Utility Subsidies as Social Transfers: An Empirical Evaluation of Targeting Performance

Subsidies to residential utility customers are important in‐kind transfer mechanisms in developing countries. Do these subsidies reach the poor? This article finds the average targeting performance of water and electricity subsidies to be similar to that of other social‐transfer mechanisms using the same targeting method. The most common form — a quantity‐based consumption subsidy aiming to subsidise low‐volume customers — is highly regressive. Many geographically‐targeted and most means‐tested utility subsidies are progressive, but still exclude many poor households. Connection subsidies are an attractive alternative in low coverage areas, but they will only reach the poor if utilities extend network access to poor households and if households choose to connect.     

The Repeatability of Uncertainty and Sensitivity Analyses for Complex Probabilistic Risk Assessments

The performance of a probabilistic risk assessment (PRA) for a nuclear power plant is a complex undertaking, involving the assembly of an accident frequency analysis, an accident progression analysis, a source term analysis, and a consequence analysis. Each of these analyses is, in itself, quite complex. Uncertainties enter into a PRA from each of these analyses. An important focus in recent PRAs has been to incorporate these uncertainties at each stage of the analysis, propagate the subsequent uncertainties through the entire analysis, and include uncertainty in the final results. Monte Carlo procedures based on Latin hypercube sampling provide one way to perform propagations of this type. In this paper, the results of two complete and independent Monte Carlo calculations for a recently completed PRA for a nuclear power plant are compared as a means of providing empirical evidence on the repeatability of uncertainty and sensitivity analyses for large-scale PRA calculations. These calculations use the same variables and analysis structure with two independently generated Latin hypercube samples. The results of the two calculations show a high degree of repeatability for the analysis of a very complex system.     

Power at the top

Theory and Society -     

Advances in the pharmacological treatment of pathological gambling

In the present paper we discuss the current status of drug treatment for pathological gambling and the scientific rationales underlying the various pharmacological approaches. Specifically, we summarize the treatment study results of serotonin reuptake inhibitors, mood stabilizers, opioid antagonists, and atypical antipsychotics in pathological gambling. We also discuss dosage strategies, the duration of treatment, issues surrounding medication compliance, and approaches to treatment-refractory pathological gambling, such as pharmacological and behavioral augmentation.     

One-year outcomes from the CASAWORKS for Families intervention for substance-abusing women on welfare

AIM: To evaluate the effectiveness of a multiservice intervention designed to move substance-abusing women on welfare to sobriety and self-sufficiency by addressing their substance abuse, domestic violence, employment, and basic needs. DESIGN: A field evaluation with repeated measures at 6 and 12 months on an intent-to-treat sample of 529 women conducted in 11 selected sites across the country. There were significant improvements shown in substance use and family and social functioning by the 6-month point, and additional improvements in employment by the 12-month point. By 12 months, more than 46% were abstinent from alcohol and other drugs, and 30% were employed at least part-time. There were only modest improvements shown in the medical and psychiatric status of these women. These preliminary findings suggest that site-level interagency coordination and program-level case management were associated with improvements in the targeted areas as predicted by the model. Future work will require a more closely specified, manual-guided form of the intervention plus the inclusion of control groups and cost measures to fully evaluate the cost benefits from the final form of the intervention.     

Separating Type-I Odd-Cycle Inequalities for a Binary-Encoded Edge-Coloring Formulation

In this note, we describe an efficient algorithm for separating a class of inequalities that includes the type-I odd-cycle inequalities for a binary-encoded edge-coloring formulation.     

Landmark estimation of transition probabilities in non-Markov multi-state models with covariates

Lifetime Data Analysis - In non-Markov multi-state models, the traditional Aalen–Johansen (AJ) estimator for state transition probabilities is generally not valid. An alternative, suggested...     

“You are your only limit”: Appropriations and valorizations of affect in university branding

This article considers the role of affect in university branding in a context of neoliberal higher education, by way of examining the semiotic landscape of the Singapore Management University concourse. Contemporary branding often involves stimulating stakeholder/audience investments of meaning and affect into the brand, thereby appropriating consumers’ affective labour for brand‐building and communications. Adopting a discourse‐analytic approach, I examine how linguistic, visual and spatial modalities are utilized to evoke and semiotize particular affective meanings and orientations in the emplaced discourse within the university's brand space. This discourse, which includes organizational branding discourse as well as more organic student‐generated texts, becomes part of the affective regime, helping to encourage and enjoin what is deemed to be normative affective sensibilities and practices in that context. Consequently, the article also considers the kinds of affective subjectivities that are valorized, and how stakeholder/student‐subjects are interpellated in a context of neoliberal‐oriented higher education.     

Impact of Number of Interactions,Different Interaction Patterns,and Human Inconsistencies on Some Hybrid Evolutionary Multiobjective Optimization Algorithms*

We investigate the impact of the number of human–computer interactions, different interaction patterns, and human inconsistencies in decision maker responses on the convergence of an interactive, evolutionary multiobjective algorithm recently developed by the authors. In our context “an interaction” means choosing the best and worst solutions among a sample of six solutions. By interaction patterns we refer to whether preference questioning is more front‐, center‐, rear‐, or edge‐loaded. As test problems we use two‐ to four‐objective knapsack problems, multicriteria scheduling problems, and multiobjective facility location problems. In the tests, two different preference functions are used to represent actual decision maker preferences, linear and Chebyshev. The results indicate that it is possible to obtain solutions that are very good or even nearly optimal with a reasonable number of interactions. The results also indicate that the algorithm is robust to minor inconsistencies in decision maker responses. There is also surprising robustness toward different patterns of interaction with the decision maker. The results are of interest to the evolutionary multiobjective (EMO) community actively developing hybrid interactive EMO approaches.