On Bayesian estimators in multistage binomial designs

A new class of Bayesian estimators for a proportion in multistage binomial designs is considered. Priors belong to the beta-J distribution family, which is derived from the Fisher information associated with the design. The transposition of the beta parameters of the Haldane and the uniform priors in fixed binomial experiments into the beta-J distribution yields bias-corrected versions of these priors in multistage designs. We show that the estimator of the posterior mean based on the corrected Haldane prior and the estimator of the posterior mode based on the corrected uniform prior have good frequentist properties. An easy-to-use approximation of the estimator of the posterior mode is provided. The new Bayesian estimators are compared to Whitehead's and the uniformly minimum variance estimators through several multistage designs. Last, the bias of the estimator of the posterior mode is derived for a particular case.     

Impacts of the Triple Global Crisis on Growth and Poverty: The Case of Yemen

Yemen is an oil‐exporting and food‐importing country with the highest levels of poverty in the Middle East and North Africa. The impacts of the triple crisis are likely to further complicate pre‐existing conditions of conflict, oil depletion and governance failure. Using a dynamic CGE model, this article finds that oil‐driven growth in 2008 dominated the negative growth impacts of the food crisis, but that growth was not pro‐poor. The financial crisis of 2009 slowed growth sharply and raised the poverty rate to 42.8%, up from 34.8% in 2005/6. Poverty continues to be higher in rural areas, where almost half the population live in poverty.     

Estimation of the Force of Infection from Current Status Data Using Generalized Linear Mixed Models

Based on sero-prevalence data of rubella, mumps in the UK and varicella in Belgium, we show how the force of infection, the age-specific rate at which susceptible individuals contract infection, can be estimated using generalized linear mixed models (McCulloch & Searle, 2001). Modelling the dependency of the force of infection on age by penalized splines, which involve fixed and random effects, allows us to use generalized linear mixed models techniques to estimate both the cumulative probability of being infected before a given age and the force of infection. Moreover, these models permit an automatic selection of the smoothing parameter. The smoothness of the estimated force of infection can be influenced by the number of knots and the degree of the penalized spline used. To determine these, a different number of knots and different degrees are used and the results are compared to establish this sensitivity. Simulations with a different number of knots and polynomial spline bases of different degrees suggest - for estimating the force of infection from serological data - the use of a quadratic penalized spline based on about 10 knots.     

Assessment of the Effectiveness of Radon Screening Programs in Reducing Lung Cancer Mortality

The present study was aimed at assessing the health consequences of the presence of radon in Quebec homes and the possible impact of various screening programs on lung cancer mortality. Lung cancer risk due to this radioactive gas was estimated according to the cancer risk model developed by the Sixth Committee on Biological Effects of Ionizing Radiations. Objective data on residential radon exposure, population mobility, and tobacco use in the study population were integrated into a Monte‐Carlo‐type model. Participation rates to radon screening programs were estimated from published data. According to the model used, approximately 10% of deaths due to lung cancer are attributable to residential radon exposure on a yearly basis in Quebec. In the long term, the promotion of a universal screening program would prevent less than one death/year on a province‐wide scale (0.8 case; IC 99%: –3.6 to 5.2 cases/year), for an overall reduction of 0.19% in radon‐related mortality. Reductions in mortality due to radon by (1) the implementation of a targeted screening program in the region with the highest concentrations, (2) the promotion of screening on a local basis with financial support, or (3) the realization of systematic investigations in primary and secondary schools would increase to 1%, 14%, and 16.4%, respectively, in the each of the populations targeted by these scenarios. Other than the battle against tobacco use, radon screening in public buildings thus currently appears as the most promising screening policy for reducing radon‐related lung cancer.     

Planners' Perspectives on Obstacles to Sustainable Urban Development: Implications for Transformative Planning Strategies

A major problem confronting planning is the gap between transformative proposals and enduring urban development trends. The paper interprets interviews with 62 planners involved in a sustainable urban development strategy in a large region focussed on Toronto, Canada. Surveyed planners were asked about the obstacles they encounter when attempting to modify prevailing urban development. Mentioned obstacles are consistent with expectations arising from three major perspectives on inertia: institutionalism, political economy and path dependence. Interviews also highlight the role of planners' practical knowledge in identifying and interpreting obstacles, and the existence of a consensus among respondents over sustainable urban development.     

Economic Modeling Triggers More Efficient Planning: An Experimental Justification

Consider a firm as an organization that needs to efficiently coordinate several specialized departments in an uncertain environment. Decision making involves collective planning sessions and decentralized operational processes. In this setting this paper explores the role of economic modeling through an experimental game. Results support the idea that economic modeling favors higher performance. Economic modeling facilitates the emergence of common knowledge and the decomposition of a group decision problem into individual decision problems that are meaningfully interrelated. This paper was presented at the Porquerolles Summer School on Cognitive Sciences, September 2001.     

To test or not to test: do workplace drug testing programs discourage employee drug use?

Workplace drug testing programs are often met with intense criticism. Despite resistance among labor and consumer groups and a lack of rigorous empirical evidence regarding effectiveness, drug testing programs have remained popular with employers throughout the 1990s and into the current century. The present study analyzed nationally representative data on over 15,000 US households to determine whether various types of workplace drug testing programs influenced the probability of drug use by workers. The study estimated several empirical specifications using both univariate and bivariate probit techniques. The specification tests favored the bivariate probit model over the univariate probit model. Estimated marginal effects of drug testing on any drug use were negative, significant, and relatively large, indicating that drug testing programs are achieving one of the desired effects. The results were similar when any drug use was replaced with chronic drug use in the models. These results have important policy implications regarding the effectiveness and economic viability of workplace anti-drug programs.