A Diamond-Stiglitz approach to the demand for self-protection

The existing research concerning the relationship between risk aversion and prudence and the demand for self-protection assumes that the loss variable follows a Bernoulli distribution, and that changes in the level of self-protection are mean preserving. The analysis here replaces these two very strong conditions with ones which are more general. When doing this, the method of analysis is also significantly modified. This modification includes representing a change in the level of self-protection using the procedure developed by Diamond and Stiglitz (Journal of Economic Theory 8:337-360, 1974) for representing a change in risk. This alternate representation allows the existing findings to be generalized considerably, and also simplifies the analysis.     

Interplay between Friends' Aggression and Friendship Quality in the Development of Child Aggression during the Early School Years

The aim of this study was to investigate the unique and combined role of friendship quality and friends' aggression in regard to the persistence of young children's physical aggression from kindergarten to grade 2. The sample included 1555 children (808 girls) assessed annually using teacher ratings. Two theoretical perspectives (i.e., the social learning and the social bonding perspectives) served as frameworks to guide the analyses and interpret the results. In line with the social learning perspective, friends' aggression was related to a significant increase in children's physical aggression. However, in line with the social bonding perspective, good friendship quality played both a compensatory and a protective role, by, respectively, reducing children's initial level of physical aggression and by mitigating, albeit marginally, the associations between friends' and children's physical aggression. These results suggest that fostering a positive relationship between friends in the early school years may decrease physical aggression even if the friends are aggressive.     

Teacher-Based Racial Discrimination: The Role of Racial Pride and Religiosity Among African American and Caribbean Black Adolescents

This study explored the extent to which private regard and religiosity beliefs serve as protective factors for school bonding among African American and Caribbean black adolescents who experience racial discrimination in school. Findings are drawn from a nationally representative sample of (n = 810) African American and (n = 360) Caribbean black adolescents (52% girls) aged 13–17 (M_age = 15, SD = 1.42) years. Results suggest that perceiving racial discrimination from teachers was associated with lower levels of school bonding for African American and Caribbean black adolescents. For African American adolescents, perceiving more racial discrimination from teachers and reporting lower private regard beliefs was associated with less school bonding. The findings for Caribbean black adolescents revealed that endorsing moderate levels of religiosity and perceiving higher rates of teacher discrimination was associated with less school bonding. The developmental significance and implications for future research are discussed.     

Female Labor Supply,Human Capital,and Welfare Reform

We estimate a dynamic model of employment, human capital accumulation—including education, and savings for women in the United Kingdom, exploiting tax and benefit reforms, and use it to analyze the effects of welfare policy. We find substantial elasticities for labor supply and particularly for lone mothers. Returns to experience, which are important in determining the longer‐term effects of policy, increase with education, but experience mainly accumulates when in full‐time employment. Tax credits are welfare improving in the U.K., increase lone‐mother labor supply and marginally reduce educational attainment, but the employment effects do not extend beyond the period of eligibility. Marginal increases in tax credits improve welfare more than equally costly increases in income support or tax cuts.     

Signaling to Partially Informed Investors in the Newsvendor Model

We analyze a signaling game between the manager of a firm and an investor in the firm. The manager has private information about the firm's demand and cares about the short‐term stock price assigned by the investor. Previous research has shown that under continuous decision choices and the Intuitive Criterion refinement, the least‐cost separating equilibrium will result, in which a low‐quality firm chooses its optimal capacity and a high‐quality firm over‐invests in order to signal its quality to investors. We build on this research by showing the existence of pooling outcomes in which low‐quality firms over‐invest and high‐quality firms under‐invest so as to provide identical signals to investors. The pooling equilibrium is practically appealing because it yields a Pareto improvement compared to the least‐cost separating equilibrium. Distinguishing features of our analysis are that: (i) we allow the capacity decision to have either discrete or continuous support, and (ii) we allow beliefs to be refined based on either the Undefeated refinement or the Intuitive Criterion refinement. We find that the newsvendor model parameters impact the likelihood of a pooling outcome, and this impact changes in both sign and magnitude depending on which refinement is used.     

Further Beyond the Basic Background Check: Predicting Future Unethical Behavior

In this paper, we analyze the ethical issues of using honesty and integrity tests in employment screening. Our focus will be on the United States context: legal requirements related to applicant privacy differ in other countries, but we posit that our proposed balancing test is broadly applicable. We start by discussing why companies have ethical and legal obligations, based on a stakeholder analysis, to assess the integrity of potential employees. We then move to a consideration of how companies currently use background checks as a pre‐employment screening tool, noting their limitations. We then take up honesty and integrity testing, focusing particularly on the problems of false positives and due process. We offer a balancing test for the use of honesty and integrity testing that takes in three factors: (1) the potential harm posed by a dishonest employee in a particular job, (2) the linkage between the test and the assessment process, and (3) the accuracy and validity of the honesty and integrity test. We conclude with implications for practice and future research.     

