Tracking a changing copula

A copula models the relationships between variables independently of their marginal distributions. When the variables are time series, the copula may change over time. Recursive procedures based on indicator variables are proposed for tracking these changes over time. Estimation of the unknown parameters is by maximum likelihood. When the marginal distributions change, pre-filtering is necessary before constructing the indicator variables on which the recursions are based. This entails estimating time-varying quantiles and a simple method based on time-varying histograms is proposed. The techniques are applied to the Hong Kong and Korean stock market indices. Some interesting and unexpected movements are detected, particularly after the attack on the Hong Kong dollar in 1997.     

Combining choice modelling and multi-criteria analysis for technology diffusion: An application to the uptake of electric vehicles

Efforts to reduce greenhouse gas emissions in the residential sector by adopting technologies such as solar photovoltaics and electric vehicles (EVs) have major implications for the capacity of electricity distribution networks, particularly at local areas with high uptake. Consumer decisions to purchase these technologies are also influenced by several complex criteria such as costs/benefits, performance, appeal/status, risk, psychographics, and demographics. This complexity motivated the development of an innovative diffusion model, incorporating features of multi-criteria analysis and choice modelling, to estimate the adoption of these technology options spatially across the landscape of heterogeneous consumers. We test the model to forecast market share of EVs through to 2030, using the vehicle stock across all 1.5 million households in Victoria, Australia. Seven financial and non-financial criteria were included and calibrated via focus groups and a large‐scale survey. Annual change of criteria values and their elasticity to adoption were incorporated. Geographical differences in uptake of EVs were primarily due to driving distance, employment status and household income, with urban areas having about three times the proportional uptake. By testing the model for a range of incentives, we demonstrate its capability to inform and evaluate policy options.     

Monotonicity in asset returns: New tests with applications to the term structure,the CAPM,and portfolio sorts

Many theories in finance imply monotonic patterns in expected returns and other financial variables. The liquidity preference hypothesis predicts higher expected returns for bonds with longer times to maturity; the Capital Asset Pricing Model (CAPM) implies higher expected returns for stocks with higher betas; and standard asset pricing models imply that the pricing kernel is declining in market returns. The full set of implications of monotonicity is generally not exploited in empirical work, however. This paper proposes new and simple ways to test for monotonicity in financial variables and compares the proposed tests with extant alternatives such as t-tests, Bonferroni bounds, and multivariate inequality tests through empirical applications and simulations.     

Variable reduction,sample selection bias and bank retail credit scoring

This paper investigates the effect of including the customer loan approval process to the estimation of loan performance and explores the influence of sample selection bias in predicting the probability of default. The bootstrap variable reduction technique is applied to reduce the variable dimension for a large data-set drawn from a major UK retail bank. The results show a statistically significant correlation between the loan approval and performance processes. We further demonstrate an economically significant improvement in forecasting performance when taking into account sample selection bias. We conclude that financial institutions can obtain benefits by correcting for sample selection bias in their credit scoring models.     

Rorty,Caputo and business ethics without metaphysics: ethical theories as normative narratives

Using the works of Richard Rorty and John Caputo, I want to suggest that we might be better off treating the traditional ethical theories of Kant, Mill, Aristotle and Hobbes as normative narratives rather than as justificatory schemes for moral decision making to be set up against one another. In a spirit akin to Husserl's ‘bracketing’ of metaphysics, when discussing ethical theories in business ethics, we can easily avoid metaphysics and use an approach that sees ethical theory as socially convincing normative narratives – narratives that unify us with others insofar as they describe our phenomenological experiences in a way with which many of us mutually resonate. I will do this by attempting to show how John Caputo's thinking in Against Ethics and Rorty's postmodern pragmatism might be appropriated to some extent by us in business ethics.     

The mediating effects of perception and emotion: Digital signage in mall atmospherics

Digital signage (DS), public screens showing video, is an important, little-researched topic. The “direct” route in the elaboration likelihood model suggests that DS influences cognition, which then influences emotions whereas the “peripheral” route is emotion→cognition. We predict that these operate in parallel and report a survey of mall consumers (n=315). DS has a significant, positive, total effect on approach behaviors, mediated by positive affect and (arguably) perception of mall environment. Results extend the limited capacity model of mediated message processing from television to DS, which predicts the effectiveness of vivid moving visual images as atmospheric stimuli.     

Music to Your Brain: Background Music Changes Are Processed First,Reducing Ad Message Recall

Background music captures attention, evokes images, and creates ambience, but may interfere with processing of advertised messages, reducing recall. Brains are hardwired to process unexpected background sound changes first, automatically preempting processing of brand message elements and reducing recall. The degree of this recall reduction depends on the structural characteristics of the music, as well as the advertised brand. Backgrounds with more frequent harmonic and textural changes create more frequent distraction, reducing message recall. Faster tempos increase the frequency of those distractions. However, faster tempos also enable streaming of like distractions, improving message recall. In Experiment 1, backgrounds, varying in harmonic, textural, and temporal characteristics, were compared across ads for six brands. Message recall was higher for ads with backgrounds with less‐frequent change. Message recall from ads for new, unfamiliar brands suffered more from background music interference than from ads for established brands. In Experiment 2, background change frequency was reduced in two ads, holding all else constant, which improved message recall.     

Organisational Culture and Budgetary Control in a UK Local Government Organisation

This paper is an attempt to explore the possibilities of working within the functional paradigm to understand the relationship between organisational culture and financial control. More specifically, the research is an empirical study informed by contingency theory. The research uses canonical correlation analysis to investigate the complex contingent relationship, as suggested by Williams, Mcintosh and Moore (1990). The research was carried out within a local government organisation in the UK, and used a questionnaire to determine managers' perceptions of organisational culture and budget-related behaviour. A correlation was found between organisational culture and budget-related behaviour, particularly with respect to budgetary participation and the usefulness of budgets to support the managerial role. However, the relationship was not straightforward, and the analysis indicated some tension between culture and the financial control system in operation.     

Science,Technology and the Quest for Sustainable Development

The quest for sustainable development is seen in this article as an intrinsic part of the reconstitution of environmentally-oriented science and technology policy that has been taking place over the past 15 years in most European countries. Rather than dealing with environmental problems after they have occurred, the trend is increasingly to base environmental research and development on so-called preventive principles and to seek to integrate environmental concern into all other areas of science and technology development. There is also a widespread effort to foster new ways to involve the 'public' in the making of science and technology policy. The article is based on results from the project, Public Engagement and Science and Technology Policy Options (PESTO), for which the author served as coordinator.     

Group Structured Reasoning for Coalescing Group Decisions

In this paper we present the notion of structured reasoning through a model, called the Generic/Actual Argument Model (GAAM). The model which has been used as a computational representation for machine modelling of reasoning and for hybrid combinations of human and machine reasoning can be used as a coalescent framework for decision making. Whilst the notion of structuring reasoning is not new, structured reasoning is advanced as a technique where group consensus on reasoning structures at various levels can be used to facilitate the comprehension of complex reasoning particularly where there are multiple perspectives. For an issue, the approach provides a scaffolding structure for cognitive co-operation and a normative reasoning structure against which group participants can identify points of difference and points in common as well as the nature of the differences and similarities. Intra-group transparency characterized by the ability to recognise points in common and understand the nature of differences is important to the process of coalescing group decisions that carry maximum group support.