In animal breeding, genetic parameters along with economic weights (EWs) of traits are applied. Profit functions currently used to calculate rabbit traits’ EWs do not consider nutrient requirements based on animal weight, growth rate and doe reproductive status. Therefore, the aim of this study was to develop a flexible bioeconomic model of rabbit-production systems and implement it in a computer programme in order to calculate economic values and relative EWs for rabbit traits. The bioeconomic model includes calculation of the doe age structure in the stationary state of a doe population; calculation of progeny structure; modelling growth, digestible energy, feed and water requirements for does in different reproductive statuses and for all progeny groups using a normative approach; calculation of the total feed and non-feed costs, revenues and profit per doe and per year; calculation of marginal economic values for up to 20 production and functional traits and estimation of the relative EWs of selected traits. The application of the programme is shown through an example calculation of trait economic values for a typical Czech commercial rabbit-production system. The trait economic value expresses the change in profit per doe and per year when the trait mean is increased by one unit. The programme developed is primarily useful for selection purposes in rabbit-breeding systems. Using this programme, some economic analyses of the impact of production, management and economic circumstances on the economic efficiency of various rabbit-production systems can also be performed.

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.

Using internet-based software known as 1000Minds, choice-experiment surveys were administered to experts and farmers from the Irish sheep industry to capture their preferences with respect to the relative importance – represented by part-worth utilities – of target traits in the definition of a breeding objective for sheep in Ireland. Sheep production in Ireland can be broadly separated into lowland and hill farming systems; therefore, each expert was asked to answer the survey first as if he or she were a lowland farmer and second as a hill farmer. In addition to the experts, a group of lowland and a group of hill farmers were surveyed to assess whether, and to what extent, the groups’ preferences differ from the experts’ preferences. The part-worth utilities obtained from the surveys were converted into relative economic value terms per unit change in each trait. These measures – referred to as ‘preference economic values’ (pEVs) – were compared with economic values for the traits obtained from bio-economic models. The traits ‘value per lamb at the meat processor’ and ‘lamb survival to slaughter’ were revealed as being the two most important traits for the surveyed experts responding as lowland and hill farmers, respectively. In contrast, ‘number of foot baths per year for ewes’ and ‘number of anthelmintic treatments per year for ewes’ were the two least important traits. With the exception of ‘carcase fat class’ (P < 0.05), there were no statistically significant differences in the mean pEVs obtained from the surveyed experts under both the lowland and hill farming scenarios. Compared with the economic values obtained from bio-economic models, the pEVs for ‘lambing difficulty’ when the experts responded as lowland farmers were higher (P < 0.001); and they were lower (P < 0.001) for ‘carcase conformation class’, ‘carcase fat class’ (less negative) and ‘ewe mature weight’ (less negative) under both scenarios. Compared with surveyed experts, pEVs from lowland farmers differed significantly for ‘lambing difficulty’, ‘lamb survival to slaughter’, ‘average days to slaughter of lambs’, ‘number of foot baths per year for ewes’, ‘number of anthelmintic treatments per year for ewes’ and ‘ewe mature weight’. Compared with surveyed experts, pEVs from hill farmers differed significantly for ‘lambing difficulty’, ‘average days to slaughter of lambs’ and ‘number of foot baths per year for ewes’. This study indicates that preference-based tools have the potential to contribute to the definition of breeding objectives where production and price data are not available.

Methods which estimate the effects on farm profit of a change in a genetic trait (economic weight) are compared. A neoclassical economic model based on a Cobb Douglas type production function, is extended to the long run and compared with a conventional profit equation for two types of trait changes. With this model, an optimal production plan can be derived for the farm which depends on input prices and the production function parameters. In the calculation of economic weights by animal breeders, costs are usually linear with respect to farm output, and so input levels and output are determined arbitrarily. Differences between methods for the estimation of both absolute and relative economic weights are shown to be small for proportional trait changes of 0·01 to 0·05. However, for proportional trait changes of 0·3, proportional differences were from 0·01 to 0·75 and from 0 to 0·6 for absolute and relative economic weights respectively, depending on the production function parameters. This dependence on the size of the trait change is attributed to the non-linearity of the production function. The effects of ‘rescaling’, which implicitly discounts economic weights for output increasing traits, are also evaluated. Absolute and relative ‘rescaled’ economic weights for 0·01 proportional trait changes are shown to differ proportionally from those estimated by the neoclassical economic model by from 0·14 and 0·12 to 0·50 respectively. For 0·3 trait changes, proportional differences were from 0·16 to 0·79 and from 0·8 to 0·43 for absolute and relative trait changes respectively. The results have important implications for conventional breeding programmes, and the economic evaluation of breeds and major genes.

This paper addresses the rescaling controversy in the estimation of economic weights for livestock improvement programmes. A model of genetic improvement based on the neoclassical theory of the firm and incorporating genetic improvement is proposed for the estimation of economic weights. Disparities between estimates of economic weights calculated per animal as opposed to per unit of product, per breeding female or per enterprise disappear when economic weights are calculated using this model. Equivalences of economic weights at the different bases of evaluation, previously obtained by rescaling the production enterprise to a fixed input, output or profit are compared with this model. The conventional approach to the derivation of economic weights is characterized as implicitly making unreasonable assumptions about the behaviour offarm firms.

Extension of the proposed model to the level of the farm product market allows assessment of the distribution of gains from genetic improvement between producers and consumers using the economic surplus approach. In an illustrative example, the distribution of benefits among producers and consumers from genetic improvement in the Ontario cow-calf sector is shown to depend on the elasticity of demand for beef products in the North American market. When the demand for farm output is elastic, a significant proportion of the benefits from genetic improvement would accrue to producers. Conversely, when demand is inelastic, the majority of benefits would accrue to consumers. Economic weights calculated from the perspective of all producers could thus be different from those calculated from the perspective of an individual farmer or society as a whole. Finally, the market level model is used to compare the effects of genetic improvement which enhance product quality with cost-reducing genetic improvements.