Economic studies of religion tend to focus on religious affiliation and attendance at religious services to the exclusion of other dimensions of religion, including religious belief. We address this lacuna, using data from the World Values Survey to construct an index of religious beliefs based on whether an individual believes in God, heaven, hell, an immortal soul, and the afterlife. Following the approach in a seminal article, we compare the roles of religious beliefs and attendance in determining economic values related to cooperation, patriarchy, institutional trust, lawfulness, thrift, markets, and market fairness. Controlling for denominational, country and period fixed effects and a set of individual-level characteristics, we find that religious beliefs matter for six of these seven values, relative to five for attendance. In addition, beliefs are more important than attendance for promarket and patriarchal values and less important for thrift, market fairness, lawfulness, and institutional trust. We also consider the relationships between beliefs, attendance, and economic values for eight religious’ affiliations: Protestant, Catholic, Orthodox Christian, Muslim, Buddhist, Hindu, other religions, and non-religious. Taken together, beliefs and attendance are most important for patriarchal values, promarket attitudes, lawfulness, and institutional trust. Relative to attendance, beliefs matter most for patriarchal attitudes and least for institutional trust. Our results suggest that religious beliefs constitute an important dimension of religious life. An exclusive focus on attendance may understate the role of religion in economic values.

Involuntary culling (IC) is where a cow is disposed of due to injury, poor health or infertility. The main reasons for IC are infertility, mastitis and lameness. These reasons have differing age profiles in when they affect cows, cost variable amounts to treat and have an effect on the value of the cow at market. They also reduce cow welfare in different ways. These factors influence the economically optimum cow replacement decision, which must balance the risks of future loss from the current cow against its future prospects and the net costs of a replacement. So the farmer's economic decision as to when to cull a cow may not occur at the same time as when the cow could, and sometimes should, be culled to maximise her welfare. To explore this dilemma, we developed a Dynamic Programme (DP) model to assess the optimum replacement policies for each of 180 possible cow states (12 parities and 15 milk-yield levels) under a simplified set of alternative husbandry systems and remedial practices. The DP was used to explore the relationships between financial outcomes, investment in improving welfare, lifespan and IC in dairy systems. There is a trade-off between dairy cattle lifespan and risk of suffering over which farmers have some control by the replacement and investment decisions they make. Our results show that improving cow welfare by reducing mastitis, lameness or infertility over the long term increases the mean longevity of the herd and also reduces the potential of long-term suffering resulting from chronic conditions. Additionally, it has the effect of increasing replacement opportunities and the annuities for each cow (£ per cow per year) mainly by increasing milk yield and reducing costly on-farm culls, creating a win-win situation for both farmer and cow.

In breeding programmes, the genetic selection process is based on the prediction of animal breeding values, and its results may vary according to the employed selection method. The current study developed an economic selection index for animals of the Angus breed; performed cluster analyses using the breeding values in order to evaluate the genetic profile of the animals candidates to selection, and compared the obtained results between the economic selection index and the cluster analyses. The evaluated traits included weaning weight, 18-month weight, scrotal circumference, fat thickness and ribeye area. Economic values were obtained using bioeconomic modelling, simulating a complete cycle production system of beef cattle breeds in Brazil, and the selection objective were the weaning rate and slaughter weight. The chosen selection index was composed of all of the traits used as selection criteria for the simulated production system. During the cluster analyses, the population was divided into two to four groups, in which the groupings containing potential animals were assessed. The animals of the grouping which was used for comparison with the selection index were identified, and most of the bulls that were included in the index were among the best in the analysed group. These results suggest that the cluster analyses can be used as a tool for the selection of animals to be used as parents for future generations.

Past findings on the connection between class position and political preferences are overwhelmingly derived from cross-sectional studies, which provided a limited basis for inferring causality. This study uses long-term panel data on thousands of British respondents to measure the impact of intra-generational class mobility across a range of political identities and preferences. Upward class mobility leads to small increases in economic conservatism, but party choice, class identity and attitudes to non-economic issues do not change. This updating of economic values is much smaller than cross-sectional differences between classes. These results are consistent with the short-run effects of class mobility operating primarily through a limited economic self-interest mechanism. Beliefs that are plausibly unconnected to economics are unaffected. The overall association between class and a range of identities, opinions and preferences is therefore more likely to be caused by early life experiences and longer-term socialization than by the immediate material interests associated with jobs.

