NIMBY, CLAMP, and the Location of New Nuclear-Related Facilities: U.S. National and 11 Site-Specific Surveys

Public and political opposition have made finding locations for new nuclear power plants, waste management, and nuclear research and development facilities a challenge for the U.S. government and the nuclear industry. U.S. government-owned properties that already have nuclear-related activities and commercial nuclear power generating stations are logical locations. Several studies and utility applications to the Nuclear Regulatory Commission suggest that concentrating locations at major plants (CLAMP) has become an implicit siting policy. We surveyed 2,101 people who lived within 50 miles of 11 existing major nuclear sites and 600 who lived elsewhere in the United States. Thirty-four percent favored CLAMP for new nuclear power plants, 52% for waste management facilities, and 50% for new nuclear laboratories. College educated, relatively affluent male whites were the strongest CLAMP supporters. They disproportionately trusted those responsible for the facilities and were not worried about existing nuclear facilities or other local environmental issues. Notably, they were concerned about continuing coal use. Not surprisingly, CLAMP proponents tended to be familiar with their existing local nuclear site. In short, likely CLAMP sites have a large and politically powerful core group to support a CLAMP policy. The challenge to proponents of nuclear technologies will be to sustain this support and expand the base among those who clearly are less connected and receptive to new nearby sites.     

Exploring Neglected Dimensions of Social Policy: The SDW, Fiscal Welfare and the Exemplar of Local Taxation in England

Titmuss's Social Division of Welfare (SDW) thesis is a vitally important but much neglected element of social policy analysis. This article seeks to explore the SDW, with a particular focus on fiscal welfare. Fiscal welfare has been described as forming a hidden welfare state, and while taxation is one of the main ways in which governments affect the lives of citizens, studies of welfare pay remarkably little attention to its impact. Fiscal welfare is examined by using, as an exemplar, local taxation in England, a subject that itself is neglected within social policy. Local taxation in England is of interest because it illustrates the impact of a system of taxation on different groups of citizens, and how this can operate to the benefit of rich over poor citizens. This is because the current system is highly regressive, meaning that those on low and middle incomes spend proportionately more of their income paying the tax than do those on high incomes. What is of further interest is how within the debate about reform of local taxation, concern with regressivity becomes obscured and ceases to be the focus of attention. We are thus provided with an example of how fiscal welfare remains a hidden issue. The article concludes by arguing that social policy analysis needs to move beyond the narrow confines of social welfare and develop a broader understanding of welfare, based on the SDW.     

Con Job: An Estimate of Ex‐Felon Voter Turnout Using Document‐Based Data*

Objective. Ex‐felon voter turnout was estimated for the first time using government records rather than statistical models. Statistical models have estimated that 25–35 percent of eligible ex‐felons would vote in federal elections. Methods. Six‐hundred‐sixty recently released ex‐felons in Erie County, NY, who would have been legally eligible to register and vote in 2004 or 2005, were compared with data from the Erie County Board of Elections to determine whether they registered and voted in either 2004 or 2005. Results. Five percent this population of ex‐felons voted in either 2004 or 2005. Conclusions. Single‐digit turnout among ex‐felons raises questions about the assumptions underlying statistical estimates, and it also suggests that elections would have to be very close for ex‐felons to have an impact on the results.     

Studying Complexity of Model-based Clustering

Cluster analysis is a popular statistics and computer science technique commonly used in various areas of research. In this article, we investigate factors that can influence clustering performance in the model-based clustering framework. The four factors considered are the level of overlap, number of clusters, number of dimensions, and sample size. Through a comprehensive simulation study, we investigate model-based clustering in different settings. As a measure of clustering performance, we employ three popular classification indices capable of reflecting the degree of agreement in two partitioning vectors, thus making the comparison between the true and estimated classification vectors possible. In addition to studying clustering complexity, the performance of the three classification measures is evaluated.     

Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence

Most existing reduced-form macroeconomic multivariate time series models employ elliptical disturbances, so that the forecast densities produced are symmetric. In this article, we use a copula model with asymmetric margins to produce forecast densities with the scope for severe departures from symmetry. Empirical and skew t distributions are employed for the margins, and a high-dimensional Gaussian copula is used to jointly capture cross-sectional and (multivariate) serial dependence. The copula parameter matrix is given by the correlation matrix of a latent stationary and Markov vector autoregression (VAR). We show that the likelihood can be evaluated efficiently using the unique partial correlations, and estimate the copula using Bayesian methods. We examine the forecasting performance of the model for four U.S. macroeconomic variables between 1975:Q1 and 2011:Q2 using quarterly real-time data. We find that the point and density forecasts from the copula model are competitive with those from a Bayesian VAR. During the recent recession the forecast densities exhibit substantial asymmetry, avoiding some of the pitfalls of the symmetric forecast densities from the Bayesian VAR. We show that the asymmetries in the predictive distributions of GDP growth and inflation are similar to those found in the probabilistic forecasts from the Survey of Professional Forecasters. Last, we find that unlike the linear VAR model, our fitted Gaussian copula models exhibit nonlinear dependencies between some macroeconomic variables. This article has online supplementary material.     

Cell Phone Survey Feasibility in The U.S.: Sampling and Calling Cell Numbers Versus Landline Numbers

In 2004, we conducted a nationwide dual frame survey of landlineand cell phone numbers to evaluate the feasibility of includingcell phone numbers in a random digit dial telephone survey.Households with both landline and cell phones were eligiblefor selection in both samples. This article describes our designand data collection methods; compares the results from the twosamples (with an emphasis on operational characteristics); andpresents the outcomes of two experimental manipulations designedto improve the cell phone response rate.     

Sampling Telephone Numbers and Adults, Interview Length, and Weighting in The California Health Interview Survey Cell Phone Pilot Study

This article describes several features included in a CaliforniaHealth Interview Survey cell phone pilot study that differ fromearlier cell phone surveys conducted in the United States. Onedifference is that the study used a screening design and onlyadults living in cell-only households were interviewed. Mostof the previous studies used dual frame designs. Another differencewas the development and implementation of a within-householdadult sampling procedure to cover adults when cell phones wereshared in the household. The study was also intended to determineif conducting a cell phone interview of the same scope and lengthas a regular telephone interview was feasible. Most previoussurveys were focused on cell phone topics and were shorter thanthe comparable landline surveys. We then explore some interestingproblems that arise in weighting a cell phone survey using ascreening design. We conclude with a discussion of planninga new cell phone survey in 2007 that incorporates findings fromthis study.     

Mitofsky Waksberg: Learning From The Past

Warren Mitofsky and Joseph Waksberg were two of the most influentialresearchers in telephone surveys and survey research methods.Their development of the Mitofsky–Waksberg method forrandom digit dialing sampling revolutionized telephone samplingand surveys. Jointly and separately, Waksberg and Mitofsky wereinstrumental in the development of many innovative methods andapplications. This article reviews some of their contributionsand discusses how their approaches to these problems may bea model for addressing issues that are being encountered currentlyin the United States in cell phone research.     

Operationalizing environmental indicators for physical activity in older adults

This qualitative study describes environmental supports and barriers to physical activity in an older adult sample drawn from low- and high-walkable neighborhoods. Thirty-seven individuals age 55 and over were recruited and answered open-ended survey questions, with a subsample invited back to partake in a semistructured interview. Content analysis identified categories and themes linking perceptions of neighborhood-environment characteristics to activity. Emerging categories and themes did not differ across neighborhood walkability, so results are presented for both groups combined. Infrastructure was the most common category identified to encourage activity, specifically, well-maintained sidewalks, bike paths or lanes, and traffic control. Other categories of land use, landscape, and aesthetics were reported. Poorly maintained or missing sidewalks, crosswalks, bike paths or lanes, and traffic safety were categories that discouraged activity. In conclusion, the information obtained is helpful in solidifying which environmental characteristics are important to measure as they relate to activity behavior in an older adult population.