The German East-West Mortality Difference: Two Crossovers Driven by Smoking

Before the fall of the Berlin Wall, mortality was considerably higher in the former East Germany than in West Germany. The gap narrowed rapidly after German reunification. The convergence was particularly strong for women, to the point that Eastern women aged 50–69 now have lower mortality despite lower incomes and worse overall living conditions. Prior research has shown that lower smoking rates among East German female cohorts born in the 1940s and 1950s were a major contributor to this crossover. However, after 1990, smoking behavior changed dramatically, with higher smoking intensity observed among women in the eastern part of Germany. We forecast the impact of this changing smoking behavior on East-West mortality differences and find that the higher smoking rates among younger East German cohorts will reverse their contemporary mortality advantage. Mortality forecasting methods that do not account for smoking would, perhaps misleadingly, forecast a growing mortality advantage for East German women. Experience from other countries shows that smoking can be effectively reduced by strict anti-smoking policies. Instead, East Germany is becoming an example warning of the consequences of weakening anti-smoking policies and changing behavioral norms.     

Stock investors’ preference for short-term vs. long-term bonuses

Bonuses in the finance sector may be based on too short time intervals for environmental and social factors to be taken into account in investment decisions. We report two experiments to investigate whether investors prefer short-term to long-term bonuses. In Experiment 1 employing 27 undergraduates, preferences were measured for four short-term certain bonuses, evenly distributed across a time interval, and one certain long-term bonus at the end of the time interval. A majority chose the short-term bonuses, and in order for the long-term bonus to be equally preferred it had to be about 40% higher than the four added short-term bonuses. Experiment 2 employing another 36 undergraduates introduced outcome uncertainty that more accurately reflects the choices stock investors face. The participants again choose between a long-term bonus and four distributed short-term bonuses. It was shown that uncertainty made more participants prefer the long-term bonus to the added short-term bonuses than when the outcome was certain. A smaller increase of the long-term bonus of about 20% was now required to make it equally attractive as the four added short-term bonuses.     

Can Psychosocial Intervention Improve Peer and Sibling Relations Among War‐affected Children? Impact and Mediating Analyses in a Randomized Controlled Trial

Social resources are considered important protectors in traumatic conditions, but few studies have analyzed their role in psychosocial interventions among war‐affected children. We examined (1) whether a psychosocial intervention (teaching recovery techniques, TRT) is effective in improving peer and sibling relations, and (2) whether these potentially improved relations mediate the intervention's impacts on children's mental health. Participants were 428 Palestinian children [10–13 (mean = 11.29, standard deviation SD = .68)‐year‐old girls (49.4 percent) and boys (50.6 percent)], who were cluster‐randomized into the TRT and wait‐list control groups. They reported the quality of peer (friendship and loneliness) and sibling (intimacy, warmth, conflict, and rivalry) relations, and posttraumatic stress, depressive and psychological distress symptoms, as well as psychosocial well‐being at baseline (T1), postintervention (T2), and six month follow‐up (T3). Results showed gender‐specific TRT intervention effects: Loneliness in peer relations reduced among boys and sibling rivalry reduced among girls. The TRT prevented the increase in sibling conflict that happened in the control group. The mediating hypothesis was partially substantiated for improved peer relations, and beneficial changes in sibling relations were generally associated with improved mental health.     

Too Scared or Too Capable? Why Do College Students Stay Away from the H1N1 Vaccine?

Although college students were among the populations that had the highest frequency of infection for H1N1 influenza, only 8% of them received H1N1 vaccine this past flu season nationwide. During the peak of this pandemic, information about H1N1 vaccine was widely available. However, knowledge test and behavioral data indicated that most college students were not equipped with basic facts about H1N1 and the H1N1 vaccine. To investigate socio‐psychological factors that might have deterred this high‐risk population from learning about and getting the H1N1 vaccine, this study tested the utility of a risk information seeking model in addressing this health communication problem. Data collected from an online survey of 371 college students showed that respondents seemed to overestimate how much they knew about the vaccine. Risk information seeking, however, positively influenced their intentions to get the vaccine. Results suggested that to communicate effectively to this population, it is important to emphasize the difference between perceived knowledge and actual knowledge, monitor emotional responses to potential risks, and promote getting flu vaccination as a socially desirable behavior.     

Modeling probability density through ultraspherical polynomial transformations

We present a method for fitting parametric probability density models using an integrated square error criterion on a continuum of weighted Lebesgue spaces formed by ultraspherical polynomials. This approach is inherently suitable for creating mixture model representations of complex distributions and allows fully autonomous cluster analysis of high-dimensional datasets. The method is also suitable for extremely large sets, allowing post facto model selection and analysis even in the absence of the original data. Furthermore, the fitting procedure only requires the parametric model to be pointwise evaluable, making it trivial to fit user-defined models through a generic algorithm.     

Conditional covariance penalties for mixed models

The prediction error for mixed models can have a conditional or a marginal perspective depending on the research focus. We introduce a novel conditional version of the optimism theorem for mixed models linking the conditional prediction error to covariance penalties for mixed models. Different possibilities for estimating these conditional covariance penalties are introduced. These are bootstrap methods, cross-validation, and a direct approach called Steinian. The behavior of the different estimation techniques is assessed in a simulation study for the binomial-, the t-, and the gamma distribution and for different kinds of prediction error. Furthermore, the impact of the estimation techniques on the prediction error is discussed based on an application to undernutrition in Zambia.     

The effect of accounting standards on Big Bath behavior

This paper investigates the influence of accounting standards on systematic earnings understatement. To isolate the effect of reporting regulations from those of other institutional drivers of earnings management, Holthausen (2003) proposes analyzing reporting practices in a country undergoing a transition in accounting standards. We respond to this call by analyzing earnings management practices of large German-listed companies before and after their transitions from German GAAP to IFRS. Specifically, we focus on Big Bath behavior following Chief Financial Officer turnovers between 1999 and 2006. Our findings provide evidence of the effect of accounting standards on the existence of this particular earnings understatement pattern. However, while we detect Big Bath behavior for our sample of German GAAP firms, we find no such indication for those firms reporting under IFRS. Controlling for alternative explanations such as self-selection bias does not change our findings. We conclude that accounting standards seem to have a considerable influence on earnings management behavior, independent of managers’ and auditors’ incentives.     

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.     

Evaluation of scheduling strategies for a dynamic job shop in a tool-shared,flexible manufacturing environment

A two-phase approach is used to examine the impact of job scheduling rules and tool selection policies for a dynamic job shop system in a tool-shared, flexible manufacturing environment. The first phase develops a generalized simulation model and analyses 'simple' job scheduling rules and tool selection policies under various operating scenarios. The results from this investigation are then used to develop and analyse various bi-criteria rules in the second phase of this study. The results show that the scheduling rules have the most significant impact on system performance, particularly at high shop load levels. Tool selection policies affect some of the performance measures, most notably, proportion of tardy jobs, to a lesser degree. Higher machine utilizations can be obtained at higher tool duplication levels but at the expense of increased tooling costs and lower tool utilization. The results also show that using different processing time distributions may have a significant impact on shop performance.