Public Policy and the Displacement Effects of Casinos: A Case Study of Riverboat Gambling in Missouri

A critical issue in assessing the economic impact of casinos is whether gambling activity displaces consumer expenditure from conventional retail establishments. We test this hypothesis using industry-level, time series data for eleven counties in Missouri, a state that recently introduced riverboats. Our results are generally inconsistent with the displacement hypothesis. However, we do find evidence of substitution between gambling and other businesses in the entertainment and amusement sector. This conclusion lends credence to the view that gaming serves as a substitute for other forms of entertainment. Our results also imply that the search for displacement should probably be focused on activities that constitute the closest consumer substitutes. We conclude with a discussion of the policy implications for state regulation of this new source of revenue.     

Sequential design approaches for bioequivalence studies with crossover designs

The planning of bioequivalence (BE) studies, as for any clinical trial, requires a priori specification of an effect size for the determination of power and an assumption about the variance. The specified effect size may be overly optimistic, leading to an underpowered study. The assumed variance can be either too small or too large, leading, respectively, to studies that are underpowered or overly large. There has been much work in the clinical trials field on various types of sequential designs that include sample size reestimation after the trial is started, but these have seen only little use in BE studies. The purpose of this work was to validate at least one such method for crossover design BE studies. Specifically, we considered sample size reestimation for a two-stage trial based on the variance estimated from the first stage. We identified two methods based on Pocock's method for group sequential trials that met our requirement for at most negligible increase in type I error rate.     

Panel Tests of Okun's Law for Ten Industrial Countries

Okun's Law is one of the most enduring stylistic facts in macroeconomics. This article uses new developments in trend/cycle decomposition to test Okun's Law for a panel of ten industrial countries, finding that Okun's original estimate for the U.S. of three points of real GDP growth for each one percent reduction in the unemployment rate now averages just under two points of real GDP growth for the sample countries. Pooled estimates for Europe are smaller than estimates for the rest of the sample. Also, this article finds that omission of capital and labor inputs may have biased previous estimates.     

Generating multivariate continuous data via the notion of nearest neighbors

Taylor and Thompson [15] introduced a clever algorithm for simulating multivariate continuous data sets that resemble the original data. Their approach is predicated upon determining a few nearest neighbors of a given row of data through a statistical distance measure, and subsequently combining the observations by stochastic multipliers that are drawn from a uniform distribution to generate simulated data that essentially maintain the original data trends. The newly drawn values are assumed to come from the same underlying hypothetical process that governs the mechanism of how the data are formed. This technique is appealing in that no density estimation is required. We believe that this data-based simulation method has substantial potential in multivariate data generation due to the local nature of the generation scheme, which does not have strict specification requirements as in most other algorithms. In this work, we provide two R routines: one has a built-in simulator for finding the optimal number of nearest neighbors for any given data set, and the other generates pseudo-random data using this optimal number.     

Modeling Competing Infectious Pathogens from a Bayesian Perspective: Application to Influenza Studies with Incomplete Laboratory Results

In seasonal influenza epidemics, pathogens such as respiratory syncytial virus (RSV) often co-circulate with influenza and cause influenza-like illness (ILI) in human hosts. However, it is often impractical to test for each potential pathogen or to collect specimens for each observed ILI episode, making inference about influenza transmission difficult. In the setting of infectious diseases, missing outcomes impose a particular challenge because of the dependence among individuals. We propose a Bayesian competing-risk model for multiple co-circulating pathogens for inference on transmissibility and intervention efficacies under the assumption that missingness in the biological confirmation of the pathogen is ignorable. Simulation studies indicate a reasonable performance of the proposed model even if the number of potential pathogens is misspecified. They also show that a moderate amount of missing laboratory test results has only a small impact on inference about key parameters in the setting of close contact groups. Using the proposed model, we found that a non-pharmaceutical intervention is marginally protective against transmission of influenza A in a study conducted in elementary schools.     

DESIGNING INSPECTION STRATEGIES FOR UNCERTAIN ENVIRONMENTS

This paper considers the problems of designing inspection strategies for production systems terms in the presence of environmental uncertainty. The framework for determining information priorities to support inspection system planning is presented in the contaxt of a generic production system that encompasses the characteristics of many real-world serial production systems. The impact on the design decision of five key variables is considered: quality of producton processes, quality of inspection procedures, penalty cost for undetected defective units, relative cost of improving process vs. inspection, and shape of the cost functions for process and inspection enhancement. The framework for analysis involves varying factors over two or three orders of magnitude to determine optimal inspection strategies across a wide range of environments These results are used to compare design decisions made in the presence of environmental uncertainty using expected-opportunity-cost and minimization-of-maximum-opportunity-cost approaches. Design strategies are identified for situations ranging from complete lack of knowledge about the environment through increasing levels of information. Information-gathering priorities are established, and the impact on the design decision of this additional information is assayed.     

Staff perceptions of staff-family interactions in nursing homes

Each year thousands of older adults are admitted to nursing homes. Following admission, nursing home staff and family members must interact and communicate with each other. This study examined relationship and communication patterns between nursing home staff members and family members of nursing home residents, as part of a larger multi-method comparative case study. Here, we report on 6-month case studies of two nursing homes where in-depth interviews, shadowing experiences, and direct observations were completed. Staff members from both nursing homes described staff–family interactions as difficult, problematic and time consuming, yet identified strategies that when implemented consistently, influenced the staff–family interaction positively. Findings suggest explanatory processes in staff–family interactions, while pointing toward promising interventions.