Modeling Greenhouse Gas Emissions on Diversified Farms: The Case of Dairy Sheep Farming in Greece

Agricultural activity has been identified as a considerable source of Greenhouse Gas (GHG) emissions. Emissions from ruminant livestock farms are produced particularly due to CH4 emissions from enteric fermentation. Dairy sheep farming is the most important livestock production activity in Greece, characterized by a high degree of farm diversification. This paper addresses the issue of the evaluation of GHG emissions of Greek dairy sheep farms, through the use of a whole farm mathematical programming model that uses farm level data and optimizes total gross margin. Mathematical programming models are an appropriate tool, when addressing complex issues, such as GHG emissions. The analysis is undertaken on different farm types, instead of a representative farm, to account for the heterogeneity of the sheep farming activity. Thus, marginal abatement cost and appropriate mitigation strategies for diversified farms are determined. The results indicate that intensive farms cause few emissions per produced milk (2.7kg of CO2 eq). Also, the marginal abatement cost ranges among 51-64€/t for all types of sheep farms (at 20% abatement level). The model used in this analysis and the results it yields are useful to researchers and policy makers, who aim to design efficient mitigation measures.Dairy sheep farming, linear programming, GHG emissions, abatement cost, Environmental Economics and Policy,

Greek cotton farmers' supply response to partial decoupling of subsidies

A mathematical programming model based on a countrywide sample of farms is used to assess the impacts of the new C.A.P on the supply of the cotton sector in Greece. Results show a decrease in cotton cultivated area along with the introduction of a new production system called "semi-abandonment cotton". Farm income is practically unchanged, largely due to the decoupled payments. When these payments are not considered, farm income turns negative in some cases, thus leading towards abandonment of activities.Cotton, C.A.P, decoupling, mathematical programming, Agricultural and Food Policy, Agricultural Finance,

Multiple goals in farmers’ decision making: The case of sheep farming in Western Greece

Management strategies and performance differ among farmers, as a result of different, multiple and often conflicting goals. Many approaches to building farm level models that incorporate multiple goals have been developed over the years, most of which share a common weakness. The determination of the goals to be used as attributes in the utility function is the result of a highly interactive process with the individual farmer, often difficult to implement. In this study, we use a non-interactive methodology, described in recent literature, to elicit the utility function of selected sheep farmers in western Greece, since farmers often appear reluctant to answer straightforward questions about their goals and preferences. Τhe results indicate that sheep farmers aim at the achievement of multiple goals, and that the maximization of gross margin is an important attribute in the utility function of mainly larger farms with a commercial orientation. The minimization of purchased forage, family labor and cost of hired labor are also important goals, especially for small and less commercial family farms. The multi objective farm level model built reproduces the Greek sheep farmers’ behavior more accurately and can replace the single objective model in decision making or agricultural planning problems.Sheep farming, mixed integer programming, multiple goals, noninteractive elicitation, Livestock Production/Industries, C61, D21, Q12,

Modeling Greenhouse Gas Emissions on Diversified Farms: The Case of Dairy Sheep Farming in Greece

Agricultural activity has been identified as a considerable source of Greenhouse Gas (GHG) emissions. Emissions from ruminant livestock farms are produced particularly due to CH4 emissions from enteric fermentation. Dairy sheep farming is the most important livestock production activity in Greece, characterized by a high degree of farm diversification. This paper addresses the issue of the evaluation of GHG emissions of Greek dairy sheep farms, through the use of a whole farm mathematical programming model that uses farm level data and optimizes total gross margin. Mathematical programming models are an appropriate tool, when addressing complex issues, such as GHG emissions. The analysis is undertaken on different farm types, instead of a representative farm, to account for the heterogeneity of the sheep farming activity. Thus, marginal abatement cost and appropriate mitigation strategies for diversified farms are determined. The results indicate that intensive farms cause few emissions per produced milk (2.7kg of CO2 eq). Also, the marginal abatement cost ranges among 51-64€/t for all types of sheep farms (at 20% abatement level). The model used in this analysis and the results it yields are useful to researchers and policy makers, who aim to design efficient mitigation measures

