What to Do at Low Doses: A Bounding Approach for Economic Analysis

To quantify the health benefits of environmental policies, economists generally require estimates of the reduced probability of illness or death. For policies that reduce exposure to carcinogenic substances, these estimates traditionally have been obtained through the linear extrapolation of experimental dose-response data to low-exposure scenarios as described in the U.S. Environmental Protection Agency's Guidelines for Carcinogen Risk Assessment (1986). In response to evolving scientific knowledge, EPA proposed revisions to the guidelines in 1996. Under the proposed revisions, dose-response relationships would not be estimated for carcinogens thought to exhibit nonlinear modes of action. Such a change in cancer-risk assessment methods and outputs will likely have serious consequences for how benefit-cost analyses of policies aimed at reducing cancer risks are conducted. Any tendency for reduced quantification of effects in environmental risk assessments, such as those contemplated in the revisions to EPA's cancer-risk assessment guidelines, impedes the ability of economic analysts to respond to increasing calls for benefit-cost analysis. This article examines the implications for benefit-cost analysis of carcinogenic exposures of the proposed changes to the 1986 Guidelines and proposes an approach for bounding dose-response relationships when no biologically based models are available. In spite of the more limited quantitative information provided in a carcinogen risk assessment under the proposed revisions to the guidelines, we argue that reasonable bounds on dose-response relationships can be estimated for low-level exposures to nonlinear carcinogens. This approach yields estimates of reduced illness for use in a benefit-cost analysis while incorporating evidence of nonlinearities in the dose-response relationship. As an illustration, the bounding approach is applied to the case of chloroform exposure.     

Yardstick competition and political agency problems

We examine how yardstick competition between jurisdictions affects the agency problem resulting from uncertainty about politicians (adverse selection) and their policies (moral hazard). We find that yardstick comparison can contribute both to disciplining and to selecting politicians.Earlier versions of this paper have circulated as Queen Mary Working Paper No. 444 and CORE Discussion Paper 2002/29. We would like to thank our editor, Maurice Salles, two anonymous referees, Mark Armstrong and Enrico Minelli for helpful comments and suggestions. We would also like to thank seminar participants at CORE, Queen Mary, Marseilles, and the 2002 Public Economic Theory conference, Université Paris 1.     

Which is the ‘self’ in ‘self‐interest’?

This article contends that homogenisation of the term ‘self‐interest’– in sociological and economic discourse – has resulted in many misconceptions about what particular doctrines of ‘self‐interest’ were instituted to achieve at certain historical periods and in specific cultural milieux. At its worst, the article argues, this has led to a misunderstanding of the import of particular doctrines of self interest,which are read in terms of general tradition – such as that which views self‐interested conduct as a natural faculty – rather than in terms of the context specific aims of those advocating them. The article attempts to show how, historically, there have been quite significant changes in the characterisation of the ‘self’ deemed to be ‘self‐interested’. In particular, it focuses on the ‘self’ of certain early modern conceptions of self interest, and suggests this creation is best viewed not as a subjectivity transcendentally presupposed by experience, but as one historically cultivated to counter the exigencies of particular circumstances – the disaster of perpetual ‘warre’ in 17th century Europe – and to meet the purposes of a certain way of life – existence in the civitas.     

Multiple imputation of missing data with ante-dependence covariance structure

A controlled clinical trial was conducted to investigate the efficacy effect of a chemical compound in the treatment of Premenstrual Dysphoric Disorder (PMDD). The data from the trial showed a non-monotone pattern of missing data and an ante-dependence covariance structure. A new analytical method for imputing the missing data with the ante-dependence covariance is proposed. The PMDD data are analysed by the non-imputation method and two imputation methods: the proposed method and the MCMC method.     

The State of Care Management in Learning Disability and Mental Health Services 12 Years into Community Care

This paper reports on the organization of care management froma longitudinal study of community care for people resettledfrom long-stay learning disability and psychiatric hospitals.The findings from a 12-year follow-up of care management arrangementsin 12 learning disability and eight mental health study siteservices are described. The diversity of care management arrangementsfound at earlier points in the evaluation remained evident.Also, many of the former ‘care in the community’service users were excluded from mainstream care managementarrangements in their localities. The difficulty of developingperson-centred arrangements in learning disability and the lackof integration of the Care Programme Approach and care managementwere evident. The findings and observations are placed in thewider policy and practice context, with suggestions for takingcare management forward nationally and locally.     

Benchmark Analysis: Shopping with Proper Confidence

We discuss the issue of using benchmark doses for quantifying (excess) risk associated with exposure to environmental hazards. The paradigm of low-dose risk estimation in dose-response modeling is used as the primary application scenario. Emphasis is placed on making simultaneous inferences on benchmark doses when data are in the form of proportions, although the concepts translate easily to other forms of outcome data.     

MEANINGFUL REGRESSION AND ASSOCIATION MODELS FOR CLUSTERED ORDINAL DATA

Many proposed methods for analyzing clustered ordinal data focus on the regression model and consider the association structure within a cluster as a nuisance. However, the association structure is often of equal interest—for example, temporal association in longitudinal studies and association between responses to similar questions in a survey. We discuss the use, appropriateness, and interpretability of various latent variable and Markov models for the association structure and propose a new structure that exploits the ordinality of the response. The models are illustrated with a study concerning opinions regarding government spending and an analysis of stability and change in teenage marijuana use over time, where we reveal different behavioral patterns for boys and girls through a comprehensive investigation of individual response profiles.     

National survey evidence on disasters and relief: Risk beliefs, self-interest, and compassion

A nationally representative sample of respondents estimated their fatality risks from four types of natural disasters, and indicated whether they favored governmental disaster relief. For all hazards, including auto accident risks, most respondents assessed their risks as being below average, with one-third assessing them as average. Individuals from high-risk states, or with experience with disasters, estimate risks higher, though by less than reasonable calculations require. Four-fifths of our respondents favor government relief for disaster victims, but only one-third do for victims in high-risk areas. Individuals who perceive themselves at higher risk are more supportive of government assistance.