The views of key stakeholders on an evolving food risk governance framework: Results from a Delphi study

Evidence of a decline in public trust associated with food risk governance over recent years has called into question the appropriateness of the current dominant risk analysis framework. Within the EU-funded SAFE FOODS project a novel risk analysis framework has been developed that attempts to address potential shortcomings by increasing stakeholder (including consumer) input, improving transparency, and formally incorporating benefit and non-health aspects into the analysis. To assess the viability of this novel framework, the views of food risk experts from the EU and beyond were sought using a distributed online questionnaire process called Delphi. In this paper the main results of this survey are described, revealing varying levels of support for the key innovations of the novel framework. Implications of our results for the new and old frameworks, for the future of risk analysis, and for the policy community more widely, are discussed.     

Modelling employment durations of NHL head coaches: turnover and post‐succession performance

Match‐level National Hockey League (NHL) data are used to identify factors likely to trigger the departure of a team's coach, and to measure the short‐term impact on subsequent match results. There is a statistically significant link between individual match results and the job departure hazard for up to 15 games prior to the point of departure. The hazard depends on the team's current standing within its conference relative to a pre‐season forecast, recent performance in the Stanley Cup, the coach's age and previous employment with his present team as a player. After controlling for a mean‐reversion effect, teams that changed their coach within‐season are found to perform worse subsequently than those that did not, but the negative effect is short‐lived. Copyright © 2006 John Wiley & Sons, Ltd.     

Developing a framework for network and cluster identification for use in economic development policy-making

Drawing on extensive academic research concerning clusters and networks, this paper seeks to create a framework capable of reviewing and monitoring different aspects of clusters and networks on an ongoing basis. The nine-element framework allows evaluation of the structures and processes for the eight basic cluster types identified from the literature. The use of this framework as a complimentary tool to the Multi-sectoral Qualitative Analysis (MSQA) methodology is then demonstrated using three examples (the construction, hardwood timber and higher education sectors). The data was gathered from three sets of key stakeholders (government, institutions and industry) provided from a recent study funded by the Welsh Assembly Government's Small Grants Research Programme. These cases illustrate the use of the framework in helping to generate the initial information necessary for subsequent cluster development policy (within overall regional economic development) by government to occur. The framework provides tools for reviewing and monitoring individual sectors. Information captured within the framework can also help in ameliorating problems in sectors likely to decline further. The need for further development research is also identified. Specifically at the level of the firm and network, there is a need to generate a more detailed framework of analysis of factors that contribute to successful processes of network management, learning and innovation, from which more detailed policy could be enacted in future.     

The tradeoff between mortgage prepayments and tax-deferred retirement savings

Many households face the tradeoff between paying an extra dollar off the remaining mortgage on their house and saving that extra dollar in tax-deferred accounts (TDAs) used for retirement. We show that, under certain conditions, it becomes a tax arbitrage to reduce mortgage prepayments and to increase TDA contributions because of the tax deductibility of mortgage interest and tax-exemption of qualified retirement savings. Using data from the Survey of Consumer Finances, we document that a significant number of households that are accelerating their mortgage payments instead of saving in TDAs forgo a profitable tax arbitrage opportunity. Finally, we show empirically that this inefficient behavior is unlikely to be driven by liquidity or other financial constraints. Rather, the observed behavior can be attributed to a certain extent to the reluctance of many households to participate in financial markets as either lenders or borrowers.     

Dominant CEO,Deviant Strategy,and Extreme Performance: The Moderating Role of a Powerful Board

This study examines the effect of dominant CEOs – defined as CEOs who are very powerful relative to other executives in their top management teams – on firm strategy and performance. Based on a sample of 51 publicly traded, single‐business firms from the US computer industry for the period 1997–2003, our results suggest that firms with dominant CEOs tend to have a strategy deviant from the industry central tendency and thus extreme performance – either big wins or big losses. Further, powerful boards weaken the tendency of dominant CEOs towards extremeness and, more important, improve the likelihood of dominant CEOs having big wins versus big losses. This study reconciles the pessimistic and heroic views regarding dominant CEOs, and suggests that the notion of power balance should be considered in a broader context.     

Learning Objectives and Testing: An Analysis of Six Principles of Economics Textbooks,Using Bloom's Taxonomy

This study applies Bloom's Taxonomy of Educational Objectives to six principles of economics textboks and the accompanying instructor's manuals to determine whether the test banks provided are likely to measure the textbooks' stated objectives. The study finds significant discrepancies between the stated objectives of most textbooks and the instruments included in the instructor's manuals to measure student achievement.     

Critical factors in computing externalities for electricity resources

The New York State Environmental Externalities Cost Study and computerized externality model (EXMOD) are used to examine the specification of methods design and application factors in the computation of electricity externalities. We report the sensitivity of externality estimates with alternative specifications for 15 different factors in the analysis, including the selection of facility type, site, and operating characteristics; air emission assumptions and air modeling procedures; dose-response assumptions; economic valuation assumptions; and other modeling procedures and assumptions. Many of the factors that most influence externality computations can be well specified in the analysis, such as the facility type, age, characteristics, emission rates, whether there is SO₂ trading, and the inclusion of long range impacts. Most significant among the factors for which there remains significant scientific uncertainty are the selection and application of air dispersion models, selection of air pollution thresholds for health impacts, reduced life span risks associated with ozone exposure and with long-term exposure to PM₁₀, values for CO₂ damages, and the value to be applied to increased risks of reduced life span for individuals age 65 or older.