Greek cotton farmers' supply response to partial decoupling of subsidies

A mathematical programming model based on a countrywide sample of farms is used to assess the impacts of the new C.A.P on the supply of the cotton sector in Greece. Results show a decrease in cotton cultivated area along with the introduction of a new production system called "semi-abandonment cotton". Farm income is practically unchanged, largely due to the decoupled payments. When these payments are not considered, farm income turns negative in some cases, thus leading towards abandonment of activities

Multiple goals in farmers’ decision making: The case of sheep farming in Western Greece

Management strategies and performance differ among farmers, as a result of different, multiple and often conflicting goals. Many approaches to building farm level models that incorporate multiple goals have been developed over the years, most of which share a common weakness. The determination of the goals to be used as attributes in the utility function is the result of a highly interactive process with the individual farmer, often difficult to implement. In this study, we use a non-interactive methodology, described in recent literature, to elicit the utility function of selected sheep farmers in western Greece, since farmers often appear reluctant to answer straightforward questions about their goals and preferences. Τhe results indicate that sheep farmers aim at the achievement of multiple goals, and that the maximization of gross margin is an important attribute in the utility function of mainly larger farms with a commercial orientation. The minimization of purchased forage, family labor and cost of hired labor are also important goals, especially for small and less commercial family farms. The multi objective farm level model built reproduces the Greek sheep farmers’ behavior more accurately and can replace the single objective model in decision making or agricultural planning problems

Measuring technical efficiency in the Greek agricultural sector

This paper measures the degree of technical efficiency of Greek farms at discrete points in time. Stochastic frontier production functions are estimated from four annual Farm Accountancy Data Network (FADN) surveys of the 1992–1995 period. From the results, a measure of technical efficiency is calculated for each farm for each year. The four distributions of technical efficiency values are examined and compared. All four samples show a wide range of farm-specific technical efficiency but efficiency is improving over the period. The paper also presents frontier estimates for small and large farms classified according to economic size. In that case, technical efficiency measures are calculated and their distributions are examined and compared. The results show that large farms are more efficient than small farms. However, efficiency is improving in both size farms over the period. In general, the results of this study indicate that there is substantial scope for improving technical efficiency of Greek farms.

Investigation of Factors Influencing the Technical Efficiency of Agricultural Producers Participating in Farm Credit Programs: The Case of Greece

This study investigates a number of factors influencing technical efficiency of Greek farms participating in the 1994 European Union (EU) farm credit program. Technical efficiency measures are obtained within the framework of a parametric stochastic frontier. Factors showing a positive effect on technical efficiency are value of liabilities, number of hours of mechanical operation, large land size, and rental land, whereas those showing a negative effect are value of EU product subsidies, value of off-farm family income, and hired labor. The value of investments incurred by farms because of their participation in the 1994 farm credit program does not show any significant effect on technical efficiency. The predicted levels of technical efficiency indicate that the average technical efficiency of farms 3 years after participating in the 1994 farm credit program is lower than the average technical efficiency of the same farms the year before participating in the program. Thus, the program has failed to increase the efficiency of farms

Investigation of Factors Influencing the Technical Efficiency of Agricultural Producers Participating in Farm Credit Programs: The Case of Greece

This study investigates a number of factors influencing technical efficiency of Greek farms participating in the 1994 European Union (EU) farm credit program. Technical efficiency measures are obtained within the framework of a parametric stochastic frontier. Factors showing a positive effect on technical efficiency are value of liabilities, number of hours of mechanical operation, large land size, and rental land, whereas those showing a negative effect are value of EU product subsidies, value of off-farm family income, and hired labor. The value of investments incurred by farms because of their participation in the 1994 farm credit program does not show any significant effect on technical efficiency. The predicted levels of technical efficiency indicate that the average technical efficiency of farms 3 years after participating in the 1994 farm credit program is lower than the average technical efficiency of the same farms the year before participating in the program. Thus, the program has failed to increase the efficiency of farms.farm credit program, stochastic frontier, technical efficiency, Q10, Q12, Q16, Q19,