembrouck et al., 2002; Vandermeulen; 2006). Vandermeulen et al. (2006) emphaied 12

13 the role of different intitutional environment to hape farmer deciion but alo alternative buine opportunitie and dynamicity of buine activitie. 5. RESULTS Etimation reult and meaure to ae the goodne of fit for both model 1 and model 2 are reported in table A2 in the Appendix. Hereby we dicu the impact and ignificance of each explanatory variable by comparing the reult obtained in the two empirical model. Several of the explanatory variable related to farm characteritic how a ignificant impact on the likelihood of farmer to participate in RDP contract. For example being a mall farm (mall) increae the likelihood to participate in RDP contract and epecially oin deciion on SCS and SAS. A tated in the previou ection the role of farm ize i very controverial. In thi cae the reult i in line with previou finding from Vanlembrouck et al. (2002) for mall farm participation in environmentally-oriented policy contract while it i rather new in term of participation in invetment-related policy contract. Regarding the farming ytem, and therefore farm pecialization, intenity of input ue and type of management, reult indicate that farm pecialized in horticulture (horticult), family-farm and farm with intene ue of labor (lu_uaa) are le likely to participate in RDP contract. On contrary dairy farm, and farm with advanced management ytem, uch a adoption of a buine and development plan (dev_plan) and ue of accountancy ervice (acc_erv), how a poitive attitude for both SCS and SAS type of contract. Land tenure how a ignificant effect only in model 2 with a negative impact on the likelihood of farmer to contract only SAS or SCS while poitive in cae of participation in both type of policy. Farmer characteritic alo matter. Oldet farmer are le likely to participate, while in cae manager are alo participating in manual activitie in the farm (the mot ued form of management in Italy) they are more willing to participate in both SAS and SCS contract. If we refer to explanatory variable related to ocial capital iue it i intereting to highlight that a negative ocial embeddedne (ditrut in ociety) lead to a lower partipation of farmer in RDP contract while the oppoite i found in cae of memebrhip in both profeional and non-trictly profeional related network. Finally farm location alo matter. More pecifically being located in one of the region of South Italy where decreae the likelihood to participate in both SCS and SAS, while location in a mountainou area (mount) increae farmer likelihood to partipate in RDP contract. 6. DISCUSSION AND CONCLUSIONS European public intervention in rural development became concrete in the 1970 with the o-called ocio-tructural directive, chiefly devoted to modernizing the farm ector. In the year to follow, the approach evolved, increaingly privileging the area element over the ectoral element. Thu everal principle were etablihed and conolidated in time, including not only improvement in farm efficiency but alo the enhancement of it multifunctional role 13

14 and the creation of a link between agriculture and region, chiefly aiming to forge utainable path of local development. The eentially role to be played by rural area in the balanced development of European ociety wa thu officially recognied and upported. Agenda 2000 moved cloer to an organic policy for rural development guided by principle of integration among economic activitie, of utainability, promotion of diverification and ubidiarity (which privilege the active role of local economic and ocial takeholder in programming and managing intervention). Today, with the enlargement to 27 Member State, 90% of EU territory conit of area claified a rural, compriing about 50% of Europe population. The heterogeneity of rural area in Europe ha thu increaed in recent year: thi ha led to greater ocial and economic difference within Europe rural context. Some area experience difficult geomorphological condition and uffer from ocio-demographic decline, while other, epecially thoe cloe to large conglomeration, are ubect to expanive urban preure and to inevitable competition for land ue. In light of uch conideration, the need to upport and contextualie intervention within the new cenario of the enlarged EU wa reinforced firt with the Fichler Reform in 2003, which permitted a tranfer of reource from Pillar I to Pillar II, and then with the renewed et of obective and action configured by Regulation 1698/2005 5, with which more pace wa given to the programming and management function of local partnerhip and with which the room for manoeuvre wa extended by new opportunitie tied to cenario development (epecially with regard to quality, animal welfare and energy aving). In the light of the reult achieved carrying out our analyi, and due to the unatifactory actual public intervention, a point which clearly urface lie in the difficulty of the current RDP framework to warrant a widepread ignificant impact on farm competitivene. It would appear the need for a more targeted framework of RDP policy by achieve the main obective declared by the EC throughout the year and the Reform. In fact, it i often the more marginal area which are teward of outtandingly important environmental aet, whoe continuity in time can only be enured by human preence and by agricultural activitie able to offer both economic upport and environmental ervice. In uch area the CAP mut continue to be a bulwark againt depopulation and environmental degradation. Thi may be done by privileging agriculture that repect the environment and i capable of enhancing the area pecific value, but alo with more inciive action to promote diverification of local economie. Thi will help all the takeholder in uch area to play an ever more active role in performing economic and ocial ervice. In um, trengthening regional competitivene and attractivene and reducing diparitie among the region i indeed a big challenge which deerve it own agenda. To achieve uch a viion, the European Commiion hould ue all the opportunitie offered by it regulatory, budget and coordination power and reponibilitie in view of enuring: 5 Regulation for rural development policy for the period , focued on three theme or thematic axe, and the Leader approach (or fourth thematic axi) which permit the etting-up and implementation of highly pecific proect by local partnerhip o a to repond to particular local problem. 14

