Understanding Cumulative Risk Perception from Judgments and Choices: An Application to Flood Risks

Catastrophic events, such as floods, earthquakes, hurricanes, and tsunamis, are rare, yet the cumulative risk of each event occurring at least once over an extended time period can be substantial. In this work, we assess the perception of cumulative flood risks, how those perceptions affect the choice of insurance, and whether perceptions and choices are influenced by cumulative risk information. We find that participants' cumulative risk judgments are well represented by a bimodal distribution, with a group that severely underestimates the risk and a group that moderately overestimates it. Individuals who underestimate cumulative risks make more risk‐seeking choices compared to those who overestimate cumulative risks. Providing explicit cumulative risk information for relevant time periods, as opposed to annual probabilities, is an inexpensive and effective way to improve both the perception of cumulative risk and the choices people make to protect against that risk.     

Peer Crowd Affiliation and Internalizing Distress in Childhood and Adolescence: A Longitudinal Follow‐Back Study

Concurrent and longitudinal associations between peer crowd affiliation and internalized distress were examined in a sample of 246 youth (148 girls, 98 boys). Children completed measures of depression, social anxiety, loneliness, and self‐esteem when they were in grades 4 to 6 (Time 1), and again 6 years later during adolescence (grades 10 – 12; Time 2). At Time 2, adolescents also reported their self‐concept and their identification with reputation‐based peer crowds, including Populars, Jocks, Brains, Burnouts, Non‐Conformists, and None/Average crowds. Results indicated that adolescents' report of peer crowd affiliation was concurrently associated with self‐concept and levels of internalizing distress. Follow‐back analyses of internalizing trajectories revealed that Populars/Jocks had experienced significant declines in internalizing distress across development, whereas Brains exhibited some increases in internalizing distress between childhood and adolescence.     

PATTERN RECOGNITION VIA ROBUST SMOOTHING WITH APPLICATION TO LASER DATA

Nowadays airborne laser scanning is used in many territorial studies, providing point data which may contain strong discontinuities. Motivated by the need to interpolate such data and preserve their edges, this paper considers robust nonparametric smoothers. These estimators, when implemented with bounded loss functions, have suitable jump‐preserving properties. Iterative algorithms are developed here, and are equivalent to nonlinear M‐smoothers, but have the advantage of resembling the linear Kernel regression. The selection of their coefficients is carried out by combining cross‐validation and robust‐tuning techniques. Two real case studies and a simulation experiment confirm the validity of the method; in particular, the performance in building recognition is excellent.     

A Bayesian Hierarchical Model for the Evaluation of a Website

Consider a website and the surfers visiting its pages. A typical issue of interest, for example while monitoring an advertising campaign, concerns whether a specific page has been designed successfully, i.e. is able to attract surfers or address them to other pages within the site. We assume that the surfing behaviour is fully described by the transition probabilities from one page to another, so that a clickstream (sequence of consecutively visited pages) can be viewed as a finite-state-space Markov chain. We then implement a variety of hierarchical prior distributions on the multivariate logits of the transition probabilities and define, for each page, a content effect and a link effect. The former measures the attractiveness of the page due to its contents, while the latter signals its ability to suggest further interesting links within the site. Moreover, we define an additional effect, representing overall page success, which incorporates both effects previously described. Using WinBUGS, we provide estimates and credible intervals for each of the above effects and rank pages accordingly.     

Predicting Children's Prosocial and Co‐operative Behavior from Their Temperamental Profiles: A Person‐centered Approach

The goal of this study was to examine how aspects of self‐regulation and negative emotionality predicted children's co‐operative and prosocial behavior concurrently and longitudinally using the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development. Mothers completed measures of children's temperamental proneness to negative emotionality and self‐regulation at 54 months. Teachers and parents completed measures of children's co‐operative and prosocial behavior at 54 months, first grade, and third grade. A latent profile analysis of the temperamental variables revealed four profiles of children: those high in regulation and low in negative emotionality, those moderate in regulation and moderate in negative emotionality, those low in regulation and high in negative emotionality, and finally those who were very low in regulation but high in anger emotionality. Generally, children with profiles that were high or moderate in terms of regulation and low or moderate in terms of negative emotionality were rated as the most prosocial and co‐operative. Children with profiles that were less well regulated and who were high in negative emotionality (particularly anger proneness) were rated as less co‐operative and prosocial by parents and teachers.     

Predictors of Antisocial and Prosocial Behavior in an Adolescent Sports Context

This study examined antisocial and prosocial behavior of N = 439 adolescent athletes between 14 and 17 years of age (67 teams). Multi‐level analyses showed that team membership explained 20 and 13 percent of the variance in antisocial and prosocial behavior in the sports context, respectively. The team effects suggest that aggregating antisocial or prosocial adolescents within teams may partially explain differences in antisocial and prosocial behavior among athletes in the sports context. A trend was found toward a relation between higher levels of moral reasoning within teams, and less antisocial behavior in the sports context. Favorable moral atmosphere was positively associated with more prosocial behavior in the sports context. Finally, supportive coach–athlete relationships were associated with both less antisocial and more prosocial behavior in the sports context.     

Bayesian Conditional Mean Estimation in Log‐Normal Linear Regression Models with Finite Quadratic Expected Loss

Log‐normal linear regression models are popular in many fields of research. Bayesian estimation of the conditional mean of the dependent variable is problematic as many choices of the prior for the variance (on the log‐scale) lead to posterior distributions with no finite moments. We propose a generalized inverse Gaussian prior for this variance and derive the conditions on the prior parameters that yield posterior distributions of the conditional mean of the dependent variable with finite moments up to a pre‐specified order. The conditions depend on one of the three parameters of the suggested prior; the other two have an influence on inferences for small and medium sample sizes. A second goal of this paper is to discuss how to choose these parameters according to different criteria including the optimization of frequentist properties of posterior means.     

Monetarist and Keynesian Policies for the Italian Labour Market: An Application of Interactive Control Methods

ABSTRACT: This paper aims at analysing the effects of monetarist and keynesian policies on Italian unemployment rate. Furthermore, it examines whether an optimal policy exists such that unemployment can be lowered without negatively affecting other policy targets (inflation or balance of trade). To answer these questions, interactive control methods are applied to a simple, intermediate-run, disequilibrium model of the Italian economy. A comparison between actual and optimal policies is also provided.     

CONGLOMERATES AND REGULATION

Conglomerates operating integrated productions in different regulated and unregulated sectors may benefit of scope economies. However, the precise size of these synergies is often unknown to both rival firms and regulators. We show that the conglomerate's private information on scope economies may negatively affect both the regulated and the unregulated sectors depending on the precise nature of competition (strategic substitutes or complements). We also unveil a novel effect of regulation that involves an informational externality to the conglomerate's rivals. Notwithstanding these complications, and independently of the nature of competition, we show that in our model it is desirable, as for welfare, to let the firm run integrated productions, unless diseconomies of scope may realize. (JEL L51, L43, L52)