Lottery pricing under time pressure

This article investigates how subjects determine minimum selling prices for lotteries. We design an experiment where subjects have at every moment an incentive to state their minimum selling price and to adjust the price, if they believe that the price that they stated initially was not optimal. We observe frequent and sizeable price adjustments. We find that random pricing models cannot explain the observed price patterns. We show that earlier prices contain information about future price adjustments. We propose a model of Stochastic Pricing that offers an intuitive explanation for these price adjustment patterns.     

Financing social security out of contributions: About origins,present discussions and prospects of a success story

In writing the overture to an issue on contribution financed social security one cannot but speak of Bismarck; it must also address Beveridge who saw contributions, although in their design and role clearly differently from Bismarck, as one core revenue tool to finance his vision. Beveridge attributed to the private financial sector a prominent role in securing people against the negative effects on income of shocks and crises, while Bismarck did not. Beveridge's concept, when first published, had, and still has today, the most attractive charm of rigorously satisfying peoples' striving for equitable and inclusive societal solutions. Bismarck's concept intrinsically offers income security only to those who contribute, while the level of protection depends on the level of contributions paid (with the exception of health insurance). In reality, both concepts, where implemented, had to face the realities of socio‐economic and political developments: Beveridge's vision was achieved in respect of access to health services where his proposal, in its predominantly tax‐financed version, has since turned into a worldwide blueprint for health schemes; in its other components, it was not resilient enough to achieve the intended standards and now is replete with means‐tested (poor relief) elements. Bismarck's scheme has proven its potential to achieve “universality”, not necessarily by theoretical design but as a matter of fact, i.e. covering people from cradle to grave (like Beveridgean schemes). With globalization, schemes of both origins have had to face massive neoliberal attacks over the last three decades. Which of the approaches is best able to survive must be left an open question: in the current worldwide context of rapid change, both have weak and strong points, and whether a symbiosis of the two offers the answer to future challenges remains to be seen.     

Estimating the density of a possibly missing response variable in nonlinear regression

This paper considers linear and nonlinear regression with a response variable that is allowed to be “missing at random”. The only structural assumptions on the distribution of the variables are that the errors have mean zero and are independent of the covariates. The independence assumption is important. It enables us to construct an estimator for the response density that uses all the observed data, in contrast to the usual local smoothing techniques, and which therefore permits a faster rate of convergence. The idea is to write the response density as a convolution integral which can be estimated by an empirical version, with a weighted residual-based kernel estimator plugged in for the error density. For an appropriate class of regression functions, and a suitably chosen bandwidth, this estimator is consistent and converges with the optimal parametric rate n^1/2. Moreover, the estimator is proved to be efficient (in the sense of Hájek and Le Cam) if an efficient estimator is used for the regression parameter.     

Missing values: sparse inverse covariance estimation and?an?extension to sparse regression

We propose an ℓ ₁-regularized likelihood method for estimating the inverse covariance matrix in the high-dimensional multivariate normal model in presence of missing data. Our method is based on the assumption that the data are missing at random (MAR) which entails also the completely missing at random case. The implementation of the method is non-trivial as the observed negative log-likelihood generally is a complicated and non-convex function. We propose an efficient EM algorithm for optimization with provable numerical convergence properties. Furthermore, we extend the methodology to handle missing values in a sparse regression context. We demonstrate both methods on simulated and real data.     

Design of computer experiments: space filling and beyond

When setting up a computer experiment, it has become a standard practice to select the inputs spread out uniformly across the available space. These so-called space-filling designs are now ubiquitous in corresponding publications and conferences. The statistical folklore is that such designs have superior properties when it comes to prediction and estimation of emulator functions. In this paper we want to review the circumstances under which this superiority holds, provide some new arguments and clarify the motives to go beyond space-filling. An overview over the state of the art of space-filling is introducing and complementing these results.     

Development of Science Anxiety Scale for Primary School Students

The principal aim of the study is to develop a new scale Science Anxiety Scale and to examine its the psychometric properties and construct validity of the Science Anxiety Scale in a sample of 797 primary school students. Exploratory factor analysis was applied and found to have a two-dimensional structure. Confirmatory factor analyses provide evidence for a solid two-dimension structure reflecting the theorized construct: personal and environmental. Also, for convergent validity, item reliability, construct reliability and average variance values were calculated and it was found that item reliability and construct reliability values generally provided the required criteria. The average variance extracted value had a value below the criteria value for both sub-dimensions. Discriminant validity was above the criteria value in all dimensions. The reliability of the Science Anxiety Scale scales appeared to be satisfactory, with good internal consistency. The Science Anxiety Scale was found to be reliable and valid for the Turkish primary student context with a few exceptions.     

