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Market failures are the main cause of poor acknowledgement of the true impact of functional sheep traits on the management and economic performance of farms, which results in their omission from the breeding goal or the estimation of non-representative economic weights in the breeding goal. Consequently, stated-preference non-market valuation techniques, which recently emerged to mitigate these problems, are necessary to estimate economic weights for functional traits. The purpose of this paper is to present an example of the use of a choice experiment (CE) in the estimation of economic weights for sheep traits for the design of breeding goals. Through a questionnaire survey the preferences of sheep farmers are recorded and their marginal willingness to pay (MWTP) for 10 production and functional traits is estimated. Data are analysed using random parameter logit models. The results reveal unobserved preference heterogeneity for fertility, adaptability to grazing and resistance to disease, thus highlighting that these traits are appreciated differently by farmers, because their needs are diverse. Positive MWTP is found for Greek breeds, high milk production and lambs with low fat deposition, for which there is high demand in Greek markets. On the other hand, MWTP for the cheese-making ability of milk is negative, stemming from the fact that sheep milk prices in Greece are not formulated according to milk composition. In addition, farmers seem to understand differences between udder shapes and attribute different values to various types. This application of the CE method indicates that communication channels among farmers and breeders should be established in order to enhance market performance and to provide orientation to the design of breeding programmes. Non-market valuation can be used complementarily to market valuation techniques, in order to provide accurate estimates for production and functional traits.

In this study, the level of technical efficiency of 58 sheep farms rearing the Chios breed in Greece was measured through the application of the stochastic frontier analysis method. A Translog stochastic frontier production function was estimated using farm accounting data of Chios sheep farms and the impact of various socio-demographic and biophysical factors on the estimated efficiency of the farms was evaluated. The farms were classified into efficiency groups on the basis of the estimated level of efficiency and a technical and economic descriptive analysis was applied in order to illustrate an indicative picture of their structure and productivity. The results of the stochastic frontier model indicate that there are substantial production inefficiencies among the Chios sheep farms and that these farms could increase their production through the improvement of technical efficiency, whereas the results of the inefficiency effects model reveal that the farm-specific explanatory factors can partly explain the observed efficiency differentials. The measurement of technical inefficiency and the detection of its determinants can be used to form the basis of policy recommendations that could contribute to the development of the sector.