Trends in Child Health Insurance Coverage: A Local Perspective

Background: Over the past decade, the percentage of Americans with access to employer-sponsored insurance (ESI) has declined. Dependents, specifically children, are the most likely to bear the burden of lost coverage. Objectives: The objectives of this study were to 1) describe trends in children’s health insurance taking into account the heterogeneity across different sub-populations and 2) assess the associations between individual, local (offers of ESI), and supply side (proximity to safety net hospitals) characteristics and children’s health insurance. Methods: We analyzed locally collected survey data for children living in the 12 counties of greater Houston, Texas (years 2003, 2006, 2008, 2011). For each year, telephone interviews were conducted with caregivers through random digit dialing. Among households with at least one employed caregiver (N=2,508), we performed an adjusted multinomial logistic regression analysis to evaluate the odds of being publicly insured or uninsured, with the option for ESI and proximity to a public hospital as primary independent variables. Results: Low-income and racial/ethnic minority children experienced the largest increases in coverage through public insurance. Children in households without the option for ESI had higher odds (Odds ratio 10.87, 95% confidence interval 7.31-16.17) of being publicly insured or uninsured (Odds ratio 9.50, 95% confidence interval 6.14-14.70) compared to those in households with the option for ESI. Proximity to a public hospital was not associated with being uninsured. Conclusions: As the availability of ESI has declined, public insurance has acted as a safety net for low-income and minority children. While access to free care plays an important role, it may not substitute for insurance coverage

1954: Abilene Christian College Bible Lectures - Full Text

Preface The 1954 Abilene Christian College Lectureship was one of the best attended and most successful in the history of the school. Considerable interest was manifested in the timely theme, “Overcoming Dangerous Tendencies,” and in the two special topics, “Ways and Means of Doing Mission Work,” and “Caring For Widows and Orphans.” The reports from the mission fields were highly stimulating, and all in all, the speeches were unusually high caliber. The Panel Discussions were also on timely subjects and well presented. They received a warm response, as did also the thirty classes that were conducted each day. These classes were taught by persons expert in their particular fields, and covered a wide range of interests to the faithful, working Christian. We at Abilene Christian College predict for this book of Lectures a wide and hearty reception, and believe that its reading will issue in profit to the individual and to the church at large. J. D. Thomas Lectureship Directo

A New Approach for Capturing and Potraying the Competitive Structure of a Market: An Application To The Bush-Kerry-Nader Presidential Contest

This short note introduces a new methodology for capturing and portraying the competitive structure of a market. Using the current Presidential contest as the context, the methodology first describes a simple and efficient data collection approach that generates the data necessary for applying Tversky’s Elimination-By-Aspects Model (1972a, 1972b) at the market level. Then, relying on recently published mathematical results (Batsell, Polking, Cramer, and Miller, 2003) the method shows the complete decomposition of the competitive structure of a market based on the elimination model. Also introduced is a new way to graphically portray the competitive structure of a market in the form of a choice-based perceptual map, which has several desirable properties.Competitive Structures, Choice Models, Political Elections, Elimination Models, Presidential Elections

A New Class of Market Share Models

Applications of market share models which (implicitly) rely on Luce's choice axiom have been widely criticized because they cannot account for the effects of differential product substitutability and product dominance. Three types of choice models—Tversky's Elimination-By-Aspects model, Tree Models, and Generalized PROBIT—have been offered as solutions to the problems identified with the Luce model, but they each suffer from limitations which have prevented their widespread application in marketing contexts. Tversky's elegant EBA model has not been widely used because it requires a large number of parameters and no special-purpose parameter estimation software has yet emerged. Tree models have been offered as more parsimonious special cases of EBA, but they are more restrictive in that they presume: (1) that products, and the process of choosing from among them, can be characterized in terms of hierarchical, attribute-based trees; and (2) that the aspects governing choice are well-known. Generalized PROBIT can paramorphically handle the problems with the Luce model, but parameter estimation software has proved problematic because it cannot guarantee a globally optimum solution. This paper proposes a new class of market share models. Rather than model the choice process explicitly, the new models simply scale the effects competing products have on each other's market share. These competitive effects are scaled in the context of a class of market-share models which: (1) do not assume a tree-like structure for the competing products; (2) do not presume any a priori knowledge about the attributes governing choice; (3) are characterized in terms of parameters that can be estimated using ordinary least-squares; and (4) provide clear managerial insight into the sources of competition. The paper begins with a brief review of previous work. Following the review, the paper offers a theorem and proof which guarantees the existence of the new class of models. The empirical validity and strategic utility of the models are demonstrated using two separate sets of data.

Coherent probability from incoherent judgment

People often have knowledge about the chances of events but are unable to express their knowledge in the form of coherent probabilities. This study proposed to correct incoherent judgment via an optimization procedure that seeks the (coherent) probability distribution nearest to a judge's estimates of chance. This method was applied to the chances of simple and complex meteorological events, as estimated by college undergraduates. No judge responded coherently, but the optimization method found close (coherent) approximations to their estimates. Moreover, the approximations were reliably more accurate than the original estimates, as measured by the quadratic scoring rule. Methods for correcting incoherence facilitate the analysis of expected utility and allow human judgment to be more easily exploited in the construction of expert systems. Suppose you think the probability that the Internet will expand next year is.90. Suppose you also think the probability that the Internet will expand and PC makers will be profitable is.91. Then you have assigned a greater chance to a conjunction rather than to one of its conjuncts; hence, your judgments are incoherent. You may, nonetheless, prove to be more insightful than someone wit