Methodological aspects of a mathematical programming model to evaluate soil tillage technologies in a risky environment

In this work we develop a methodology for the economic evaluation of soil tillage technologies, in a risky environment, and to capture the influence of farmer behaviour on his technology choice. The model has short-term activities, that change with the type of year, and long-term activities, in which sets of traction investment activities are included. Although these activities do not change with the type of year, they lead to different availability of resources for each type of year, since the same tractor has different available fieldwork days under different weather conditions. We prove that the model is sensitive to the greater income variability resulting from the use of alternative technologies and to the balance between income and risk, accounting for the probability of occurrence of each state of nature and giving an investment solution that considers the best production plan for each type of year. (c) 2005 Elsevier B.V. All rights reserved

Investment behavior of Canadian Egg Producers: Analyzing the Impacts of Risk Aversion and Variability of Prices and Costs of Production

Animal welfare is a major concern for consumers. This concern has not gone unnoticed by sector stakeholders, especially egg producers. One of the fundamental changes likely to affect egg producers regards modes of production, specifically changes in housing systems, ranging from conventional cages to free range. From farmers’ perspective, changing their mode of production generates a technological and economic/marketing risk. This study documents the level of risk in the Canadian egg sector (conventional and specialty eggs) using data from 2009 to 2011. Our results indicate multiple uncertainty sources (technological, cost of production, price of eggs) that vary according to the types of eggs. We use a quadratic programming approach applied to expected mean-variance models to analyze the impact of risk on decision to invest when the resources must be allocated to different types of production that have different risk levels. Overall our results show how, given risk aversion parameters, producers minimize their risk levels by devoting their resources to the least risky type of eggs. An important result of our study is that supply management, by reducing the perceived risk level, has favored the development of specialty eggs, for the benefit of consumers

Sustainable agricultural development: Knowledge‐based decision support

The article introduces the knowledge‐based agricultural decision support system. The system includes database and knowledge base as well as modules used for formation of models, optimization, simulation, decision analysis and inference. The linear programming model contains several hundreds of variables and restrictions. The farm model, using entered data, is formed according to “if‐then” type rules that are stored in the knowledge base. Having solved the task of optimization, the particular values of variables indicate what kind of crops should be grown and in what area, as well as what animals and how many of them should be kept and what resources and how much of them have to be used for achieving the biggest benefit under the environmental and other conditions. The simulation was employed to test the sensitivity of the plan to weather and market variations. Having applied a set of production rules to the given facts and modelling results within the module of decision analysis and inference, conclusions and suggestions are made. Decision support system performs the analysis of production efficiency, resource reserves and shortage, and with the help of the Internet in real time provides a farmer with conclusions and suggestions necessary to increase the efficiency of production conforming to environmental constraints. The integration of optimization calculations and knowledge management into the agricultural decisions‐support system expands its possibilities and improves the quality of solutions. Santrauka Pristatoma žiniomis grįsta žemės ūkio sprendimų paramos sistema. Ją sudaro duomenų ir žinių bazės, modelių formavimo, optimizavimo, imitavimo, sprendimų analizės ir išvadų formavimo moduliai. Žemės ūkio įmonės modelis sudaromas pagal įvestus duomenis, remiantis žinių bazėje saugomomis „jeigu–taip“ tipo taisyklėmis. Išsprendus optimizavimo uždavinį gautos kintamųjų vertės rodo, kokie javai ir kokiame plote turi būti auginami, taip pat kokie gyvuliai ir kiek jų turi būti laikoma, kokie ištekliai ir kiek jų turi būti panaudota, norint pasiekti didžiausią naudą ūkyje nurodytomis aplinkosaugos ir kitomis sąlygomis. Imitavimo būdu patikrinamas gamybos plano jautrumas orų ir rinkos pokyčiams. Išvadų formulavimo modulyje, pritaikius duotiems faktams ir modeliavimo rezultatams produkcinių taisyklių rinkinį, gaunamos išvados bei pasiūlymai. Sprendimų paramos sistema atlieka gamybos efektyvumo, išteklių rezervų bei išteklių trūkumo analizę. Ūkininkas internetu gauna išvadas bei pasiūlymus, kaip didinti gamybos efektyvumą. Optimizavimo skaičiavimų ir žinių bazės integravimas į žemės ūkio sprendimų paramos sistemą išplečia jos galimybes ir pagerina sprendimų kokybę. First published online: 21 Oct 2010 Reikšminiai žodžiai: darni žemės ūkio plėtra, sprendimų paramos sistema, tiesinis programavimas, optimizavimas, imitavimas, žinių baz

Farm Investment Behaviour under the CAP Reform Process

The results of the study, based on survey analysis as well as on modelling of farm behaviour, can be summarised in four main outcomes: Similar to the results of the first Investment study carried out in 2006 and published in 2008 (Gallerani. et. al.), in the context of the present study (carried out in 2009) for about half of the farms decoupling did not result in any change. Among those farms showing some reaction, one of the more prominent effects is the increase in on-farm investment. The price trends in 2007/2008 and the ongoing economic and financial crisis have partially reshaped access to credit, perceptions of objectives, constraints and expectations. In particular, farms have witnessed a major reduction in access to credit, particularly the share of farms using short term credit, which dropped from more than 40% in 2006 to about 7% in 2009. The change in economic conditions has increased this role of the CAP, and the importance of CAP payments in covering current expenditures has become more evident. Prices confirm their role as the key variable for investment choices. The results of the modelling exercise confirm that farm and farm-household income and investment choices depend more on the price level than on the level of payment received. Altogether, the combined effect of the recent policy reform (decoupling and first pillar payment reductions), as well as price and cost developments tend to reinforce the role of policy for the economic and social sustainability of farming. Notably, policy areas such as income support, investment and credit management, market access, as well as transitory and cross-policy mechanisms, appear to be of particular importance. Uncertainty (and related risk-management instruments) seems to play an increasing role in the investment decision process.JRC.J.5-Agriculture and Life Sciences in the Econom