Individual- and Neighbourhood-Level Indicators of Subjective Well-Being in a Small and Poor Eastern Cape Township: The Effect of Health,Social Capital,Marital Status,and Income

Our study used multilevel regression analysis to identify individual- and neighbourhood-level factors that determine individual-level subjective well-being in Rhini, a deprived suburb of Grahamstown in the Eastern Cape province of South Africa. The Townsend index and Gini coefficient were used to investigate whether contextual neighbourhood-level differences in socioeconomic status determined individual-level subjective well-being. Crime experience, health status, social capital, and demographic variables were assessed at the individual level. The indicators of subjective well-being were estimated with a two-level random-intercepts and fixed slopes model. Social capital, health and marital status (all p < .001), followed by income level (p < .01) and the Townsend score (p < .05) were significantly related to individual-level subjective well-being outcomes. Our findings showed that individual-level subjective well-being is influenced by neighbourhood-level socioeconomic status as measured by the Townsend deprivation score. Individuals reported higher levels of subjective well-being in less deprived neighbourhoods. Here we wish to highlight the role of context for subjective well-being, and to suggest that subjective well-being outcomes may also be defined in ecological terms. We hope the findings are useful for implementing programs and interventions designed to achieve greater subjective well-being for people living in deprived areas.     

Lost in data translation: A critical review of datasets on refugees

Quantitative data are the backbone of the international refugee regime. Academic researchers and international organizations have been drawing attention to the problems of refugee data that obscure refugee vulnerabilities. Despite these efforts, the limitations of quantitative refugee data, particularly with regard to gendered aspects of refugee vulnerabilities, have often been overlooked. This article aims to address this issue by examining the major limitations of quantitative refugee data. It focuses on the question of “What are the major limitations of quantitative refugee data regarding gendered aspects of refugee vulnerabilities?” By conducting a systematic review of 67 datasets from international organizations, nation-states, and independent data collectors, it argues that there are five fundamental problems with the data: (1) lack of disaggregation, (2) lack of cross-tabulation and inability to harmonize datasets, (3) inconsistent periodization frequency, (4) lack of sex and gender diversity measurement, and (5) survivor bias. This article highlights the importance of critically analysing the data that informs theories and decisions regarding refugee vulnerabilities.     

Violence,life aspirations and displacement trajectories in civil war

Drawing on qualitative data from the civil wars in Syria and Libya since 2011, this paper seeks to build a better understanding of immobility and of displacement trajectories within conflict countries and towards neighbouring countries. The paper shows that different types of violent experiences—personal threats, generalized violence, an increasing hopelessness relating to the absence of violence in the future—trigger different exit movements across internal and external borders. Second, the analysis demonstrates that migration decisions in civil war contexts are complex processes with people balancing between strategies of how to avoid violence with strategies of how to realize broader life aspirations related to family, love, work and political change. Life aspirations often play a more important role once people move out of a situation of immediate danger and in later phases of trajectories and influence (im)mobility patterns in three different directions: stay, move (on) or return. Life aspirations, especially related to political change, outweigh perceptions of violence in some cases. Financial vulnerability can force people to stay in or return to violent contexts.     

Linking maternal psychopathology to children's excessive crying and sleeping problems in a large representative German sample—The mediating role of social isolation and bonding difficulties

Attaining self-regulation is a major developmental task in infancy, in which many children show transient difficulties. Persistent, clinically relevant difficulties in self-regulation include excessive crying or sleeping disorders. Many families with affected children are burdened with multiple psychosocial risk. This suggests that regulatory problems are best conceptualized as the maladaptive interplay of overly burdened parents and a dysfunctional parent–child interaction. The current study examines whether social isolation and bonding difficulties function as mediating mechanisms linking maternal psychopathology to (1) children's excessive crying and (2) sleeping problems. The sample comprised N = 6598 mothers (M = 31.51 years) of children between zero to three years of age (M = 14.08 months, 50.1% girls). In addition to socio demographic data, the written questionnaire included information on maternal depression/anxiety, isolation, bonding, and children's regulatory problems. Hypotheses were tested with a mediation model controlling for psychosocial risk and child characteristics. As expected, maternal symptoms of depression/anxiety were linked to infants‘ excessive crying and sleeping problems. Social isolation and bonding difficulties mediated this association for excessive crying as well as for sleeping problems, but social isolation was a single mediator for sleeping problems only. The findings provide important insights in the mediating pathways linking maternal psychopathology to children's regulatory problems.