The Determinants of Technology Adoption by UK Farmers using Bayesian Model Averaging. The Cases of Organic Production and Computer Usage.

We introduce and implement a reversible jump approach to Bayesian Model Averaging for the Probit model with uncertain regressors. This approach provides a direct estimate of the probability that a variable should be included in the model. Two applications are investigated. The �rst is the adoption of organic systems in UK farming, and the second is the in�uence of farm and farmer characteristics on the use of a computer on the farm. While there is a correspondence between the conclusions we would obtain with and without model averaging results, we �find important di¤erences, particularly in smaller samples.Agriculture, Adoption, Model Averaging, Organic, Computer

Bayesian estimation of the infrequency of purchase model with an application to food demand in the UK

A Bayesian method of estimating multivariate sample selection models is introduced and applied to the estimation of a demand system for food in the UK to account for censoring arising from infrequency of purchase. We show how it is possible to impose identifying restrictions on the sample selection equations and that, unlike a maximum likelihood framework, the imposition of adding up at both latent and observed levels is straightforward. We find that higher income households consume proportionately more meat and more fresh fruit and vegetables. Regional differences in fruit and vegetable consumption are marked with the highest levels of consumption in London and the South East. The presence of children in a household reduces levels of vegetable consumption. Households employed in the professional or managerial sectors have higher levels of fruit and vegetable consumption. Age has an influence on the consumption of fats and sugars, with consumption declining amongst older households and on the types of fruit and vegetables consumed with younger households preferring more ready meals and prepared fruit and vegetables.Bayesian estimation; Demand system; Infrequency of purchase;

Integrating spatial dependence into stochastic frontier analysis

An approach to incorporate spatial dependence into Stochastic Frontier analysis is developed and applied to a sample of 215 dairy farms in England and Wales. A number of alternative specifications for the spatial weight matrix are used to analyse the effect of these on the estimation of spatial dependence. Estimation is conducted using a Bayesian approach and results indicate that spatial dependence is present when explaining technical inefficiency.Spatial dependence, technical efficiency, Bayesian, spatial weight matrix

Bayesian estimation of the infrequency of purchase model with an application to food demand in the UK

A Bayesian method of estimating multivariate sample selection models is introduced and applied to the estimation of a demand system for food in the UK to account for censoring arising from infrequency of purchase. We show how it is possible to impose identifying restrictions on the sample selection equations and that, unlike a maximum likelihood framework, the imposition of adding up at both latent and observed levels is straightforward. We find that higher income households consume proportionately more meat and more fresh fruit and vegetables. Regional differences in fruit and vegetable consumption are marked with the highest levels of consumption in London and the South East. The presence of children in a household reduces levels of vegetable consumption. Households employed in the professional or managerial sectors have higher levels of fruit and vegetable consumption. Age has an influence on the consumption of fats and sugars, with consumption declining amongst older households and on the types of fruit and vegetables consumed with younger households preferring more ready meals and prepared fruit and vegetables

Assessing the impact on chronic disease of incorporating the societal cost of greenhouse gases into the price of food: an econometric and comparative risk assessment modelling study

Objectives To model the impact on chronic disease of a tax on UK food and drink that internalises the wider costs to society of greenhouse gas (GHG) emissions and to estimate the potential revenue. Design An econometric and comparative risk assessment modelling study. Setting The UK. Participants The UK adult population. Interventions Two tax scenarios are modelled: (A) a tax of £2.72/tonne carbon dioxide equivalents (tCO2e)/100 g product applied to all food and drink groups with above average GHG emissions. (B) As with scenario (A) but food groups with emissions below average are subsidised to create a tax neutral scenario. Outcome measures Primary outcomes are change in UK population mortality from chronic diseases following the implementation of each taxation strategy, the change in the UK GHG emissions and the predicted revenue. Secondary outcomes are the changes to the micronutrient composition of the UK diet. Results Scenario (A) results in 7770 (95% credible intervals 7150 to 8390) deaths averted and a reduction in GHG emissions of 18 683 (14 665to 22 889) ktCO2e/year. Estimated annual revenue is £2.02 (£1.98 to £2.06) billion. Scenario (B) results in 2685 (1966 to 3402) extra deaths and a reduction in GHG emissions of 15 228 (11 245to 19 492) ktCO2e/year. Conclusions Incorporating the societal cost of GHG into the price of foods could save 7770 lives in the UK each year, reduce food-related GHG emissions and generate substantial tax revenue. The revenue neutral scenario (B) demonstrates that sustainability and health goals are not always aligned. Future work should focus on investigating the health impact by population subgroup and on designing fiscal strategies to promote both sustainable and healthy diets

