A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.     

The Determinants of Racial Disparities in Perceived Job Insecurity: A Test of Three Perspectives

Why do African Americans report higher levels of perceived job insecurity than whites? We analyze data from the 1996 and 1998 General Social Survey to test alternative predictions from the compositional, inclusive‐discrimination, and dispositional perspectives concerning the sources of the racial gap in perceived insecurity. Results from ordered probit regressions provide most support for the inclusive‐discrimination perspective, which maintains that employment practices associated with “modern racial prejudice” induce perceived insecurity on a widespread and generalized basis among African Americans. Accordingly, compared to whites, African Americans experience perceived insecurity net of human capital credentials and job/labor market characteristics. Additional analyses provide one qualification to these findings: dynamics associated with the inclusive‐discrimination perspective are more pronounced in the private sector than the public sector.     

The Impact of Items and Anchors on Parent–Child Reports of Problem Behavior

Research has repeatedly demonstrated that parent and child reports of child behavior and emotional functioning often do not agree in terms of symptom severity or even symptom presence. Given the potential clinical impact that discrepant reports may have on the therapeutic process, a significant amount of research has addressed the factors influencing this observed discrepancy. Traditionally, this research has evaluated the impact of demographic factors on mean differences and obtained correlation coefficients between parent and child reports. The current research improves upon previous research in this area in two ways. First, the current research uses parent and child measures with identical rather than similar items as is commonly found in previous research. Second, the current research moves beyond identifying demographic influences on discrepant reports by explaining observed discrepancies in terms of differences in parent and child perceptions of typical child behavior.David Carlston and Benjamin Ogles are affiliated with Department of Psychology, Ohio University, Athens, USA.Funding for this project was provided by the Ohio Department of Mental Health.     

Sweatshops and third world living standards: Are the jobs worth the sweat?

Many studies have shown that multinational firms pay more than domestic firms in Third World countries. Economists who criticize sweatshops have responded that multinational firms’ wage data do not address whether sweatshop jobs are above average because many of these jobs are with domestic subcontractors. We compare apparel industry wages and the wages of individual firms accused of being sweatshops to measures of the standard of living in Third World economies. We find that most sweatshop jobs provide their workers an above average standard of living. The authors thank Jeffery Hummel, Charles Murray, Larry Pratt, and Edward Stringham for helpful comments on earlier drafts. Financial support from the American Institute for Economic Research is gratefully acknowledged. The usual disclaimer applies.     

Batch sampling to improve power in a community trial. Experience from the Pawtucket Heart Health Program

Experiments involving large social units, such as schools, work sites, or whole cities, are commonly limited in statistical power because the number of randomized units is small, leaving few degrees of freedom for residual (between-unit) error. The authors describe a method for increasing residual degrees of freedom in a community experiment without substantially increasing cost or difficulty. In brief, they propose that the experimental units should be divided into random subsamples (batches). Batch sampling can improve statistical power if the community endpoint means are stable over time or if their temporal variation is comparable in period to the batch-sampling schedule. The authors demonstrate the theoretical advantages of the batch system and illustrate its use with data from the Pawtucket Heart Health Program, in which such a design was implemented.     

What Drives Citizen Participation in Political Gatherings in Modern South Africa? A Quantitative Analysis of Self-Reported Behaviour

Social Indicators Research - Community and public gatherings are an important component of political participation in sub-Saharan Africa. Formal and informal community meetings and rallies are...     

Point Estimates of Test Sensitivity and Specificity from Sample Means and Variances

In a wide variety of biomedical and clinical research studies, sample statistics from diagnostic marker measurements are presented as a means of distinguishing between two populations, such as with and without disease. Intuitively, a larger difference between the mean values of a marker for the two populations, and a smaller spread of values within each population, should lead to more reliable classification rules based on this marker. We formalize this intuitive notion by deriving practical, new, closed-form expressions for the sensitivity and specificity of three different discriminant tests defined in terms of the sample means and standard deviations of diagnostic marker measurements. The three discriminant tests evaluated are based, respectively, on the Euclidean distance and the Mahalanobis distance between means, and a likelihood ratio analysis. Expressions for the effects of measurement error are also presented. Our final expressions assume that the diagnostic markers follow independent normal distributions for the two populations, although it will be clear that other known distributions may be similarly analyzed. We then discuss applications drawn from the medical literature, although the formalism is clearly not restricted to that application.     

Household time activities,food waste,and diet quality: the impact of non-marginal changes due to COVID-19

Review of Economics of the Household - In early 2020, a novel coronavirus quickly spread across the globe. In response to the rapidly increasing number of confirmed U.S. cases, state and local...