A Deliberative Method for Ranking Risks (II): Evaluation of Validity and Agreement among Risk Managers

A deliberative method for ranking risks was evaluated in a study involving 218 risk managers. Both holistic and multiattribute procedures were used to assess individual and group rankings of health and safety risks facing students at a fictitious middle school. Consistency between the rankings that emerged from these two procedures was reasonably high for individuals and for groups, suggesting that these procedures capture an underlying construct of riskiness. Participants reported high levels of satisfaction with their groups' decision-making processes and the resulting rankings, and these reports were corroborated by regression analyses. Risk rankings were similar across individuals and groups, even though individuals and groups did not always agree on the relative importance of risk attributes. Lower consistency between the risk rankings from the holistic and multiattribute procedures and lower agreement among individuals and groups regarding these rankings were observed for a set of high-variance risks. Nonetheless, the generally high levels of consistency, satisfaction, and agreement suggest that this deliberative method is capable of producing risk rankings that can serve as informative inputs to public risk-management decision making.     

Adaptive independence samplers

Markov chain Monte Carlo (MCMC) is an important computational technique for generating samples from non-standard probability distributions. A major challenge in the design of practical MCMC samplers is to achieve efficient convergence and mixing properties. One way to accelerate convergence and mixing is to adapt the proposal distribution in light of previously sampled points, thus increasing the probability of acceptance. In this paper, we propose two new adaptive MCMC algorithms based on the Independent Metropolis–Hastings algorithm. In the first, we adjust the proposal to minimize an estimate of the cross-entropy between the target and proposal distributions, using the experience of pre-runs. This approach provides a general technique for deriving natural adaptive formulae. The second approach uses multiple parallel chains, and involves updating chains individually, then updating a proposal density by fitting a Bayesian model to the population. An important feature of this approach is that adapting the proposal does not change the limiting distributions of the chains. Consequently, the adaptive phase of the sampler can be continued indefinitely. We include results of numerical experiments indicating that the new algorithms compete well with traditional Metropolis–Hastings algorithms. We also demonstrate the method for a realistic problem arising in Comparative Genomics.     

Ecological Risks of Diazinon from Agricultural Use in the Sacramento – San Joaquin River Basins, California

A probabilistic risk assessment was conducted to evaluate the likelihood and ecological significance of potential toxic effects of diazinon in the Sacramento-San Joaquin system. Diazinon, an organophosphorus insecticide, is used in the Sacramento-San Joaquin River Basin as a dormant spray on almonds and other tree crops, as well as for other agricultural and urban applications. Diazinon and other pesticides have been detected in the Sacramento and San Joaquin Rivers and their tributaries. Diazinon exposure was characterized based on monitoring programs conducted in 1991-94. Diazinon effects were characterized using laboratory toxicity data for 63 species, supplemented by results from field mesocosm and microcosm studies. The assessment addressed the possibility that reductions in invertebrate populations could lead to impacts on species of fish that feed on those invertebrates. The risk assessment concluded that fish in these rivers are not at risk from the direct effects of diazinon in the water. Invertebrates are at greater risk, especially in agriculturally dominated streams and drainage channels during January and February. Cladocerans--including Daphnia magna and Ceriodaphnia dubia, two common bioassay species--are especially sensitive to diazinon and other organophosphates and are likely to be subject to acute toxic effects in some locations at some times. Any ecological damage that may occur, however, is brief and limited to cladocerans. None of the fish species of concern depend on cladocerans as critical components of their diet. Invertebrates that are not affected by observed concentrations of diazinon (copepods, mysids, amphipods, rotifers, and insects) are preferred foods for fish in the Sacramento-San Joaquin system.     

Corporate Strategy Formulation and Taxation: Evidence from UK Firms*

This paper considers the relationship between corporate strategy formulation and taxation. Drawing on prior literature we briefly review the important influence that international taxation has on an array of corporate strategy decisions. We then consider issues in strategy formulation and taxation planning in order to develop an understanding of when and how taxation factors impinge on strategic decision‐making. We draw out the apparent paradox between the nature of strategic decision‐making and financial decision‐making and look for areas of reconciliation. In order to shed light on some of these issues we present findings from the qualitative analysis of a set of personal interviews undertaken with senior tax practitioners in seven UK‐based multinational enterprises and then consider quantitative responses from the tax practitioners working in 145 UK firms.     

A Response to Farrell

This article responds directly to an article published in this journal in February 2010 by Graham Farrell entitled ‘Situational crime prevention and its discontents: rational choice and harm reduction versus “cultural criminology” ’. (Farrell's article, in turn, was a rejoinder to my original 2007 article ‘Situational crime prevention and its discontents: rational choice theory versus the “culture of now” ’). In his article, Farrell sets out a case for the role of ‘harm reduction’ and rational choice theory as tools to reduce the contemporary crime problem, concluding that ‘Cultural criminology seems to offer little, if anything, useful to inform crime reduction efforts’. This article rejects this statement and offers a counter critique of the instrumental approach promoted by Farrell. Importantly, this response article is not intended as an outright critique of situational crime prevention per se, rather it is an assessment of Farrell's specific critical logic and the various shortcomings associated with his argument.     

At the nexus of risk and time preferences: An experimental investigation

Although many economic decisions involve choices between uncertain outcomes occurring at different times, most theoretical and empirical work restricts attention to one dimension or another. In this paper, we investigate whether both risk and time preferences can be represented by a single parameter. We collect experimental data to estimate models which allows for a disentanglement of risk and time preferences. Results reveal that the discounted expected utility model assumption, that risk and time preferences can be explained by a single parameter, is not supported by the data. The model estimates imply people prefer to delay the resolution of risky outcomes.     

True integer value time series

We construct an integer-valued stationary symmetric AR(1) process which can have either a positive or a negative lag-one autocorrelation. Nearly all integer-valued time series models are designed for observations which are non-negative integers or counts. They have innovations which are distributed on the non-negative integers and therefore obviously non-symmetric. We build our model using innovations that come from the difference of two independent identically distributed Poisson random variables. These innovations have a symmetric distribution, which has many advantages; in particular, they will allow us to model negative correlations. For our AR(1) process, we examine its basic properties and consider estimation via conditional least squares.