Agri‐environmental measures play an important role in Italian rural areas, as shown by the financial commitment to the Rural Development programmes. However, in contrast with other European Union (EU) countries, policy‐makers still have limited experience on how farmers approach environmental incentive schemes. This paper casts new light on this issue from a northern Italian perspective. The rationale of the farmers’ decision‐making process is explored using two multinomial models. The first explains the probability of non‐participation or participation in one of three specific agri‐environmental measures. The model outcomes show that labour‐intensive farming types and high dependency of household income on farming activity constrain farmers’ participation, whereas previous experience, easy‐to‐implement environmentally friendly farm practices and adequate compensation of extra costs encourage participation. The second model explores the effect of farmers’ attitudes and beliefs on their predispositions towards participation in any of the schemes. The results highlight that, besides income factors, the farm's future in the business, and the relationship with neighbouring farmers and their opinions on environmentally friendly practices all have significant effects on adoption of agri‐environmental measures. The paper concludes by suggesting that farmers’ attitudes and beliefs, as well as the local behavioural influences, have to be taken into account when designing and communicating agri‐environmental measures.

Purpose – The research aims to explore whether quality signals, such as grape variety names explicitly used by ‘quality wines produced in specified regions’, affect wine retail prices in different ways in large-scale retail and in specialised shops. Methodology–Tocai wine, which is produced in northeastern Italian regions and involved in a dispute with the Hungarian geographical indication Tokaj, has been taken as a case study. A hedonic price model has been estimated based on retail prices observed in local markets. Findings – The research shows that consumers buying at large-scale retailers are willing to pay a higher price premium for quality signals than those buying in specialised shops, ceteris paribus. For the latter, willingness to pay for quality signals is reduced by the information provided by the specialised shop retailer, which decreases the customer’s uncertainty about wine quality; quality signals appearing on wine labels generally have a more relevant positive effect on wine price than brand reputation, confirming the findings available in the current literature. Originality/value – This paper originally contributes to the literature by proving in a real market situation that consumers are willing to pay a higher price premium for quality signals when information is supplied only by wine labels, as in large-scale retail, than when it is provided by a knowledgeable seller’s assistance, as in specialised shops. The paper confirms that the information transmitted to the consumer during purchase affects price in a way similar to that reported by the literature for simulated markets in the case of expert consumers

This paper investigates the effects on prices of nutrition and health claims for foodstuffs, in addition to other attributes, using fruit beverages as a case study. The model estimation is based on revealed purchasing behaviour for fruit beverages in the north-east of Italy. Applying an hedonic price model, the price of a product is explained as a function of product attributes. The model estimate identifies the implicit retail-market-level price of specific attributes such as nutrition and health claims, ceteris paribus. Nutrition and health claims significantly affect retail prices.\ud Our findings suggest that retail price response to nutrition and health claims differs\ud in relation to other product attributes, showing a strong reduction of price variation\ud among flavours when such benefits are claimed on the label

Common Agricultural Policy was and still is one of the key pillars of European integration. Published in two volumes materials refer directly to the current and future of the CAP in EU and non EU member states, the strategic objectives and principles of agricultural policy for the agri-food sector and rural areas, address the issues of equilibrium between agriculture, forestry and land use, relate to the dilemmas for the EU budget and the CAP after 2020, CAP instruments and their adjustment, transformations of the rural economy and programming of the rural and agricultural policy, as well as productivity and production efficiency and tensions between sectoral action and between different models of territorial activities.

Purpose This paper bridges the gap between theory and practice in the application of the Income Stabilisation Tool (IST). With an application to the dairy sector, the purpose of this paper is to propose methodology for the quantification of reference income when farm structural change occurs and estimate the role of farm attributes on the probability of income loss, offering an ex ante evaluation of farm resilience to risk. Design/methodology/approach Based on a balanced Farm Accountancy Network farm-level panel ranging from 2008 to 2014, three hypotheses of reference income calculation are tested to assess whether farms structural changes over the years significantly affect the level of IST indemnification. The role of farm characteristics on the probability of an income reduction is then evaluated by estimating a multinomial logit model. Findings Results show that farms’ structural changes significantly affect IST indemnities and need to be considered in calculating the reference income. The estimated model suggests that farm characteristics significantly affect the probability of a severe income drop and hence risk resilience. Extensive livestock systems seem to reduce the probability of an income drop, while farms in upland areas managed by young farmers seem to experience increased risk exposure. Originality/value The research provides one of the first attempts to define risk profile of dairy farms by modelling the probability of an income reduction on observable attributes. Indeed, among different sectors, dairy farms emerge as the main candidates for the application of the IST.