In this study, the economic values for production and functional traits of dairy sheep are estimated through the application of a profit function model using farm-level technical and economic data. The traits incorporated in the model were milk production, prolificacy, fertility, milking speed, longevity and mastitis occurrence. The economic values for these traits were derived as the approximate partial derivative of the specified profit function. A sensitivity analysis was also conducted in order to examine how potential changes in input and output prices would affect the breeding goal. The estimated economic values of the traits revealed their economic impact on the definition of the breeding goal for the specified production system. Milk production and fertility had the highest economic values (€40.30 and €20.28 per standard genetic deviation (SDa)), while, mastitis only had a low negative value of −0.57 €/SDa. Therefore, breeding for clinical mastitis will have a minor impact on farm profitability because it affects a small proportion of the flock and has low additive variance. The production traits, which include milk production, prolificacy and milking speed, contributed most to the breeding goal (70.0%), but functional traits still had a considerable share (30.0%). The results of this study highlight the importance of the knowledge of economic values of traits in the design of a breeding program. It is also suggested that the production and functional traits under consideration can be categorized as those which can be efficiently treated through genetic improvement (e.g. milk production and fertility) while others would be better dealt with through managerial interventions (e.g. mastitis occurrence). Also, sub-clinical mastitis that affects a higher proportion of flocks could have a higher contribution to breeding goals.

Breeding programmes for livestock require economic weights for traits that reflect the most profitable animal in a given production system, which affect the response in each trait after selection. The profitability of sheep production systems is affected by changes in pasture growth as well as grain, meat and wool prices between seasons and across years. Annual pasture growth varies between regions within Australia’s Mediterranean climate zone from low growth with long periods of drought to high growth with shorter periods of drought. Therefore, the objective of this study was to assess whether breeding objectives need to be adapted for regions, depending on how reliable the pasture growth is across years. We modelled farms with Merino sheep bred for wool and meat in 10 regions in Western Australia. Across these 10 regions, mean annual pasture growth decreased, and the CV of annual pasture growth increased as pasture growth for regions became less reliable. We calculated economic values for nine traits, optimising management across 11 years, including variation for pasture growth and wool, meat and grain prices between and within years from 2002 to 2012. These economic values were used to calculate responses to selection for each trait for the 10 regions. We identified two potential breeding objectives, one for regions with low or high reliability and the other for regions with medium reliability of pasture growth. Breeding objectives for high or low pasture growth reliability had more emphasis on live weight traits and number of lambs weaned. Breeding objectives for medium reliability of pasture growth had more emphasis on decreasing fibre diameter. Relative economic weights for fleece weight did not change across the regions. Regions with low or high pasture reliability had similar breeding objectives and response to selection, because the relationship between the economic values and CV of pasture growth were not linear for live weight traits and the number of lambs weaned. This non-linearity was caused by differences in distribution of pasture growth between regions, particularly during summer and autumn, when ewes were pregnant, with increases in energy requirements affecting the value of lambs weaned. In addition, increasing live weight increased the intake capacity of sheep, which meant that more poor quality pasture could be consumed during summer and autumn, which had more value in regions with low and high pasture reliability. We concluded that breeding values for sheep production systems should be customised depending on the reliability of pasture growth between years.

The objective of the present review was (i) to survey different approaches for choosing the complex of traits for which economic values (EVs) are calculated, (ii) to call attention to the proper definition of traits and (iii) to discuss the manner and extent to which relationships among traits have been considered in the calculation of EVs. For this purpose, papers dealing with the estimation of EVs of traits in livestock were reviewed. The most important reasons for incompatibility of EVs for similar traits estimated in different countries and by different authors were found to be inconsistencies in trait definitions and in assumptions being made about relationships among traits. An important problem identified was how to choose the most appropriate criterion to characterise production or functional ability for a particular class of animals. Accordingly, the review covered the following three topics: (i) which trait(s) would best characterise the growth ability of an animal; (ii) how to define traits expressed repeatedly in subsequent reproductive cycles of breeding females and (iii) how to deal with traits that differ in average value between sexes or among animal groups. Various approaches that have been used to solve these problems were discussed. Furthermore, the manner in which diverse authors chose one or more traits from a group of alternatives for describing a specific biological potential were reviewed and commented on. The consequences of including or excluding relationships among economically important traits when estimating the EV for a specific trait were also examined. An important conclusion of the review is that, for a better comparability and interpretability of estimated EVs in the literature, it is desirable that clear and unique definitions of the traits, complete information on assumptions used in analytical models and details on inter-relationships between traits are documented. Furthermore, the method and the model used for the genetic evaluation of specific traits in a certain breeding organisation are important for the exact definition of traits, for which the economic values will be calculated, and for the inclusion or exclusion of relationships among traits in the calculation of the EVs in livestock breeding.

The objective of this work was to establish economic values (EVs) of mastitis and lameness in order to enhance the current UK dairy profit index (£PLI) by including these health traits. The EVs of traits currently in £PLI were also re-evaluated to account for changes in costs/returns over time and to determine their sensitivity to changes in some of the basic assumptions used in their derivation.

Predicted transmitting abilities (PTAs) for mastitis are not available in the UK. Instead, PTAs for somatic cell count (SCC), which has a strong genetic correlation with clinical mastitis, were used to predict clinical mastitis. Similarly, PTAs for locomotion and (for bulls with no locomotion PTA) the ‘legs and feet’ composite were used to predict lameness.

