An attempt to modelling revenue insurance schemes at the farm level by means of Positive Mathematical Programming

Farmers face increasing income uncertainty and the debate is growing on the role of insurance schemes and of public support in this field. This paper applies a PMP modelling approach that takes into explicit consideration risk aversion behaviour to test its applicability to evaluating the potential impact of insurance schemes. This is done by introducing a revenue insurance scheme into a model developed on a small group of crop farms in Italy. The paper represents a preliminary assessment of the soundness of the proposed approach. It identifies some limitations that should be overcome to improve the proposed approach. Despite these limitations, it seems a useful tool to investigate the impact of insurance schemes and policy relevant parameters such as premium and coverage rates. Indeed, it permits the assessment of how this affects production choices, farm profitability and the impact of public support to reduce the net premium paid by farmers.Insurance schemes, PMP, Farmers’ behaviour, Risk aversion, Agricultural and Food Policy, Q12, C61, Q18,

Modeling farmer participation to a revenue insurance scheme by means of Positive Mathematical Programming

European farmers face increasing income uncertainty and the debate is growing on the role of insurance schemes and of public support in this field. This debate is further stimulated by the perspective of introducing instruments to cope with risk also in the Common Agricultural Policy. Therefore, there is a need for empirical analysis and tools aimed at providing empirical evidences on this subject. This paper applies a PMP modelling approach that takes into explicit consideration risk aversion behaviour to test the possibility to use it to assess the implications of participating in a insurance scheme. This is done by introducing a revenue insurance scheme into a model developed on a small group of crop farms in Italy. In particular, a quadratic mix integer programming approach has been developed in order to model the choice of participating or not in the proposed insurance scheme. The model has been than used to conduct simulations considering changes in the level of the insurance premium. The paper tries 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 and farm profitability and the role of public support in this field.insurance schemes, PMP, farmers’ participation, risk aversion, non-linear mix-integer programming, Farm Management, Risk and Uncertainty, Q12, C61, Q18,

Evaluating Changes in Cropping Patterns due to the 2003 CAP Reform. An Ex-post Analysis of Different PMP Approaches Considering New Activities

Replaced with revised version of paper 02/22/08.ex-post policy evaluation, positive mathematical programming, CAP reform, Agricultural and Food Policy, Crop Production/Industries, Research Methods/ Statistical Methods,

The impact of reforming the Common Agricultural Policy on the sustainability of the irrigated area of Central Italy. An empirical assessment by means of a Positive Mathematical Programming model

The Common Agricultural Policy (CAP) is a major driver of the environmental and social sustainability of the agriculture in the European Union (EU). Under the 2003 CAP reform, most direct payments to agricultural producers were decoupled from production. This work assesses the possible impact of the CAP reform on the sustainability of an irrigated area of Central Italy with particular attention being paid to decoupling. The analysis has been conducted using the Positive Mathematical Programming (PMP) method that directly estimates the cost function parameters by imposing the first-order conditions of the farm model under consideration. The analysis assesses the impact of the CAP reform on farm cropping patterns, water and chemical use, labour use and economic results. By referring to this set of indicators it is possible to investigate the likely effect of the CAP reform on the environmental, social and economic sustainability of the considered farming systems. The results of the empirical analysis mainly show a reduction in water and chemical input use, an increase in the economic results of farms, but also a reduction of the labour.Common Agricultural Policy, Sustainability, Positive Mathematical Programming, Farmers’ behaviour, Irrigated agriculture, Decoupling, Agricultural and Food Policy, Consumer/Household Economics, Crop Production/Industries, Demand and Price Analysis, Farm Management, Land Economics/Use,

Common Agricultural Policy and climate variability changes: an impact assessment of the first-pillar reform on an agricultural area of Grana Padano in different climate scenarios

