The younger, the better? Age-related differences in academic performance at university

In this paper, we investigate differences in academic performance among students of different ages within the same cohorts using a unique database of students at Bocconi University. Our data allow to control for potential selection effects as well as for differences in cognitive ability, as measured by an attitudinal entry test. Contrary to most of the existing evidence for younger pupils, we document that at the undergraduate level, youngest students perform better compared with their oldest peers. This finding is only partly explained by differences in cognitive ability and rather seems to be associated with differences in social activities.     

Calibration estimation in dual-frame surveys

Survey statisticians make use of auxiliary information to improve estimates. One important example is calibration estimation, which constructs new weights that match benchmark constraints on auxiliary variables while remaining “close” to the design weights. Multiple-frame surveys are increasingly used by statistical agencies and private organizations to reduce sampling costs and/or avoid frame undercoverage errors. Several ways of combining estimates derived from such frames have been proposed elsewhere; in this paper, we extend the calibration paradigm, previously used for single-frame surveys, to calculate the total value of a variable of interest in a dual-frame survey. Calibration is a general tool that allows to include auxiliary information from two frames. It also incorporates, as a special case, certain dual-frame estimators that have been proposed previously. The theoretical properties of our class of estimators are derived and discussed, and simulation studies conducted to compare the efficiency of the procedure, using different sets of auxiliary variables. Finally, the proposed methodology is applied to real data obtained from the Barometer of Culture of Andalusia survey.     

Unspanned Macroeconomic Factors in the Yield Curve

In this article, we extract common factors from a cross-section of U.S. macro-variables and Treasury zero-coupon yields. We find that two macroeconomic factors have an important predictive content for government bond yields and excess returns. These factors are not spanned by the cross-section of yields and are well proxied by economic growth and real interest rates.     

Some maximum-indifference estimators for the slope of a univariate linear model

As known, the least-squares estimator of the slope of a univariate linear model sets to zero the covariance between the regression residuals and the values of the explanatory variable. To prevent the estimation process from being influenced by outliers, which can be theoretically modelled by a heavy-tailed distribution for the error term, one can substitute covariance with some robust measures of association, for example Kendall's tau in the popular Theil–Sen estimator. In a scarcely known Italian paper, Cifarelli [(1978), ‘La Stima del Coefficiente di Regressione Mediante l'Indice di Cograduazione di Gini’, Rivista di matematica per le scienze economiche e sociali, 1, 7–38. A translation into English is available at http://arxiv.org/abs/1411.4809 and will appear in Decisions in Economics and Finance] shows that a gain of efficiency can be obtained by using Gini's cograduation index instead of Kendall's tau. This paper introduces a new estimator, derived from another association measure recently proposed. Such a measure is strongly related to Gini's cograduation index, as they are both built to vanish in the general framework of indifference. The newly proposed estimator is shown to be unbiased and asymptotically normally distributed. Moreover, all considered estimators are compared via their asymptotic relative efficiency and a small simulation study. Finally, some indications about the performance of the considered estimators in the presence of contaminated normal data are provided.     

Prevalence and characteristics of sexual violence victimization among U.S. adults, 2001-2003

This article provides the most recent U.S. prevalence estimates of forced sex and unwanted sexual activity. Results of a national telephone survey conducted in 2001-2003 indicate that 1 in 59 U.S. adults (2.7 million women and 978,000 men) experienced unwanted sexual activity in the 12 months preceding the survey and that 1 in 15 U.S. adults (11.7 million women and 2.1 million men) have been forced to have sex during their lifetime. There were 60.4% of females and 69.2% of males who were 17 years old or younger at the time the first forced sex occurred. This study provides an update to the National Violence Against Women Survey with more recent national data. Findings suggest that victimization rates have remained consistent since the 1990s. These findings suggest that a continued effort toward primary prevention of sexual violence, particularly rape of children and adolescents, is needed.     

Indigenous data,indigenous methodologies and indigenous data sovereignty

The field of Indigenous methodologies has grown strongly since Tuhiwai Smith’s 1999 groundbreaking book Decolonizing Indigenous Methodologies. For the most part however, there has been a marked absence of quantitative methodologies with the methods aligned with Indigenous methodologies predominantly qualitative. This article proposes that the absence of an Indigenous presence from Indigenous data production has resulted in an overwhelming statistical narrative of deficit for dispossessed Indigenous peoples around the globe. Using the theoretical concept of Indigenous Lifeworlds this article builds on the core premises of Walter and Andersen’s 2013 book Indigenous quantitative methodologies. Arguing for a fundamental disturbance of the Western logics of statistical data the article details recent developments in the field including the emergence of the Indigenous Data Sovereignty movement. The article also explores Indigenous quantitative methodologies in practice using the case study of a Tribal Epidemiology Centre in New Mexico.     

Examining the Effects of a Service-Trained Facility Dog on Stress in Children Undergoing Forensic Interview for Allegations of Child Sexual Abuse

Disclosure of child sexual abuse can be a stressful experience for the child. Gaining a better understanding of how best to serve the child, while preserving the quality of their disclosure, is an ever-evolving process. The data to answer this question come from 51 children aged 4–16 (M = 9.1, SD = 3.5), who were referred to a child advocacy center in Virginia for a forensic interview (FI) following allegations of sexual abuse. A repeated measures design was conducted to examine how the presence of a service-trained facility dog (e.g. animal-assisted intervention (AAI) may serve as a mode of lowering stress levels in children during their FIs. Children were randomized to one of the two FI conditions: experimental condition (service-trained facility dog present-AAI) or control condition (service-trained facility dog not present- standard forensic interview). Stress biomarkers salivary cortisol, alpha-amylase, immunoglobulin A (IgA), heart rate, and blood pressure, and Immunoglobulin A were collected before and after the FI. Self-report data were also collected. Results supported a significant decrease in heart rate for those in the experimental condition (p = .0086) vs the control condition (p = .4986). Regression models revealed a significant decrease in systolic and diastolic blood pressure in the experimental condition (p = .03285) and (p = .04381), respectively. Statistically significant changes in alpha-amylase and IgA were also found in relation to disclosure and type of offense. The results of this study support the stress reducing effects of a service-trained facility dog for children undergoing FI for allegations of child sexual abuse.