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European farmers face an increasing income uncertainty. The debate is growing on the role of the insurance schemes and on the support provided by the CAP in this field. Therefore, there is a need for the empirical analysis and the tools aimed at providing empirical evidences on this subject. This paper develops an innovative Positive Mathematical Programming model that takes into explicit consideration the risk aversion behaviour. This is used to investigate the implications of participating in the crop revenue insurance scheme. in particular, a quadratic mix integer program has been developed on a small group of crop farms in italy and it has been used to simulate the impact of changes in the level of the insurance premium. The objective of this paper is to assess the soundness of the proposed approach and to identify its limitations. The obtained results suggest that this could be a useful tool to investigate the impact of participating in insurance schemes on production patterns, farm profitability and the role of public support. [ABSTRACT FROM AUTHOR]

Recent literature reviews of empirical models optimizing long-term investments in agriculture see gaps with regard to (i) separating investment and financing decisions, (ii) considering explicitly risk and temporal flexibility, and (iii) accounting for farm-level resource endowments and other constraints. Inspired by real options approaches, this paper therefore stepwise develops a model extending a simple net present value calculation to a farm-scale simulation model based on mathematical programming, which considers time flexibility, different financing options and downside risk aversion. We empirically assess the different model variants by analysing investments into hazelnut orchards in Italy outside of traditional producing regions. The variants suggest quite different optimal results with respect to scale and timing of the investment, its financing and the expected NPV. The stepwise approach reveals which aspects drive these differences and underlines that considering temporal flexibility, different financing options and riskiness can considerably improve traditional NPV analysis. [ABSTRACT FROM AUTHOR]

• Optimal design of multi-vector energy hubs in energy communities. • MILP model using a multi-objective function. • Application to a real case represented by a university campus. One of the main ways to reach the important targets of the European Commission in the energy field set by 2030 is to implement sustainable energy systems to cover electrical and thermal energy demands, as well as transportation needs, in urban areas. In the aforesaid scenario, multi-vector energy hubs consist of installing small and medium size power plants, mainly fed by renewable sources, and charging infrastructures for electric vehicles in sustainable urban districts. The optimal design of such systems can be faced from different points of view and using different methods, one of the most adopted being the development of mathematical programming algorithms typically aimed to minimize global costs and emissions. The contribution of this paper is to propose an innovative methodology to optimally design a multi-vector energy hub able to supply electricity and thermal energy, for space heating and cooling, to a set of buildings within a sustainable district acting as a local energy community. The developed mixed integer linear programming model is characterized by very detailed models of the technologies and by a multi-objective function which is proposed to evaluate the impact of the optimal solution on global costs and emissions. The proposed mathematical model is very comprehensive as it involves a wide range of energy technologies with detailed modelling by considering the impact of external ambient conditions and energy vector temperature values on the plant conversion efficiency, thus showing high replicability potential in real contexts. In the case study, the model is applied to a university campus in the North of Italy. [ABSTRACT FROM AUTHOR]

The article presents news relevant to economics. The University of Venice will host a conference on Advances in the Analysis of Economic Dynamic Systems in January 1986. The 1985 Annual Symposium of the College of Europe will focus on "The Community's Development Policy: The Strategic Ahead." The Panel Study of Income Dynamics' Board of Overseers will commission a paper evaluating the dynamic sample design of the Panel Study of Income Dynamics. The XII International Symposium on Mathematical Programming will be held at the Massachusetts Institute of Technology on August 5-9, 1985.

The Piedmont Region in NW Italy has recently deployed an ambitious and pioneering agricultural water pricing reform aimed at integrating and effectively enforcing EU's Water Framework Directive principles of cost recovery, polluter-pays and affordability. This paper develops a multi-model ensemble framework encompassing 5 mathematical programming models (2 Positive Mathematical Programming models, 2 Positive Multi-Attribute Utility Programming models and 1 Weighted Goal Programming model) that represent the observed behavior of socioeconomic agents to: 1) simulate the impacts of the Piedmontese water pricing reform on land use allocation and management, water conservation, profit and water tariff revenue; 2) sample modeling uncertainty through the ensemble spread; and 3) explore potential tipping points through use of scenario-discovery techniques. Our research suggests that the key challenge to the reform lies in the management of rice fields, an extensive (17% of the agricultural area), water-demanding and relatively low-added-value crop that nonetheless delivers significant ecosystem services (e.g. water retention) of historical and cultural relevance to the region. The ensemble experiment suggests that rice agriculture rapidly dwindles in the price range 0.012–0.074 EUR/m3 depending on the model. Before reaching this tipping point, agricultural water pricing can reduce withdrawals up to 1.7%–9.5%, while reducing profit between 4.9% and 5.6% and achieving a 57- to 65-fold increase in water tariff revenue. • We combine a multi-model ensemble experiment with scenario discovery techniques. • Our approach samples modeling and scenario uncertainty to identify tipping points. • Our approach is illustrated using the agricultural water pricing in Piedmont (IT). • Results show historical rice fields dwindle in the price range 0.014–0.074 EUR/m3. • Conserving rice fields considerably limits pricing water conservation potential. [ABSTRACT FROM AUTHOR]

The article offers information on the developments concerning economic studies. The University of Venice will host a conference entitled "Advances in the Analysis of Economic Dynamic Systems," on January 1986. The board of overseers to the Panel Study of Income Dynamics will commission a paper evaluating the dynamic sample design of the Panel Study of Income Dynamics, one of the many large-scale sample surveys that purposely selected its sample cases with known but differing selection probabilities. The 12th International Symposium on Mathematical Programming is scheduled on August 1985 at the Massachusetts Institute of Technology.