Agri-environmental schemes (AES) play a key role in promoting the production of environmental public goods by European Union agriculture. Although extensive literature has analyzed AES, some important issues remain understudied. This paper performs an ex-ante assessment of AES in permanent cropping, analyzing several issues that have received little attention from researchers, such as ecological focus areas (EFA) and collective participation. For this purpose, a choice experiment was used to assess farmers' preferences toward AES in a case study of olive groves in southern Spain. Results show high heterogeneity among farmers, with different classes being identified, from potential participants to non-participants. As regards EFA, almost half of the farmers would be willing to accept it for low monetary incentives (€8-9/ha per additional 1% of the farmland devoted to EFA) while the rest would do it for moderate-to-high monetary incentives (€41-151/ha per additional 1% of EFA). However, for a high share of EFA (e.g., 5-7%) higher incentives would presumably be required due to the intrinsic spatial restrictions of olive groves. With regard to collective participation, we find that it is unlikely that farmers would participate collectively with the incentive of the up-to-30% EU-wide bonus. These results are relevant for policy-making now when new AES are being designed for the next programming period 2014-2020.

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ABSTRACT. Specialised literature on the uptake of agri-environmental schemes (AES) has paid little attention to how this can be influenced by the different types of agricultural systems. This paper analyses the heterogeneity of farmers' preferences towards these schemes, distinguishing between different sub-systems within the same agricultural system. We use the choice experiment method to analyse the case study of three olive grove sub-systems in southern Spain, with the sub-systems ranging from extensive to intensive. The results reveal inter and intra sub-system heterogeneity of farmers' preferences towards AES both in general and specifically related to scheme attributes. A variety of factors appear to lie behind inter sub-system heterogeneity, especially those associated with sub-system specificities (principally, the type of joint production). Likewise, numerous factors play a role in intra sub-system heterogeneity, most of them related to farm/farmer socioeconomic and physical characteristics. These findings will help in the design of more efficient AES.

The identification and treatment of protest responses in stated preference surveys has long been subject to debate. We analyse protest responses while investigating ecosystem services providers’ preferences for incentive‐based schemes. We use a choice experiment for olive farmers’ preferences for agri‐environmental scheme participation in southern Spain. Our two main objectives are: first, to identify and discuss a range of possible motives for protest responses that emerge in a WTA context; second, we analyse the impact on WTA estimates of censoring serial non‐participation linked to protest or high compensation requirements (very high takers). Using a random parameter logit model in WTA space, we find that the inclusion or exclusion of serial non‐participants in the analysis can have a significant impact on marginal and total WTA estimates. Based on the findings, the paper makes recommendations on how to reduce the incidence of protest responses through survey design, regarding the identification of protesters as opposed to very high takers, and regarding the treatment of both groups of respondents for WTA estimation.

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In irrigated agricultural systems, the main source of uncertainty to irrigators relates to water supply, as it significantly affects farm income. This paper investigates farmers' utility changes associated with shifts in the probability density function of water supply leading to a higher water supply reliability (higher mean and lower variance in annual water allotments). A choice experiment relying on a mean-variance approach is applied to the case study of an irrigation district of the Guadalquivir River Basin (southern Spain). To our knowledge, this is the first study using parameters of these probability density functions of water supply as choice experiment attributes to value water supply reliability. Results show that there are different types of farmers according to their willingness to pay (WTP) for improvements in water supply reliability, with some willing to pay nothing (44.9%), others (28.6%) with relatively low WTP, and the remainder of farmers (26.5%) having high WTP. A range of factors influencing farmers' preferences toward water supply reliability are revealed, with those related to risk exposure to water availability being of special importance. The results will help to design more efficient policy instruments to improve water supply reliability in semi-arid regions.

Information asymmetry is one of the main obstacles to the effective design and implementation of agri‐environmental schemes (AES). The literature has generally addressed this issue through the use of principal‐agent models (PAM). We develop a PAM to support optimal design of a new AES for improving farmland biodiversity. We use the results of choice experiments to assess both the costs incurred by the agent for the provision of biodiversity and the resulting social benefits. We also make a number of novel contributions such as the inclusion of a non‐linear non‐compliance detection curve, a sensitivity analysis to identify which parameter estimates have a critical impact on PAM results, and analysis of the efficiency of different sanction scenarios. The results suggest that: (i) the second‐best solutions differ significantly from the optimal solutions attainable with perfect information, with farmers being strongly over‐compensated for the extra costs associated with improved biodiversity; (ii) monitoring levels should be higher; (iii) the sanction system should be tougher. Sensitivity analysis shows the need for accurate estimates of the marginal cost of public funds and the costs and benefits associated with the public goods, which represent the key parameters determining PAM results.