The EV of mastitis was estimated at £0·83 per percent incidence, giving an index weight for SCC PTA of £0·20. The EV of lameness was estimated at £0·99 per percent incidence, giving an index weight for locomotion PTA of £1·28. The associated index weight for the ‘legs and feet’ composite was estimated to be £1·50. Economic values for all traits (production, lifespan, mastitis and lameness) were found to be sensitive to their associated price assumption but not to price assumptions of other traits in the index or to other production parameters in the model.

Better information is needed on the influence of cow age (parity) on incidence of disease and on the probability of involuntary culling to determine the appropriate balance between the EVs for longevity and health. Currently, 16% of the weight in £PLI is attributable to non-production traits. In our revised index this weight increased to 23%. Even so, selection using this index is still predicted to result in an increase in mastitis and lameness, albeit at a very low rate. This situation may be changed by the introduction of fertility into £PLI and through better information about health traits. Incorporation of consumer preference into £PLI may require traits associated with health and welfare of the cow to receive more weight than their EV would suggest in order to maintain or improve health traits in national selection programmes.

Clinical mastitis (CM) and monthly test-day somatic cell count (SCC) records on Holstein cows were used to investigate the genetic and economic relationship of lactation average (of natural logarithms of) monthly test-day SCC (LSCC) with CM. After editing, there were 23663 lactation records on 17937 cows from 257 herds. Three groups of herds were first identified as having low (L), medium (M) and high (H) incidences of CM from the original or pooled (P) data set. Genetic parameters were estimated for the original and three data sub-sets (derived from the three herd groups). Expected genetic responses to selection against CM were calculated using genetic parameters of each data set separately, with an adapted version of the UK national index (£PLI-profitable lifetime index). Indirect economic values of SCC (EVSCC) were calculated as the direct cost of CM per cow per lactation weighted by the genetic regression coefficient of CM lactation records on their sires’ predicted transmitting ability for SCC (PTASCC). All genetic regression analyses were based on linear and threshold-liability models. Heritabilities and repeatabilities, respectively, were 0034 and 0·111 for CM and 0120 and 0·347 for LSCC in the original data set. Genetic, permanent environmental, residual and phenotypic correlations between CM and LSCC for the original (pooled) data set were 0·70, 0·44, 013 and 0·20, respectively. Parameter estimates for the three herd groups differed, with magnitude of the estimates increasing with increase in incidence from L to H herd groups. The EVSCC per unit of PTASCC for L, M, H and P herd groups, respectively, were £004, £0·15, £0·33 and £018 on the observed and £0·86, £0·96, £1·22 and £110 on the underlying-liability scales. Selection for mastitis resistance, using SCC as an indicator trait in an extended version of £PLI, resulted in a selection response of 0·9, 21, 1·7 and 1·9 more cases per 100 cows after 10 years of selection in L, M, H and P herd groups, respectively. These results suggest that genetic responses to selection for CM resistance as well as the EVSCC are specific to herd incidence and hence would be appropriate for customized selection indexes. The increase in CM cases was greater when CM was excluded from the £PLI (2·8 v 1·9), hence it is recommended that CM should be included in the breeding goal in order to arrest further decline or to make improvement in genetic resistance to clinical mastitis.

A dynamic programming model was used to derive economic values for the goal traits milk, fat and protein yield and longevity. The economic values derived were £3.37 per % cows surviving to complete lactation four (conditional on having a milk record in the first lactation) and £-0.03, £0.60 and £4.04 per kg for milk, fat and protein yield respectively. In terms of genetic standard deviations the weight for protein, fat, milk and longevity were 1.0, 0.21, —0.25 and 0.55, respectively. Using economic values and genetic (co) variances, weights were derived for milk fat, protein and four linear type traits (chosen out of fifteen on the basis of the genetic correlation with longevity): angularity (angular), foot angle (steeper), udder depth (shallower) and teat length (shorter). Three additive indices were derived, assuming that the breeding goal was for: (i) yield only (PIN), (ii) longevity only (LIN) or (ii) yield and longevity, hence economic merit (ITEM). Selection on ITEM is expected to give a 2% higher annual rate of genetic progress compared with selection on PIN. Efficiency of using ITEM was larger than 0.97 compared with the optimum index, when the real individual economic values increased or decreased by a factor 1.5 or 2.0. Weights for ITEM were calculated assuming that predicted transmitting abilities (PTAs) from complete multivariate analysis were used as index measurements. In the practical situation that index measurements came from (i) separate univariate best linear unbiased prediction (BLUP) evaluations or (ii) two multivariate BLUP evaluations (one for type and one for yield), efficiency of ITEM (compared with the optimum index) decreased with decreasing accuracy of the PTAs and with increasing ratio between number of records for type and yield, or vice versa, but remained close to 100%. Only in the (not practical) situation where accurate PTAs for type and inaccurate information for yield were combined, did the efficiency of ITEM drop as low as 0.44, due to a change of sign for udder depth in the optimal index.