Factors Preventing Gridlock in Chilean Couples’ Relationships Based on the Discourse of Couples Therapists and Highly Adjusted Couples

The term gridlock describes the occurrence of rigid patterns in couples’ conflict. This study aimed to describe strategies of conflict resolution and gridlock prevention from the perspectives of couples and couple therapists. Participants were couple therapists and highly adjusted couples scored by the dyadic adjustment scale (DAS), distributed according to traditional and non‐traditional position in life and duration of relationships. Conflict gridlock scenarios were used to create video stimulus that were presented to participants. A qualitative methodology was used to analyse couples’ and therapists’ commentaries on the scenarios. Results showed differences in preventing conflict gridlock among sub‐groups of couples. Long‐term traditional couples focused on loyalty to a common project and value sacrificing to a higher good; long‐term non‐traditional couples prioritised caring and validating the bond in the relationship. Short‐term traditional couples focused on mutual love and the relief of hurt while short‐term non‐traditional couples supported the value of equity.     

Robust bootstrap forecast densities for GARCH returns and volatilities

Bootstrap procedures are useful to obtain forecast densities for both returns and volatilities in the context of generalized autoregressive conditional heteroscedasticity models. In this paper, we analyse the effect of additive outliers on the finite sample properties of these bootstrap densities and show that, when obtained using maximum likelihood estimates of the parameters and standard filters for the volatilities, they are badly affected with dramatic consequences on the estimation of Value-at-Risk. We propose constructing bootstrap densities for returns and volatilities using a robust parameter estimator based on variance targeting implemented together with an adequate modification of the volatility filter. We show that the performance of the proposed procedure is adequate when compared with available robust alternatives. The results are illustrated with both simulated and real data.     

Homicide Rates in a Cross‐Section of Countries: Evidence and Interpretations

This study uses a regression analysis to explore the cross‐country variation in homicide rates for a large sample of countries. It starts by identifying seven significant regional variables, to which traditional socioeconomic, cultural, and institutional variables are added and tested. The importance of institutions, culture, and other factors affecting homicide rates is discussed. One unexpected finding is a curious relationship between the level of education and homicide rates: while an increase in male education tends to reduce homicide rates, an increase in female education tends to increase homicides. Several possible interpretations for this phenomenon are proposed. The study points to relatively unexplored areas of research in order to better understand homicide variation around the world.     

Social and Economic Wellbeing in Europe and the Mediterranean Basin: Building an Enlarged Human Development Indicator

This paper calculates a human Wellbeing Composite Index (WCI) for 42 countries, belonging to the European Economic Space, North Africa and the Middle East, as an alternative to the shortcomings of other well-known measures of socio-economic development (i.e. Gross Domestic Product per head and Human Development Index). To attain this goal, different data envelopment analysis (DEA) models are used as an aggregation tool for seven selected socio-economic variables which correspond to the following wellbeing dimensions: income per capita, environmental burden of disease, income inequality, gender gap, education, life expectancy at birth and government effectiveness. The use of DEA allows avoiding the subjectivity that would be involved in the exogenous determination of weights for the variables included in WCI. The aim is to establish a complete ranking of all countries in the sample, using a three-step process, with the last step consisting in the use of a model that combines DEA and compromise programming, and permits to obtain a set of common weights for all countries in the analysis. The results highlight the distance that still separates Southern Mediterranean countries from the benchmark levels established by some European countries, and also point to the main weaknesses in individual countries’ performance. Nordic countries, plus Switzerland, top the list of best performers, while Mauritania, Libya and Syria appear at the bottom.     

Skew-normal alpha-power model

In this paper, authors study properties and inference for the newly introduced skew-normal alpha-power model, generalizing both, the power-normal and skew-normal models. Inference is approached via maximum likelihood. Fisher information matrix is derived and shown to be nonsingular at the whole parametric space. Special emphasis is placed on the special case of the power–skew-normal model. Studies with real data illustrate the fact that the model can be very useful in applications, being able to overfit less general models entertained in the literature.     

The generalized two-sided power distribution

The generalized standard two-sided power (GTSP) distribution was mentioned only in passing by Kotz and van Dorp Beyond Beta, Other Continuous Families of Distributions with Bounded Support and Applications, World Scientific Press, Singapore, 2004. In this paper, we shall further investigate this three-parameter distribution by presenting some novel properties and use its more general form to contrast the chronology of developments of various authors on the two-parameter TSP distribution since its initial introduction. GTSP distributions allow for J-shaped forms of its pdf, whereas TSP distributions are limited to U-shaped and unimodal forms. Hence, GTSP distributions possess the same three distributional shapes as the classical beta distributions. A novel method and algorithm for the indirect elicitation of the two-power parameters of the GTSP distribution is developed. We present a Project Evaluation Review Technique example that utilizes this algorithm and demonstrates the benefit of separate powers for the two branches of activity GTSP distributions for project completion time uncertainty estimation.     

A study of Bayesian local robustness with applications in actuarial statistics

Local or infinitesimal Bayesian robustness is a powerful tool to study the sensitivity of posterior magnitudes, which cannot be expressed in a simple manner. For these expressions, the global Bayesian robustness methodology does not seem adequate since the practitioner cannot avoid using inappropriate classes of prior distributions in order to make the model mathematically tractable. This situation occurs, for example, when we compute some types of premiums in actuarial statistics in order to fix the premium to be charged to an insurance policy. In this paper, analytical and simple expressions that allow us to study the sensitivity of premiums, which are usually used in automobile insurance are provided by using the local Bayesian robustness methodology. Some examples are examined by using real automobile claim insurance data.     

Working mothers’ decisions on childcare: the case of Spain

This paper aims to analyze household decisions regarding the childcare of young children. We present two specifications. The first one assumes a sequential decision process. Firstly, parents choose between paid or unpaid care and, secondly, those who opt for paid childcare must decide whether to take their children to a nursery or pre-school or employ somebody to care for them. The second specification is a multinomial Logit in which it is assumed that parents choose from three alternatives: unpaid care, paid care by a nanny, and center-based care. We apply our models to a sample of working mothers with children under three. The database used is the 2008–2010 Spanish Survey of Quality of Working Life (Encuesta de Calidad de Vida en el Trabajo). The results are in line with previous work: Parental education, family composition, income and the characteristics of the mother’s job are important factors in determining the type of childcare chosen for under-three-year-olds.     

Estimating utility functions using generalized maximum entropy

This paper estimates von Neumann and Morgenstern utility functions using the generalized maximum entropy (GME), applied to data obtained by utility elicitation methods. Given the statistical advantages of this approach, we provide a comparison of the performance of the GME estimator with ordinary least square (OLS) in a real data small sample setup. The results confirm the ones obtained for small samples through Monte Carlo simulations. The difference between the two estimators is small and it decreases as the width of the parameter support vector increases. Moreover, the GME estimator is more precise than the OLS one. Overall, the results suggest that GME is an interesting alternative to OLS in the estimation of utility functions when data are generated by utility elicitation methods.