Scanner Data and the Treatment of Quality Change in Nonrevisable Price Indexes

The recently developed rolling year GEKS procedure makes maximum use of all matches in the data to construct nonrevisable price indexes that are approximately free from chain drift. A potential weakness is that unmatched items are ignored. In this article we use imputation Törnqvist price indexes as inputs into the rolling year GEKS procedure. These indexes account for quality changes by imputing the “missing prices” associated with new and disappearing items. Three imputation methods are discussed. The first method makes explicit imputations using a hedonic regression model which is estimated for each time period. The other two methods make implicit imputations; they are based on time dummy hedonic and time-product dummy regression models and are estimated on bilateral pooled data. We present empirical evidence for New Zealand from scanner data on eight consumer electronics products and find that accounting for quality change can make a substantial difference.     

On regression modelling with dummy variables versus separate regressions per group: Comment on Holgersson et al.

In a recent issue of this journal, Holgersson et al. [Dummy variables vs. category-wise models, J. Appl. Stat. 41(2) (2014), pp. 233–241, doi:10.1080/02664763.2013.838665] compared the use of dummy coding in regression analysis to the use of category-wise models (i.e. estimating separate regression models for each group) with respect to estimating and testing group differences in intercept and in slope. They presented three objections against the use of dummy variables in a single regression equation, which could be overcome by the category-wise approach. In this note, I first comment on each of these three objections and next draw attention to some other issues in comparing these two approaches. This commentary further clarifies the differences and similarities between dummy variable and category-wise approaches.     

Problem Gambling and Gaming Machine Density: Socio-spatial Analysis of Three Victorian Localities

This paper examines the debate about possible relationships between problem gambling and accessibility to electronic gaming machines (EGMs), in the context of the Victorian Government's policy that imposed a ‘cap’ on EGMs in disadvantaged communities. Using GIS (Geographical Information Systems), the spatial distribution of social disadvantage in three ‘capped’ localities was compared with the spatial distribution of gaming venues and patterns of concentrated EGM expenditure during 2001–2005, including seasonal trends. Research revealed different relationships between spatial and social categories in the study localities, indicating the need for more systematic local area analysis. This research raises questions about the limitations of conventional methodologies and regulatory strategies based on simple measures such as gaming machine density. We propose improvements to the methodology to better measure the changing level of local supply and demand for machine gaming.     

The Interplay Between Adolescents' Friendships and the Exchange of Help: A Longitudinal Multiplex Social Network Study

The aim of this study was to unravel the interrelatedness of friendship and help, and to examine the characteristics of friendship and help networks. The effects of mutual versus one‐sided help relations on friendship initiation and maintenance, and vice versa, were examined. Friendship and help networks were analyzed (N = 953 students; 41 classrooms; M_age = 12.7). The results illustrate that friendship and help networks show some similarities, but only partly overlap and have distinct characteristics. Longitudinal multiplex social network analyses showed that mutual help was important for the maintenance of friendship, but not for the initiation of friendship. Further, particularly mutual friendships provided a context in which help took place. Implications of these findings are discussed.     

Depression and Anxiety Symptoms in Female Adolescents: Relations with Parental Psychopathology and Parenting Behavior

Parental psychopathology and parenting behavior are known to be related to adolescents depression and anxiety, but unique roles of mothers and fathers are not clear. Our aim was to examine the relation of maternal and paternal psychopathology, emotional support, and respect for autonomy, and their interaction to depression and anxiety symptoms in adolescents. In total, 142 female adolescents participated, together with 138 mothers and 113 fathers. Data were analyzed using latent growth curve modeling. Paternal emotional support was negatively related to adolescent baseline level of depression and anxiety symptoms. Further, we found that there was a positive association between respect for autonomy and depression symptoms in adolescents for higher levels of paternal symptoms of psychological problems.     

Insight into Informant Discrepancies Regarding Psychosexual Functioning of Adolescents with and without Autism Spectrum Disorder

The private nature of psychosexual functioning leads adolescents and their parents to have different perspectives, which highlights studying parent–child informant discrepancies in this domain. We investigated informant discrepancy in psychosexual functioning, using the self‐report and parent report versions of the Teen Transition Inventory (TTI), of adolescents with autism spectrum disorder (ASD; 136 parent–child dyads) compared to adolescents from the general population (GP; 70 parent–child dyads). Significantly larger informant discrepancies exist in ASD dyads than GP dyads in most domains of psychosexual functioning, except for Body image, Sexual behavior, and Confidence in the future. It is important to use and pay attention to both informants, as discrepancies are relevant for both research and clinical practice regarding psychosexual functioning.     

Confidence intervals for extreme Pareto-type quantiles

In this paper, we revisit the construction of confidence intervals for extreme quantiles of Pareto-type distributions. A novel asymptotic pivotal quantity is proposed for these quantile estimators, which leads to new asymptotic confidence intervals that exhibit more accurate coverage probability. This pivotal quantity also allows for the construction of a saddle-point approximation, from which a second set of new confidence intervals follows. The small-sample properties and utility of these confidence intervals are studied using simulations and a case study from insurance.     

Nested exposure case-control sampling: a sampling scheme to analyze rare time-dependent exposures

For large cohort studies with rare outcomes, the nested case-control design only requires data collection of small subsets of the individuals at risk. These are typically randomly sampled at the observed event times and a weighted, stratified analysis takes over the role of the full cohort analysis. Motivated by observational studies on the impact of hospital-acquired infection on hospital stay outcome, we are interested in situations, where not necessarily the outcome is rare, but time-dependent exposure such as the occurrence of an adverse event or disease progression is. Using the counting process formulation of general nested case-control designs, we propose three sampling schemes where not all commonly observed outcomes need to be included in the analysis. Rather, inclusion probabilities may be time-dependent and may even depend on the past sampling and exposure history. A bootstrap analysis of a full cohort data set from hospital epidemiology allows us to investigate the practical utility of the proposed sampling schemes in comparison to a full cohort analysis and a too simple application of the nested case-control design, if the outcome is not rare.

     

An experimental investigation of risk sharing and adverse selection

Does adverse selection hamper the effectiveness of voluntary risk sharing? How do differences in risk profiles affect adverse selection? We experimentally investigate individuals’ willingness to share risks with others. Across treatments we vary how risk profiles differ between individuals. We find strong evidence for adverse selection if individuals’ risk profiles can be ranked according to first-order stochastic dominance and only little evidence for adverse selection if risk profiles can only be ranked according to mean-preserving spreads. We observe the same pattern also for anticipated adverse selection. These results suggest that the degree to which adverse selection erodes voluntary risk sharing arrangements crucially depends on the form of risk heterogeneity.