Oppositional Girlhoods and the Challenge of Relational Politics

Over the last five years, scholars from a wide variety of disciplines have problematized the discourse of “adolescent female exceptionalism” (Switzer in Fem Theory 14(3):345–360, 2013, p. 4) popularized by the NIKE Foundation’s Girl Effect. Arriving at similar conclusions, scholars point to the artificial neocolonial divisions between ‘the West’ and ‘the rest’ of the world animated by an ‘invest in girls’ logic. This paper endeavors to move beyond the “oppositional girlhoods” (Bent in Sociol Stud Child Youth 16(1):3–20, 2013a, p. 7) bind of girl effects discourse to propose that differentially positioned and experienced girlhoods might be better understood as transnational, relational cultural formations. Drawing from our empirical research with girls in North America and Sub-Saharan Africa, we consider the implications of girls’ increasing global visibility as the ‘saviors of humanity’ from different geopolitical contexts. We then go further to suggest the oppositional girlhoods frame assumes reductive, apolitical, and ahistorical claims of divergence between girlhoods in the Global North and Global South “with highly unequal effects” (Gonick et al. in Girlhood Stud 2(3):1–9, 2009, p. 3). By countering the normative construction of global girlhoods as mutually exclusive forms of personhood and historical experience, our project authorizes a new understanding of girlhoods as mutually constituted and relationally contingent. It is from within this relational framework that we propose new directions for thinking about girlhoods transnationally.     

Nonparametric Estimation of the Number of Drug Users in Hong Kong Using Repeated Multiple Lists

We update a previous approach to the estimation of the size of an open population when there are multiple lists at each time point. Our motivation is 35 years of longitudinal data on the detection of drug users by the Central Registry of Drug Abuse in Hong Kong. We develop a two‐stage smoothing spline approach. This gives a flexible and easily implemented alternative to the previous method which was based on kernel smoothing. The new method retains the property of reducing the variability of the individual estimates at each time point. We evaluate the new method by means of a simulation study that includes an examination of the effects of variable selection. The new method is then applied to data collected by the Central Registry of Drug Abuse. The parameter estimates obtained are compared with the well known Jolly–Seber estimates based on single capture methods.     

A log rank type test in observational survival studies with stratified sampling

In randomized clinical trials, the log rank test is often used to test the null hypothesis of the equality of treatment-specific survival distributions. In observational studies, however, the ordinary log rank test is no longer guaranteed to be valid. In such studies we must be cautious about potential confounders; that is, the covariates that affect both the treatment assignment and the survival distribution. In this paper, two cases were considered: the first is when it is believed that all the potential confounders are captured in the primary database, and the second case where a substudy is conducted to capture additional confounding covariates. We generalize the augmented inverse probability weighted complete case estimators for treatment-specific survival distribution proposed in Bai et al. (Biometrics 69:830–839, 2013) and develop the log rank type test in both cases. The consistency and double robustness of the proposed test statistics are shown in simulation studies. These statistics are then applied to the data from the observational study that motivated this research.     

Boosting multi-state models

One important goal in multi-state modelling is to explore information about conditional transition-type-specific hazard rate functions by estimating influencing effects of explanatory variables. This may be performed using single transition-type-specific models if these covariate effects are assumed to be different across transition-types. To investigate whether this assumption holds or whether one of the effects is equal across several transition-types (cross-transition-type effect), a combined model has to be applied, for instance with the use of a stratified partial likelihood formulation. Here, prior knowledge about the underlying covariate effect mechanisms is often sparse, especially about ineffectivenesses of transition-type-specific or cross-transition-type effects. As a consequence, data-driven variable selection is an important task: a large number of estimable effects has to be taken into account if joint modelling of all transition-types is performed. A related but subsequent task is model choice: is an effect satisfactory estimated assuming linearity, or is the true underlying nature strongly deviating from linearity? This article introduces component-wise Functional Gradient Descent Boosting (short boosting) for multi-state models, an approach performing unsupervised variable selection and model choice simultaneously within a single estimation run. We demonstrate that features and advantages in the application of boosting introduced and illustrated in classical regression scenarios remain present in the transfer to multi-state models. As a consequence, boosting provides an effective means to answer questions about ineffectiveness and non-linearity of single transition-type-specific or cross-transition-type effects.