Rural communities and wind farms: a contingent valuation investigation

Using the contingent valuation method, this study investigates the preferences of local people for a wind farm that is planned in the Province of Rome. We estimate the reductions in their bimonthly electrical bills over a period of time that respondents are willing to accept as compensation for the installation of the wind farm. Our results suggest that respondents who perceive that the wind farm generates substantial negative impacts on landscape beauty ask higher reductions than others, while respondents who believe that the wind farm produces economic benefits for local communities ask lower reductions than others. Finally, we find that the demand for compensative measures is influenced particularly by socio-economic factors such as age and education.

The complexity of biodiversity: A biological perspective on economic valuation

To value something, you first have to know what it is. Bartkowski et al. (2015) reveal a critical weakness: that biodiversity has rarely, if ever, been defined in economic valuations of putative biodiversity. Here we argue that a precise definition is available and could help focus valuation studies, but that in using this scientific definition (a three-dimensional measure of total difference), valuation by stated-preference methods becomes, at best, very difficult.We reclassify the valuation studies reviewed by Bartkowski et al. (2015) to better reflect the biological definition of biodiversity and its potential indirect use value as the support for provisioning and regulating services. Our analysis shows that almost all of the studies reviewed by Bartkowski et al. (2015) were not about biodiversity, but rather were about the 'vague notion' of naturalness, or sometimes a specific biological component of diversity. Alternative economic methods should be found to value biodiversity as it is defined in natural science. We suggest options based on a production function analogy or cost-based methods. Particularly the first of these provides a strong link between economic theory and ecological research and is empirically practical. Since applied science emphasizes a scientific definition of biodiversity in the design and justification of conservation plans, the need for economic valuation of this quantitative meaning of biodiversity is considerable and as yet unfulfilled.

Parallel Time Series Analysis and Income Inequality: A New Approach to Comparative Case Studies

This case study deals with the role of time series analysis in sociology, and its relationship with the wider literature and methodology of comparative case study research. Time series analysis is now well-represented in top-ranked sociology journals, often in the form of ‘pooled time series’ research designs. These studies typically pool multiple countries together into a pooled time series cross-section panel, in order to provide a larger sample for more robust and comprehensive analysis. This approach is well suited to exploring trans-national phenomena, and for elaborating useful macro-level theories specific to social structures, national policies, and long-term historical processes. It is less suited however, to understanding how these global social processes work in different countries. As such, the complexities of individual countries - which often display very different or contradictory dynamics than those suggested in pooled studies – are subsumed. Meanwhile, a robust literature on comparative case-based methods exists in the social sciences, where researchers focus on differences between cases, and the complex ways in which they co-evolve or diverge over time. A good example of this is the inequality literature, where although panel studies suggest a general trend of rising inequality driven by the weakening power of labour, marketisation of welfare, and the rising power of capital, some countries have still managed to remain resilient. This case study takes a closer look at what can be learned by applying the insights of case-based comparative research to the method of time series analysis. Taking international income inequality as its point of departure, it argues that we have much to learn about the viability of different combinations of policy options by examining how they work in different countries over time. By taking representative cases from different welfare systems (liberal, social democratic, corporatist, or antipodean), we can better sharpen our theories of how policies can be more specifically engineered to offset rising inequality. This involves a fundamental realignment of the strategy of time series analysis, grounding it instead in a qualitative appreciation of the historical context of cases, as a basis for comparing effects between different countries.

Stated preference methods and landscape ecology indicators: an example of transdisciplinarity in landscape economic valuation

This paper addresses the representation of landscape complexity in stated preferences research. It integrates landscape ecology and landscape economics and conducts the landscape analysis in a three-dimensional space to provide ecologically meaningful quantitative landscape indicators that are used as variables for the monetary valuation of landscape in a stated preferences study. Expected heterogeneity in taste intensity across respondents is addressed with a mixed logit model in Willingness to Pay space. Our methodology is applied to value, in monetary terms, the landscape of the Sorrento Peninsula in Italy, an area that has faced increasing pressure from urbanization affecting its traditional horticultural, herbaceous, and arboreal structure, with loss of biodiversity, and an increasing risk of landslides. We find that residents of the Sorrento Peninsula would prefer landscapes characterized by large open views and natural features. Residents also appear to dislike heterogeneous landscapes and the presence of lemon orchards and farmers' stewardship, which are associated with the current failure of protecting the traditional landscape. The outcomes suggest that the use of landscape ecology metrics in a stated preferences model may be an effective way to move forward integrated methodologies to better understand and represent landscape and its complexity.

Sexual abuse of children in low-income settings:time for action

In this article, child sexual abuse in low-income settings is reviewed, including the extent of the problem, the way children present, and how they should be managed. Liaising with other agencies, training in all aspects of sexual abuse and creating an environment that is conducive to good care by all groups involved is essential. Technical details of medical examination are not covered as appropriate guidelines are accessible.

The Valuation Implications of Enterprise Risk Management Maturity

Enterprise Risk Management (ERM) is the discipline by which enterprises monitor, analyze, and control risks from across the enterprise, with the goal of identifying underlying correlations and thus optimizing the risk-taking behavior in a portfolio context. This study analyzes the valuation implications of ERM Maturity. We use data from the industry leading Risk and Insurance Management Society Risk Maturity Model over the period from 2006 to 2011, which scores firms on a five-point maturity scale. Our results suggest that firms that have reached mature levels of ERM are exhibiting a higher firm value, as measured by Tobin's Q. We find a statistically significant positive relation to the magnitude of 25 percent. Upon decomposition of the maturity score, we find that the most important aspects of ERM from a valuation perspective relate to the level of top–down executive engagement and the resultant cascade of ERM culture throughout the firm. Firms that have successfully integrated the ERM process into both their strategic activities and everyday practices display superior ability in uncovering risk dependencies and correlations across the entire enterprise and as a consequence enhanced value when undertaking the ERM maturity journey ceteris paribus.

Predicting impact damage, residual strength and crashworthiness of composite structures

The development of the latest generation of wide-body carbon-fibre composite passenger aircraft has heralded a new era in the utilisation of these materials. The premise of superior specific strength and stiffness, corrosion and fatigue resistance, is tempered by high development costs, slow production rates and lengthy and expensive certification programmes. Substantial effort is currently being directed towards the development of new modelling and simulation tools, at all levels of the development cycle, to mitigate these shortcomings. One of the primary challenges is to reduce the extent of physical testing, in the certification process, by adopting a ‘certification by simulation’ approach. In essence, this aspirational objective requires the ability to reliably predict the evolution and progression of damage in composites. The aerospace industry has been at the forefront of developing advanced composites modelling tools. As the automotive industry transitions towards the increased use of composites in mass-produced vehicles, similar challenges in the modelling of composites will need to be addressed, particularly in the reliable prediction of crashworthiness. While thermoset composites have dominated the aerospace industry, thermoplastics composites are likely to emerge as the preferred solution for meeting the high-volume production demands of passenger road vehicles. This keynote presentation will outline recent progress and current challenges in the development of finite-element-based predictive modelling tools for capturing impact damage, residual strength and energy absorption capacity of thermoset and thermoplastic composites for crashworthiness assessments.