Multinomial Selection in the Presence of Infinite Alternatives

We propose a new procedure for the multinomial selection problem to solve a real problem of any modern Air Force: the elaboration of better air-to-air tactics for Beyond Visual Range air-to-air combat that maximize its aircraft survival probability H(θ, ω), as well as enemy aircraft downing probability G(θ, ω). In this study, using a low-resolution simulator with generic parameters for the aircraft and missiles, we could increase an average success rate of 16.69% and 16.23% for H(θ, ω) and G(θ, ω), respectively, to an average success rate of 76.85% and 79.30%. We can assure with low probability of being wrong that the selected tactic has greater probability of yielding greater success rates in both H(θ, ω) and G(θ, ω) than any simulated tactic.     

Analysis of Deviance for Hypothesis Testing in Generalized Partially Linear Models

In this study, we develop nonparametric analysis of deviance tools for generalized partially linear models based on local polynomial fitting. Assuming a canonical link, we propose expressions for both local and global analysis of deviance, which admit an additivity property that reduces to analysis of variance decompositions in the Gaussian case. Chi-square tests based on integrated likelihood functions are proposed to formally test whether the nonparametric term is significant. Simulation results are shown to illustrate the proposed chi-square tests and to compare them with an existing procedure based on penalized splines. The methodology is applied to German Bundesbank Federal Reserve data.     

Die Bedeutung der Zinsschranke

The German Corporate Tax Reform Act of 2008 requires an adjustment of classic valuation concepts because it limits interest deduction from taxable income depending on the operating performance of the company. By using time- and state-contingent discount rates in a risk-neutral valuation with predetermined debt levels, a theoretically sound valuation result is obtained. However, a modified APV-concept which assumes deterministic debt over the planning horizon and constant leverage in the terminal value phase also yields consistent valuation results when two types of tax shields with different levels of risk are distinguished.     

A Polynomial Optimization Approach to Principal–Agent Problems

This paper presents a new method for the analysis of moral hazard principal–agent problems. The new approach avoids the stringent assumptions on the distribution of outcomes made by the classical first‐order approach and instead only requires the agent's expected utility to be a rational function of the action. This assumption allows for a reformulation of the agent's utility maximization problem as an equivalent system of equations and inequalities. This reformulation in turn transforms the principal's utility maximization problem into a nonlinear program. Under the additional assumptions that the principal's expected utility is a polynomial and the agent's expected utility is rational in the wage, the final nonlinear program can be solved to global optimality. The paper also shows how to first approximate expected utility functions that are not rational by polynomials, so that the polynomial optimization approach can be applied to compute an approximate solution to nonpolynomial problems. Finally, the paper demonstrates that the polynomial optimization approach extends to principal–agent models with multidimensional action sets.     

Experiences,Burdens, and Support Needs in Siblings of Girls and Women with Anorexia Nervosa: Results from a Qualitative Interview Study

For many years, siblings of women and girls suffering from anorexia have been regarded as “the forgotten kin,” as they have been overlooked by both researchers and clinicians. Therefore, the goal of this explorative study was to investigate siblings’ experiences, burdens, and support needs in a differentiated manner. Siblings (n = 16) of patients with an ICD-10 diagnosis “anorexia nervosa” (F 50.0) took part in a qualitative, in-depth interview study; the data were assessed using content analysis. The results of this study should be especially interesting for clinical social work. Using the findings, a variety of concrete recommendations for psycho-social practice can be made, for example regarding the inclusion of siblings in treatment settings, as well as specific support concepts for siblings of anorexic women and girls in different age groups.     

Deporting Fathers: Involuntary Transnational Families and Intent to Remigrate among Salvadoran Deportees

One‐fourth of deportees from the United States are parents of US‐citizen children. We do not know how separation from families affects remigration among deportees, who face high penalties given unlawful reentry. We examined how family separation affects intent to remigrate among Salvadoran deportees. The majority of deportees with children in the United States were also separated from their spouse, and the vast majority had US‐citizen children. Family separation was the single most important factor affecting intent to remigrate. We interpret these findings in light of immigration policy debates.     

CHAOTIC DYNAMICS IN CONTESTS

Under a myopic best‐reply dynamic, efforts in repeated contests may exhibit chaotic behavior. This may help explain, for example, why experimental data often show nonconvergence to one‐shot equilibrium efforts. (JEL C61, C72, D72, D74, D83)     

Birth Outcome Measures and Infant Mortality

Recent studies have proposed alternative birth outcome measures as means of assessing infant mortality risk; nevertheless, there hasn’t yet been an integrated analysis of these approaches. We review 14 strategies, including various combinations of birth weight, gestational age, fetal growth rate, and Apgar scores—as predictors of early neonatal, late neonatal, and postneonatal mortality, and infant mortality. Using the NCHS linked birth/infant death file for 2001, we construct multivariate logit models and assess the associations between each of the 14 key birth outcome measures and four mortality outcomes. We find that all evaluated birth outcome measures are strong predictors, but Apgar scores are the strongest among all models for all outcomes, independent of birth weight and gestational age. Apgar scores’ predictive power is stronger for Mexican-, white-, and female-infants than for black- and male-infants. Second, all birth outcome measures remain significantly associated with mortality, but their predictive power reduces drastically over time. These findings suggest a rule of thumb for predicting infant mortality odds: when available, Apgar scores should always be included along with birth weight (or LBW status) and gestational age. Additionally, these findings argue for the continued study of low birthweight, gestational age, and Apgar scores as independently salient health outcomes.