Bounds on expected generalized order statistics

We establish the upper nonpositive and all the lower bounds on the expectations of generalized order statistics based on a given distribution function with the finite mean and central absolute moment of a fixed order. We also describe the distributions for which the bounds are attained. The methods of deriving the lower nonpositive (upper nonnegative) and lower nonnegative (upper nonpositive) bounds are totally different. The first one, the greatest convex minorant method is the combination of the Moriguti and well-known Hölder inequalities and the latter one is based on the maximization of some norm on the properly chosen convex set. The paper completes the results of Cramer et al. [Evaluations of expected generalized order statistics in various scale units. Appl Math. 2002;29:285–295].     

Random translation of discrete order statistics

We investigate the existence and uniqueness of a discrete parent distribution supported on the integers whose order statistics are related by a random translation. We also provide some examples using the constructive method that we propose.     

Importance of the prior mass for agreement between frequentist and Bayesian approaches in the two-sided test

We study distributional properties of generalized order statistics (gos) related by a random shift or scaling scheme in the continuous and discrete case, respectively. In the continuous case, we obtain new characterizations of distributions relating non-neighbouring gos extending some results given in the literature for the neighbouring cases. On the other hand, in the discrete case, we investigate the existence and uniqueness of a discrete parent distribution supported on the integers whose gos are related by a random translation.     

On the recoding of continuous and bounded indexes to a binomial form: an application to quality-of-life scores

The statistical analysis of patient-reported outcomes (PROs) as endpoints has shown to be of great practical relevance. The resulting scores or indexes from the questionnaires used to measure PROs could be treated as continuous or ordinal. The goal of this study is to propose and evaluate a recoding process of the scores, so that they can be treated as binomial outcomes and, therefore, analyzed using logistic regression with random effects. The general methodology of recoding is based on the observable values of the scores. In order to obtain an optimal recoding, the evaluation of the recoding method is tested for different values of the parameters of the binomial distribution and different probability distributions of the random effects. We illustrate, evaluate and validate the proposed method of recoding with the Short Form-36 (SF-36) Survey and real data. The optimal recoding approach is very useful and flexible. Moreover, it has a natural interpretation, not only for ordinal scores, but also for questionnaires with many dimensions and different profiles, where a common method of analysis is desired, such as the SF-36.     

Functional principal component analysis for the explorative analysis of multisite–multivariate air pollution time series with long gaps

The knowledge of the urban air quality represents the first step to face air pollution issues. For the last decades many cities can rely on a network of monitoring stations recording concentration values for the main pollutants. This paper focuses on functional principal component analysis (FPCA) to investigate multiple pollutant datasets measured over time at multiple sites within a given urban area. Our purpose is to extend what has been proposed in the literature to data that are multisite and multivariate at the same time. The approach results to be effective to highlight some relevant statistical features of the time series, giving the opportunity to identify significant pollutants and to know the evolution of their variability along time. The paper also deals with missing value issue. As it is known, very long gap sequences can often occur in air quality datasets, due to long time failures not easily solvable or to data coming from a mobile monitoring station. In the considered dataset, large and continuous gaps are imputed by empirical orthogonal function procedure, after denoising raw data by functional data analysis and before performing FPCA, in order to further improve the reconstruction.     

The role of human and social board capital in driving CSR reporting

The objective of this paper is to analyze the effect of the professional, technical and relational background (human and social capital) of outside directors on promoting firm CSR disclosure. Following the Hillman et al. (2000) taxonomy of board members, we classify outside directors as business experts, support specialists and community influential, and examine whether business and technical expertise or political ties in the boardroom affect CSR disclosure.This study confirms that not all outside directors are equally effective in improving CSR disclosure and that only certain kinds of outside directors, those classified as support specialists, help promote it. On the other hand, our findings also show that directors with previous experience as politicians affect CSR disclosure negatively, probably due to their interests in safeguarding their reputation within the company, in avoiding public scrutiny and in protecting their political connections. In addition, our set of analysis with interaction effects reveals that powerful CEOs have the incentive to promote CSR-related strategies and to convince business experts and support specialist directors to enhance profitable sustainability strategies and transparency in CSR disclosure. Nevertheless, the powerful CEO effect is not enough to compensate the negative role of political directors on CSR reporting. Therefore, this paper supports the theories in favor of analyzing the multiple configurations of corporate governance mechanisms by adopting a holistic approach, and the need to combine these configurations in order to analyze their impact on CSR behavior.     

Max‐infinitely divisible models and inference for spatial extremes

For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max‐stable models are inadequate to capture the rate of joint tail decay, and to estimate joint extremal probabilities beyond observed levels. We here develop a more flexible modeling framework based on the class of max‐infinitely divisible processes, which extend max‐stable processes while retaining dependence properties that are natural for maxima. We propose two parametric constructions for max‐infinitely divisible models, which relax the max‐stability property but remain close to some popular max‐stable models obtained as special cases. The first model considers maxima over a finite, random number of independent observations, while the second model generalizes the spectral representation of max‐stable processes. Inference is performed using a pairwise likelihood. We illustrate the benefits of our new modeling framework on Dutch wind gust maxima calculated over different time units. Results strongly suggest that our proposed models outperform other natural models, such as the Student‐t copula process and its max‐stable limit, even for large block sizes.     

Work Trajectories of Female and Male Immigrants in Spain

This article aims to examine in depth the work trajectories of individuals over time, in order to provide a wider perspective of the employment history of immigrants compared to native people, by gender and for more than one decade (2005–2017) in Spain. We use microdata (cohort and multivariate analysis) from the Labour Force Survey and carry out a comparison for three groups: the Spanish born in Spain, the Spanish born abroad, and the non-Spanish born abroad. The results confirm that the non-Spanish born-abroad group is characterized by the existence of segmented assimilation. All foreigners suffered a loss in their work trajectories, since their employment rate in 2017 has as yet neither reached the level of the last years of the previous economic expansion nor the level of the previous cohorts at the same age.     

Strains in Sustainability Debates: Traditional Ecological Knowledge and Western Science through the Lens of Extension Agents in a Pastoral Region

Those involved in sustainability debates on developmental pathways concur in the synergistic potential of integrating traditional ecological knowledge (TEK) and Western scientific approaches. Transhumant pastoralism is a livelihood strategy adapted to spatiotemporal environmental variability in many mountainous and arid regions worldwide. This form of livelihood is based on a mobile logic that is increasingly threatened by novel lifestyles promoted from a Western mind-set and by climate change. The aim of this article is to identify and characterize the different perspectives of environmental and social issues in a pastoral region and their association with labor collaboration among extension agents, framed in an institutional action. We tackled the inquiry about viewpoints with Q methodology and related it to regional problems, alternative solutions, and future development pathways for transhumant pastoralism and landscape management in northwest Patagonia. We identified six perspectives and characterized them with their topological position in the social network. Mediating positions registered the highest network centrality of labor collaborations among agents, whereas more dominant perspectives emphasizing TEK or scientific knowledge registered intermediate centrality. There was consensus on the need for sustainable developmental options, but the emphasis on combining knowledge still needs convergent solutions.