Defining Professionalism for Mental Health Services : A Rapid Systematic Review

Background: Efforts have been made to define professionalism across the professions, yet little attention has been paid to the concept in mental health services, where patients’ needs differ to that in other healthcare specialties. Aims: To derive a definition of professionalism for mental health services using the existing literature. Method: A rapid, systematic review was conducted to identify empirical and non-empirical records that described professionalism in a mental health service context from 2006 to 2017. Studies were synthesised narratively using thematic analysis. Results: Seventy records were included in the review. Professionalism was described on two levels; at a societal level, a dynamic social contract between professions and society, and; at an individual level, having intrapersonal, interpersonal, and working professionalism. Utilising emerging themes, an operationalised definition of professionalism, suitable for a mental health service context was derived. Conclusions: Within mental health services, emphasis is placed on the interpersonal aspects of practice such as communication skills, maintaining boundaries and humanity. Themes relating to the vulnerability of patients and the challenge of supporting autonomy and choice whilst maintaining safety and acting in a client’s best interest are also evident. ‘Practical wisdom’ and a flexible approach to working are needed to manage these challenging situations

Integrating spatial dependence into stochastic frontier analysis

An approach to incorporate spatial dependence into Stochastic Frontier analysis is developed and applied to a sample of 215 dairy farms in England and Wales. A number of alternative specifications for the spatial weight matrix are used to analyse the effect of these on the estimation of spatial dependence. Estimation is conducted using a Bayesian approach and results indicate that spatial dependence is present when explaining technical inefficiency

A health impact assessment of the UK soft drinks industry levy: a comparative risk assessment modelling study

Background In March, 2016, the UK government proposed a tiered levy on sugar-sweetened beverages (SSBs; high, moderate, and no tax for drinks with >8g, 5g to 8g, and <5g sugar per 100ml). We estimate the effect of possible industry responses to the levy on obesity, diabetes, and dental caries. Methods We modelled three possible industry responses: (1) reformulation to reduce sugar concentration, (2) increasing product price, and (3) changing the market share of high-, mid-, and low-sugar drinks. For each response, we defined a better and worse case health scenario. We developed a comparative risk assessment model to estimate the UK health impact of each scenario. Findings The best modelled scenario for health is SSB reformulation, resulting in 144,000 (95% uncertainty interval: 5,100 to 306,700) fewer adults and children with obesity in the UK, 19,000 (6,900 to 32,700) fewer incident cases of diabetes per year, and 269,000 (82,200 to 470,900) fewer decayed, missing, or filled teeth annually. Increasing the price of SSBs and changes to market share to increase the proportion of low-sugar drinks sold would also result in population health benefits, but to a lesser extent. The greatest benefit for obesity and oral health would be among individuals under 18 years, with people over 65 years experiencing the largest absolute decreases in diabetes incidence. Interpretation The health impact of the soft drink levy is dependent on its implementation by industry. There is uncertainty as to how industry will react and in the estimation of health outcomes. Health gains could be maximised by significant product reformulation with additional benefits possible if the levy is passed onto purchasers through raising the price of high- and mid-sugar drinks, and through activities to increase the market share of low-sugar products.RT and AK have previously done work on sugar-sweetened beverage taxes funded by the Union of European Soft Drinks Associations. MR is chair of Sustain and the Children's Food Campaign, which have campaigned for sugar drink taxes in the UK. MR is funded by the British Heart Foundation, grant number 006/PSS/CORE/2016/OXFORD. ADMB and OTM are members of the Faculty of Public Health, which has a position statement supporting sugary drink taxes. ADMB is funded by the Wellcome Trust, grant number 102730/Z/13/Z. OTM is a member of the UK Health Forum, which has also supported a UK sugar drinks tax. OTM is supported by a Wellcome Trust Clinical Doctoral Fellowship. SAJ was the independent Chair of the Department of Health Public Health Responsibility Deal Food Network from 2010 to 2015. SAJ is funded by the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care Oxford. The views expressed are those of the authors and not necessarily those of the National Health Service, National Institute for Health Research, or the Department of Health. PS is funded by the British Heart Foundation, grant number FS/15/34/31656. TB is funded the Health Research Council of New Zealand (16/443). AE declares no competing interests