15 A good balance between invetment in infratructure and in oft meaure to improve the competitivene and attractivene of all region. Strong coordination of all EU policie having a patial dimenion, even if they are primarily defined a having ectorial one, in order to create critical ma and leverage effect at meoeconomic level. A framework for a concept of Community Interet Programme focuing on thematic prioritie to give EU intervention a greater viibility. Thi hould be implemented by programme rather than by multiple proect. An increaed ue of all revolving financial intrument in order to improve the formation and availability of equity capital in the region. Qualitative evaluation criteria for the implementation of the coheion policy in order to enure higher added value of EU intervention and avoid mall-cale "political wihe" proect. Alignment of European funding with regional prioritie by providing a greater role to region in the management and implementation of programme in order to maximie the leveraging effect of EU financial contribution. Stronger integration of rural development in the coheion policy. REFERENCES Agugli L., Henke R., Salvioni C. (2009). Multifunctional Agriculture. Edizioni Scientifiche Italiane, Naple (Italy). Beedell, J. and Rehman, T. (2000). Uing ocial-pychology model to undertand farmer conervation behaviour. Journal of Rural Studie 16: Council Regulation (EC) No 1257/1999 (1999). Support for rural development from the European Agricultural Guidance and Guarantee Fund (EAGGF) and amending and repealing certain Regulation. Official Journal of the European Communitie of 17 May Defra, Department for Environment, Food and Rural Affair (2006). Reearch to Undertand and Model the Behaviour and Motivation of Farmer in Reponding to Policy change (England). Reearch proect EPES 0405/17 Final Report November London: Defra. Defranceco E, Gatto P, Runge F, Tretini S. (2008). Factor affecting farmer participation in agri-environmental meaure: A northern Italian perpective. Journal of Agricultural Economic 59: Damiano, D., Giannakopoulo, N. (2002). Farmer participation in agri-environmental cheme in Greece. Britih Food Journal 104: Dupraz, P., Vanlembrouck, I., Bonnieux, F. van Huylenbroeck, G. (2002). Farmer participation in European agri-environmental policie. Paper preented at X EAAE Congre on Exploring Diverity in the European Agri- Food Sytem. Zaragoza, Spain. Dwyer, J., Clark, M., Kirwan, J., Kambite, C., Lewi, N., Molnarova, A., Ken Thomon, K., Mantino, F., Tarangioli, S., Monteleone, A., Bolli, M., Fagiani, P., Storti, D., Schiller, S., Knickel, K., Farmer, M., Baldock, D., Bartley, J., Hart, K., Keenleyide, C., Trantinova, M., Prazan, J., Bradley, D., (2008). Review of Rural Development Intrument. DG Agri proect 2006-G4-10, pp Epinoa-Goded, M., Barreilo-Hurle, J., Ruto, E. (2010). What Do Farmer Want From Agri-Environmental Scheme Deign? A Choice Experiment Approach. Journal of Agricultural Economic 61 (2): European Commiion (2009). Rural Development ( ) in EU Farm. Directorate-General for Agriculture and Rural Development, Directorate L. Economic analyi, perpective and evaluation. L.3. Microeconomic analyi of EU agricultural holding. Bruel. Ferraro, P. J. (2008). Aymmetric information and contract deign for payment for environmental ervice. Ecological Economic 65(4):

