Reducing U.S. carbon dioxide emissions: an assessment of different instruments

The possibility that carbon dioxide emissions from fossil fuel use might lead to global warming has become a leading environmental concern. Many scientific and environmental organizations have called for immediate action to limit carbon dioxide production. For the most part, however, public debate has focused on a single policy instrument: a carbon tax applied to fossil fuels in proportion to their carbon content. We present a detailed model of the U.S. economy and use it to compare carbon taxes with two other instruments that could achieve the same reduction in carbon dioxide emissions: a tax on the energy content of fossil fuels (a BTU tax) and an ad valorem tax on fuel use. We find that carbon taxes can achieve a given reduction with the least overall effect on the economy, but with a large effect on coal mining. Energy taxes are fairly similar to carbon taxes but have slightly less impact on coal mining and slightly greater overall cost. In contrast, ad valorem taxes fall much more lightly on coal mining but have a much greater effect on the economy as a whole.     

Modelling map positional error to infer true feature location

The authors consider the issue of map positional error, or the difference between location as represented in a spatial database (i.e., a map) and the corresponding unobservable true location. They propose a fully model‐based approach that incorporates aspects of the map registration process commonly performed by users of geographic informations systems, including rubber‐sheeting. They explain how estimates of positional error can be obtained, hence estimates of true location. They show that with multiple maps of varying accuracy along with ground truthing data, suitable model averaging offers a strategy for using all of the maps to learn about true location.     

HOUSEHOLD CHANGE AND RURAL SCHOOL ENROLLMENT IN MALAWI AND KENYA

This study examines school enrollment in two sub-Saharan African nations, Malawi and Kenya. The article advances a refined family economy theoretical framework for understanding variations in school enrollment. It recasts family economy frameworks to consider not only how the household institution mediates a broad social change, but also how the family institution itself may be influenced by a macroinstitutional change. The findings suggest that household structural changes, as well as changes in parents' activities and perceptions, help explain enrollment practices in rural Malawi and Kenya.     

Immigrants' Language Skills and Visa Category1

This article is concerned with the determinants of English language proficiency among immigrants in a longitudinal survey for Australia. It focuses on both visa category and variables derived from an economic model of the determinants of destination‐language proficiency among immigrants. Skills‐tested and economic immigrants have the greatest proficiency shortly after immigration, followed by family‐based visa recipients, with refugees having the lowest proficiency. Other variables the same, these differences disappear by 3.5 years after immigration for speaking skills; and although they diminish, they persist longer for reading and writing skills. The variables generated from the model of destination‐language proficiency (such as schooling and age at migration) are, in part, predictions of visa category, but they are more important statistically for explaining proficiency.     

An alternative to farmer age as an indicator of life-cycle stage: The case for a farm family age index

In studies of farming, the age of the principal decision-maker (PDM) has been associated with numerous farm structural and managerial features and has been widely accepted as a good indicator of the influence of life-cycle factors on decision-making. As such, it has become an important aspect of many quantitative studies of agricultural change. However, contemporary studies of family farming demonstrate that the concept of a single PDM in family farms is becoming an anachronism as alternative enterprises, pluriactivity and the scale of family farms force more diffuse management/operating systems. This raises questions concerning whether the age of the PDM can still be taken as representative of farm structure, strategy or life-cycle stage? Using a study conducted in the Grampian Mountains region of Scotland in 2003 this note investigates the impact of using an alternative index—compiled by averaging the age of family members working on the farm. It suggests that PDM age is a relatively poor indicator of farm structural and managerial features compared to a family age index and calls for researchers to think about alternative approaches to measuring ‘age’ as an indicator.     

Liability in child welfare

Child welfare workers and agencies are vulnerable to lawsuits. Recent court rulings have more clearly defined the liability of workers. The distinguishing variable is custody. Children injured while in the custody of the state are entitled to sue for damages. Children injured by their parent, even if under the supervision of a child welfare agency, are not entitled to claim a violation of their 14th Amendment rights. These cases are reviewed and strategies designed to minimize vulnerability are offered.     

Rates of pathological gambling in publicly funded outpatient substance abuse treatment

Rates of problem or probable pathological gambling were assessed in substance abusers seeking outpatient treatment in a publicly funded outpatient substance abuse treatment program. The South Oaks Gambling Screen (SOGS) was administered to 467 consecutive admissions at three different sites. Problem gamblers comprised 6.2 percent of the total (n=29), and 4.5 percent scored as probable pathological gamblers (n=21). These rates are two and one-half times greater than would be expected according to a recent state survey using the SOGS. Implications for assessment and treatment of problem gambling are discussed.The author expresses his appreciation to John Ramsay and the staff of Epoch Counseling Center for data collection; to Les Franklin for computational analysis; and Dr. Rachel Volberg for providing supplemental data from her Maryland State Gambling Survey.