The Different Faces of Islamic Terrorism

Islamic fundamentalist terrorism is not a monolithic phenomenon, as its protagonists have been multiple and varied actors. In spite of its diversity, the roots of this phenomenon can be found in a series of psychosocial factors, in the historical background itself of the Arab-Muslim countries, in the political, social and economic structure of these societies, and, finally, in the dominant ideological and religious superstructure in these cultures. It is necessary to analyze this entire series of variables, then, in order to interpret the role and the effectiveness of Islamic fundamentalist terrorism in the world today.     

Occupational Segregation and the Female–Male Wage Differentials: Evidence for Spain

Using matched employer–employee data from the Spanish labour market in 2010, we analyse the effects of industrial, establishment and occupational segregation on the gender wage differential, disaggregating the latter contribution by different groups of workers belonging to different occupational areas and responsibility levels. These workers are employed in 61 occupations within 26,492 establishments in 51 different industries. Since the matched employer–employee data exhibit a particular type of grouped structure, which contrasts the statistical properties of such data with the random sample case, we estimate the effects of each type of gender segregation on the wage gap using a robust specification. We find that the major part of the contribution of gender segregation is not explained by differences in the observable characteristics. Furthermore, the estimations show that the educational female advantage has helped to narrow the gender wage gap caused by occupational segregation within each establishment only for those groups of workers with the lowest educational requirements.     

Sleep and behavioral correlates of napping among young adults: a survey of first-year university students in Madrid, Spain

Objective: Between November 2002 and March 2003, the authors assessed the prevalence and correlates of napping among Spanish university students. Participants: The sample comprised 1,276 first-year university students; the mean age was 18.74 +/- 1.24 years, and 35.45% were men. Methods: The study was cross-sectional, and the students completed self-report, anonymous questionnaires provided during an in-class survey. Results: Almost half (44%) of the sample reported napping (90% did so after lunch for longer than 1 hour). Multiple logistic regression analysis showed that experiencing an irregular sleep-wakefulness pattern, having a morning school schedule, and being male were significant predictor variables of napping. Further significant outcome variables related to napping were having excessive daytime sleepiness, missing classes because of tiredness, better ability to concentrate later in the afternoon, and a perception of deeper nighttime sleep. Conclusions: Habitual napping is common among Spanish university students and associated with an irregular sleep-wakefulness pattern. Taking long postlunch naps seems to be used by students to cope with insufficient sleep and daytime sleepiness.     

Influence diagnostics on the coefficient of variation of elliptically contoured distributions

In this article, we study the behavior of the coefficient of variation (CV) of a random variable that follows a symmetric distribution in the real line. Specifically, we estimate this coefficient using the maximum-likelihood (ML) method. In addition, we provide asymptotic inference for this parameter, which allows us to contrast hypothesis and construct confidence intervals. Furthermore, we produce influence diagnostics to evaluate the sensitivity of the ML estimate of this coefficient when atypical data are present. Moreover, we illustrate the obtained results by using financial real data. Finally, we carry out a simulation study to detect the potential influence of atypical observations on the ML estimator of the CV of a symmetric distribution. The illustration and simulation demonstrate the robustness of the ML estimation of this coefficient.     

Dominance intensity measure within fuzzy weight oriented MAUT: An application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers' preferences, and imprecise weights are represented by trapezoidal fuzzy weights. The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights.     

A class of copulas with piecewise linear horizontal sections

We introduce the class of bivariate copulas with piecewise linear horizontal sections whose graph is composed, at most, of two segments. It is a wide class of copulas which contains some known copulas. We study several properties of the copulas in the new class concerning absolute continuity, singular components, measures of association, concordance ordering, dependence concepts and symmetry. Finally, we provide several examples.     

Durkheim,Competitive Interaction,and the “Best”: Explaining the State-Origins of U.S. Olympians

Abstract

Durkheim's theory of the causes of specialization in society proposes that the best performers should come from places with the most competitive interaction. This paper tests this proposition in an arena where interaction is highly competitive and where performance can be objectively measured, organized athletics in the United States. Four state-level indicators of competitive interaction (population, population density, average school size, and racial diversity) are used to predict the number of Olympic athletes developing in each state for the Olympic years 1956, 1968, 1980, and 1992. Net of controls for opportunities in athletics, results show that the number of Olympians developing in states increases exponentially with population, average high school size, and racial homogeneity, as Durkheimian theory suggests. These findings are robust even with controls for unmeasured state differences. I conclude that holding constant opportunity, states with more interaction among athletes produce more of the “best.”     

On projection-based tests for directional and compositional data

A new class of nonparametric tests, based on random projections, is proposed. They can be used for several null hypotheses of practical interest, including uniformity for spherical (directional) and compositional data, sphericity of the underlying distribution and homogeneity in two-sample problems on the sphere or the simplex. The proposed procedures have a number of advantages, mostly associated with their flexibility (for example, they also work to test “partial uniformity” in a subset of the sphere), computational simplicity and ease of application even in high-dimensional cases.     

Effect of measurement error and autocorrelation on the X¯ chart

Measurement error and autocorrelation often exist in quality control applications. Both have an adverse effect on the X¯ chart's performance. To counteract the undesired effect of autocorrelation, we build-up the samples with non-neighbouring items, according to the time they were produced. To counteract the undesired effect of measurement error, we measure the quality characteristic of each item of the sample several times. The chart's performance is assessed when multiple measurements are applied and the samples are built by taking one item from the production line and skipping one, two or more before selecting the next.     

Identification and Estimation of Stochastic Bargaining Models

Stochastic sequential bargaining models (Merlo and Wilson (1995, 1998)) have found wide applications in different fields including political economy and macroeconomics due to their flexibility in explaining delays in reaching an agreement. This paper presents new results in nonparametric identification and estimation of such models under different data scenarios.