The reform of the Common Agricultural Policy it started in 2015 with several innovative aspects. Regarding the first pillar, such aspects are especially the convergence of the basic payments, the green payments and the coupled payments. In this regard seems interesting carry out analysis about to evaluate the policy impact considering the risks and opportunities due to climate change.In this study the impact of the convergence of basic payments, the introduction of the green payments and the coupled payments has been evaluated on dairy cattle farms in the Grana Padano area. The impact has been evaluated in different climate scenarios by economic, social and environmental indicators. The methodology used is the mathematical programming and especially a model of Discrete Stochastic Programming has been used to represents farms of the FADN database.The main results show that a significant part of the farms is affected by the diversification constraint that reduces the land devoted to corn silage. Farmers could cultivate corn silage after a principal crop (e.g. ryegrass) in order to avoid the diversification constraint, however, determining a negative impact on the use of environmental resources. To consider also that in the future there is an increase of corn silage yields with long cycle.Another result to underline is that which concerns the possibility of soybean cultivation in the ecological focus areas. In fact, considering the coupled payment provided for this crop, the ecological focus areas seem to be an important source of income for the farms.Finally, the analysis shows that the convergence of the basic payment will result in a reallocation of direct payments between farms with a significant impact on farm incomes

Possible Impacts of Climate Change on Mediterranean Irrigated Farming Systems

In the agricultural sector, climate change (CC) affects multiple weather variables at different stages of crop cycles. CC may influence the mean level or affect the distribution of events (e.g., rainfall, temperature). This work evaluates the economic impact of CC-related changes in multiple climatic components, and the resulting uncertainty. For this purpose, a three-stage discrete stochastic programming model is used to represents farm sector of an irrigated area of Italy and to examine the influence of CC on rainfall and on maximum temperature. These variables affect the availability of water for agriculture and the water requirements of irrigated crops. The states of nature, and their change, are defined more broadly than in previous analyses; this allows examining the changes of more climatic variables and crops cultivation. The effect of CC is obtained by comparing the results of scenarios that represent the climatic conditions in the current situation and in the future. The results show that the agricultural sector would seek to lower costs by modifying patterns of land use, farming practices and increasing the use groundwater. The overall economic impact of these changes is small and due primarily to the reduced availability of water in the future. The temperature increase is, in fact, largely offset by the effects of the increase in CO2 levels, which boosts the yield of main crops of the irrigated zone. Therefore, availability and water management becomes a crucial factor to offset the increase of evapotranspiration and of water stress resulting from the increase of temperature. However, the costs of CC are very high for some types of farming, which suffer a large reduction in income.discrete stochastic programming model, climate change, water availability, irrigation requirements, Farm Management, Resource /Energy Economics and Policy,

An evaluation of the economic impact of Climate Change through a three-stages Discrete Stochastic Programming model

The climate change in the agricultural sector acting on multiple weather variables at different times of the various crop cycles. In several cases by changing the mean level of variables (rainfall, temperature, etc..), in other cases by changing the distribution of events. This work provides an evaluation of the economic impact due to changes in multiple events, and to the associated uncertainty. For this reason, a classical two-stage stochastic programming model was extend into a three-stages model. The model is specified for an area of Sardinia, and examines the impact of climate change on rainfall and hence on the availability of water for agriculture, and on maximum temperatures and, therefore, on the requirements of some irrigated crops relevant to the agricultural economy of the area. The effect of climate change is obtained by comparing the results of scenarios that represent the climatic conditions in the current situation and in the future, obtained by projecting to 2015 the climate trends of the last fifty years. The results show that the agricultural sector of the area adapt itself with a low cost by use of land and cultural practices. This cost, however, is very high for some farms that suffer a significant reduction of the income. There is also an increase of the use of natural resources, in particularly groundwater. The economic impact of these changes is due primarily to the decreased of water availability in the future. The availability of water becomes the crucial factor to adapting to climate change, because the effects of temperature can be compensate by increased the use of water resources.Discrete Stochastic Programming Model, climate change, water availability, irrigation requirements, Crop Production/Industries, Environmental Economics and Policy, Farm Management, Land Economics/Use, Research Methods/ Statistical Methods,