16 Greene, W.H. and Henher, D.A. (2003). A latent cla model for dicrete choice analyi: contrat with mixed logit. Tranportation Reearch B 37: Greene, W.H., (2008). Econometric analyi. Upper Saddle River: Prentice-Hall. Hobb, J.E. (1997). Meauring the Importance of Tranaction Cot in Cattle Marketing. American Journal of Agricultural Economic 79(4): Jongeneel, R., Polamn, N. and Slangen L.H.G. (2008). Why are Dutch Farmer going Multifucntional?. Land Ue Policy 25: Maten, S.E. and Sauier, S. (2002). Econometric of contract: An aement of development in the empirical literature on contracting. In Broueau, E. and. Glachant, J.M. (ed.), The economic of contract: Theorie and application (pp ). Cambridge: Cambridge Univerity Pre. Ozanne, A., Hogan, T, Colman, D. (2001). Moral hazard, rik averion and compliance monitoring in agrienvironmental policy. European Review of Agricultural Economic 28 (3): Peerling, J., Polman, N. (2004). Wildlife and landcape ervice production in Dutch dairy farming; ointne and tranaction cot. European Review of Agricultural Economic 31: Peerling, J., Polman, N. (2008). Agri-environmental contracting of Dutch dairy farm: the role of manure policie and the occurrence of lock-in. European Review of Agricultural Economic 35 (2): Peerling, J., Polman, N. (2009). Farm choice between agri-environmental contract in the European Union. Journal of Environmental Planning and Management 52 (5): Polman, N., Slangen, L.H.G. (2008). Intitutional deign of agrienvironmental contract in the European Union: the role of trut and ocial capital. NJAS Wageningen Journal of Life Science 55 (4): Vandermeulen, V., Verpecht, A., Van Huylenbroeck, G., Meert, H. Boulanger, A. and Van Hecke, E. (2006). The importance of the intitutional environment on multifunctional farming ytem, in the peri-urban area of Bruel. Land Ue Policy 23 (4): Vanlembrouck, I., Van Huylenbroeck, G., Verbeke, W. (2002). Determinant of the willingne of Belgian farmer to participate in agri-environmental meaure. Journal of Agricultural Economic 51 (3): Verbeek, M., A guide to modern econometric. Chicheter: John Wiley & Son. White, B. (2002). Deigning voluntary Agri-environmental policy with hidden information and hidden action: a note. Journal of Agricultural Economic 53: Wynn, G., Crabtree, B., Pott, J. (2001). Modelling farmer entry into the environmentally enitive area cheme in Scotland. Journal of Agricultural Economic 52 (1): Woink, G.A.A., van Wenum, J. H. (2003). Biodiverity conervation by farmer: Analyi of actual and contingent participation. European Review of Agricultural Economic 30:

17 Appendix Table A1: Definition of RDP contract ued in the micro-econometric analyi RDP contract choice (1) Supporting Competitivene Scheme (SCS) (Table A1 continue) Invetment ubidie for upporting the competitivene of agricultural activitie: all ubidie for invetment in farm aet (agricultural land, human capital, building, property right, foret, land, machinery and equipment) received during the accounting year. They alo include any ubidie on interet rate. In addition, they may include national (or regional) invetment aid RDP meaure (a) Invetment in agricultural holding (b) oung farmer etting up (c) Training (g) Improving proceing and marketing of agricultural product (m) Marketing of quality agricultural product and etting up of quality cheme () Land improvement (y) Ue of farm adviory ervice Decription of the upport cheme The total amount of upport, expreed a a percentage of the volume of eligible invetment, i limited to a maximum of 40% and 50% in le favoured area. Where invetment are undertaken by young farmer thee percentage may reach a maximum of 45% and 55% in le-favoured area. The etting-up aid may comprie (i) a ingle premium up to the maximum eligible amount of 25,000 euro per farmer, (ii) an interet ubidy on loan taken on with a view to covering the cot ariing from etting up; the capitalized value of the interet ubidy may not exceed the value of the premium. The total amount of upport i a percentage of the total invetment in training activitie fixed per year and farm at Member State level. The total amount of upport, expreed a a percentage of the volume of eligible invetment, i limited to a maximum of (a) 50% in Obective 1 region and (b) 40% in the other region. The total amount of upport i et a a percentage of the total invetment in marketing and quality management activitie per year and farm at Member State level. The total amount of upport i a percentage of the total invetment in land improvement fixed per year and farm at Member State level. The total amount of upport i a percentage of the total invetment in adviory ervice fixed per year and farm at Member State level. 17