Perceptions of Present and Future Climate Change Impacts on Water Availability for Agricultural Systems in the Western Mediterranean Region

Many Mediterranean countries have experienced water shortages during the last 20 years and future climate change projections foresee further pressure on water resources. This will have significant implications for irrigation water management in agricultural systems in the future. Through qualitative and quantitative empirical research methods carried out on a case study on four Mediterranean farming systems located in Oristano, Italy, we sought to understand the relationship between farmers' perceptions of climate change (i.e., increased temperature and decreased precipitation) and of present and future water availability for agriculture as forecasted by climatic and crop models. We also explored asymmetries between farmers' perceptions and present and future climate change and water scenarios as well as factors influencing perceptions. Our hypotheses were that farmers' perceptions are the main drivers of actual water management practices and that sustainable practices can emerge from learning spaces designed from the understanding of the gaps between perceptions and scientific evidences. Results showed that most farmers perceived that climate change is occurring or will occur in their area. They also perceived that there has been an increased temperature trend, but also increased precipitation. Therefore, they are convinced that they have and will have enough irrigation water for agriculture in the near future, while climate change projections foresee an increasing pressure on water resources in the Mediterranean region. Such results suggest the need for (i) irrigation management policies that take into account farmers' perceptions in order to promote virtuous behaviors and improve irrigation water use efficiency; (ii) new, well-designed learning spaces to improve the understanding on climate change expectations in the near future in order to support effective adaptive responses at the farm and catchment scales

Evoluzione del clima e incertezza delle scelte sui sistemi colturali in un comprensorio irriguo del Nord Sardegna

L’analisi quantitativa dell’impatto dei cambiamenti climatici (CC) sui sistemi colturali implica l’impiego di modelli di simulazione adeguatamente calibrati. Il modello EPIC (Environmental Policy Integrated Climate) (Williams, 1995) è stato ampiamente validato per simulare le risposte delle colture e dei relativi fabbisogni idrici ai CC (Adejuwon, 2005, Tourè et al., 1994). In questo lavoro, i risultati delle simulazioni effettuate con EPIC sono stati utilizzati come input per il modello di analisi economica per valutare l’impatto del CC sulle scelte dei sistemi coltutali in un comprensorio irriguo della Sardegna del nord

Combining modeling and stakeholder involvement to build community adaptive responses to climate change in a Mediterranean agricultural district

The case study area (54,000 ha) is located at Oristano, Italy. The main cropping systems are based on forages (silage maize, Italian ryegrass and alfalfa under irrigation, winter cereals and grasslands under rainfed conditions), rainfed cereals (durum wheat, barley), vegetables (e.g. artichokes), rice, citrus, olives and vineyards. Some 36,000 ha are served by irrigation. The area includes the dairy cows cooperative system of Arborea (30,000 cows, 5500 ha, nitrate vulnerable zone). The rainfed dairy sheep includes 372,000 sheep and a number of small milk processing plants. The research aims to support adaptive responses to climate change through the combination of modeling approaches and stakeholder engagement. Present (2000-2010) and future (2020-2030) climatic scenarios were developed by combining global climate models with Regional Atmospheric Modelling Systems to produce calibrated time series of daily temperature and precipitation for the case study. The EPIC model was calibrated to simulate the impact of climate scenarios on the main cropping systems. The impact of THIndex on milk yield, milk quality and mortality was also simulated for dairy cows. A territorial farm-type Discrete Stochastic Programming model was implemented to simulate choices for thirteen farming typologies as influenced by crop yields and water consumptions. Participatory activities, including field experiments, interviews, focus groups and interactive workshops, involved farmers and other stakeholders in the most critical phases of the research. The assessment of uncertainties and opportunities were proposed as a basis for discussion with policy makers to identify priorities for agro-climatic measures in 2014-2020