18 (f) Agri-environment Support i granted to farmer who give agri-environmental commitment for at leat five year. Where neceary, a longer period i determined for particular type of commitment in view of their environmental effect. Support in repect of an agrienvironmental commitment hall be granted annually and be calculated on the bai of (1) income foregone, (2) additional cot reulting from the commitment given, and (3) the need to provide an incentive. The cot of any non-remunerative capital work neceary for the fulfilment of the commitment may alo be taken into account in calculating the level of annual upport. Maximum amount per year eligible for community upport are 600 euro per hectare in cae of annual crop, 900 euro per hectare in cae of pecialized perennial crop and 450 euro per hectare in cae of other land ue. Thee amount hall be baed on that area of the holding to which agrienvironmental commitment apply. (2) Supporting Agri- Environmental Service (SAS) Rural development ( econd pillar ) direct payment due to agricultural activitie which provide environmental ervice: all direct payment received during the accounting year. (e1) Le-favoured area and area with environmental retriction (h) Afforetation of agricultural land Compenatory allowance granted to farmer per hectare of area ued for agriculture. Minimum compenatory allowance i fixed in 25 euro and maximum compenatory allowance i fixed in 200 euro per hectare of area ued for agriculture. Support hall be granted for the afforetation of agricultural land provided that uch planting i adapted to local condition and i compatible with the environment. Such upport may include in addition to planting cot (i) an annual premium per hectare afforeted to cover maintenance cot for a period of up to five year, (ii) an annual premium per hectare to cover lo of income reulting from afforetation for a maximum period of 20 year for farmer or aociation thereof who worked the land before it afforetation or for any other private law peron. Maximum amount per year of the annual premium to cover lo of income eligible for community upport are fixed in 725 per hectare (i) Other foretry meaure Payment are granted to the beneficiarie provided that the protective and ecological value of thee foret are enured in a utainable manner and the meaure to be carried out are laid down by contract and their cot pecified therein. Payment are fixed between a minimum payment of 40 euro per hectare and a maximum payment of 120 euro per hectare. (t) Protection of the environment The total amount of payment i a percentage of the cot determined per year and/or farm and/or hectare at Member State level. Source: own elaboration baed on Reg. CE (1257/99) and European Commiion (2009) 18

19 Table A2: Comparion of the etimation reult of the MVP model (Model 1) and the MNL model (Model 2) Explanatory variable BVP (Model 1) MNL (Model 2) SCS SAS SCS SAS SCS and SAS Coef. Coef. Coef. Coef. Coef. Farm charactertic Farmer characteritic Social capital Farm location con ( ) *** ( ) *** ( ) *** ( ) ** ( ) *** mall ( ) *** ( ) *** ( ) ( ) * ( ) *** fixaet ( ) ** ( ) ( ) ( ) ( ) *** arable ( ) ( ) ( ) ( ) * ( ) horticult ( ) *** ( ) *** ( ) *** ( ) *** ( ) ** perm_crop ( ) ( ) ( ) *** ( ) ( ) livetock ( ) *** ( ) *** ( ) * ( ) * ( ) *** lu_uaa ( ) ** ( ) ** ( ) * ( ) ** ( ) ** fam_labor ( ) *** ( ) *** ( ) *** ( ) ** ( ) *** offfarm ( ) *** ( ) *** ( ) *** ( ) *** ( ) uaa_rent ( ) ( ) ( ) *** ( ) ( ) *** dev_plan ( ) *** ( ) *** ( ) *** ( ) *** ( ) *** acc_erv ( ) *** ( ) *** ( ) *** ( ) *** ( ) *** manager ( ) ** ( ) * ( ) ( ) ( ) ** age ( ) ( ) *** ( ) * ( ) *** ( ) ucce ( ) ( ) ( ) ( ) ( ) criminalit ( ) *** ( ) *** ( ) ( ) *** ( ) *** coop ( ) *** ( ) *** ( ) ( ) ( ) *** aoc ( ) *** ( ) *** ( ) * ( ) *** ( ) outh ( ) *** ( ) *** ( ) *** ( ) ( ) *** pop_den ( ) ( ) *** ( ) ( ) *** ( ) mount ( ) *** ( ) *** ( ) *** ( ) *** ( ) *** Ρ SCS,SAS ( ) *** Likelihood ratio tet of rho21 = 0: chi2(1) = > chi2 = Log likelihood = ; Peudo-R 2 = ; LR chi2(63) = P > chi2 =

20 Statitical ignificance: * = P < 0.10; ** = P < 0.05; *** = P <0.01; Standard error in parenthei; N. ob. = 15,380 20

21 Ancona nd EAAE Seminar Page 1 of 21