Value-added distribution to stakeholder of Spanish listed companies: a corporate governance perspective

Journal of Management and Governance - Following a stakeholder corporate governance perspective, we examine whether the characteristics of boards of directors (board size, separation of Chairman...     

Maternal union instability and childhood mortality risk in the Global South, 2010–14

Efforts to improve child survival in lower-income countries typically focus on fundamental factors such as economic resources and infrastructure provision, even though research from post-industrial countries confirms that family instability has important health consequences. We tested the association between maternal union instability and children’s mortality risk in Africa, Latin America and the Caribbean, and Asia using children’s actual experience of mortality (discrete-time probit hazard models) as well as their experience of untreated morbidity (probit regression). Children of divorced/separated mothers experience compromised survival chances, but children of mothers who have never been in a union generally do not. Among children of partnered women, those whose mothers have experienced prior union transitions have a higher mortality risk. Targeting children of mothers who have experienced union instability—regardless of current union status—may augment ongoing efforts to reduce childhood mortality, especially in Africa and Latin America where union transitions are common.     

Testing lack of symmetry in spatial–temporal processes

Symmetry and separability of a covariance function are common assumptions to simplify the modeling effort of spatial–temporal processes. However, many studies in environmental sciences show that real data have complex spatial–temporal dependency structures resulting from lack of symmetry or violation of other standard assumptions of the covariance function. In this study, we propose new formal tests for lack of symmetry by using spectral representations of the spatial–temporal covariance functions of regularly spaced spatial–temporal data. The advantage of the proposed tests is that classical analysis of variance (ANOVA) models can be used for detecting lack of symmetry inherent in spatial–temporal processes. We evaluate the performance of the tests with simulation studies and we apply them to air pollution data.     

Semi-Markov Disability Insurance Models

In this article, we present a stochastic model for disability insurance contracts. The model is based on a discrete time non homogeneous semi-Markov process (DTNHSMP) to which the backward recurrence time process is introduced. This permits a more exhaustive study of disability evolution and a more efficient approach to the duration problem. The use of semi-Markov reward processes facilitates the possibility of deriving equations of the prospective and retrospective mathematical reserves. The model is applied to a sample of contracts drawn at random from a mutual insurance company.     

Staff Reactions Toward Lesbian,Gay, or Bisexual (LGB) People Living in Residential Aged Care Facilities (RACFs) Who Actively Disclose Their Sexual Orientation

Fifty-three staff members currently working in residential aged care facilities located in Barcelona, Spain, were asked about the way they would react if a resident told them that he or she felt sexually attracted and had maintained sexual relationships with another resident of the same gender. Acceptance of non-heterosexual sexual orientation was a frequent answer, and around one in four professionals stated that they would try helping the resident in question, by offering a private space or giving some emotional support. However, some reactions were not consistent with a respectful approach toward sexual diversity, as, for instance, informing the resident’s family or advising the resident to keep his or her sexual orientation hidden. We highlight the importance of developing formal policies and offering formal training to staff in order to address the specific needs of older LGB people living in RACFs.     

The Use of Telematics Devices to Improve Automobile Insurance Rates

Most automobile insurance databases contain a large number of policyholders with zero claims. This high frequency of zeros may reflect the fact that some insureds make little use of their vehicle, or that they do not wish to make a claim for small accidents in order to avoid an increase in their premium, but it might also be because of good driving. We analyze information on exposure to risk and driving habits using telematics data from a pay‐as‐you‐drive sample of insureds. We include distance traveled per year as part of an offset in a zero‐inflated Poisson model to predict the excess of zeros. We show the existence of a learning effect for large values of distance traveled, so that longer driving should result in higher premiums, but there should be a discount for drivers who accumulate longer distances over time due to the increased proportion of zero claims. We confirm that speed limit violations and driving in urban areas increase the expected number of accident claims. We discuss how telematics information can be used to design better insurance and to improve traffic safety.     

Advancing towards inclusive social research: visual methods as opportunities for people with severe mental illness to participate in research

This article explores the possibilities offered by visual methods in the move towards inclusive research, reviewing some methodological implications of said research and reflecting on the potential of visual methods to meet these methodological requirements. A study into the impact of work on social inclusion and the social relationships of people suffering from severe mental illness (SMI) serves to illustrate the use of visual methods such as photo elicitation and graphic elicitation in the context of in-depth interviews with the aim of improving the aforementioned target group’s participation in research, participation understood as one of the basic elements of inclusive approaches. On the basis of this study, we reflect on the potential of visual methods to improve the inclusive approach to research and conclude that these methods are open and flexible in awarding participantsa voice, allowingpeople with SMI to express their needs, and therefore adding value to said approach.     

Mapping social and environmental concerns and the acceptability of genetically modified organisms in the European Union

Simultaneous conflicting attitudes towards an object make both predicting and explaining behaviour a complex endeavour. This paper explores the hypothesis of social ambivalence (so called as well or approach-avoidance conflict) as a phenomenon influencing attitudes towards the environmental effects of the introduction of GMOs (Genetic Modified Organisms). If social ambivalence exists it would be suggestive of an interplay between rational models or behaviour and normative or moral models of behaviour. This paper provides some quantitative analysis based on a representative sample of the European Union, using unique data from the Eurobarometer 58.0 (2002) examining public perceptions of environmental risks. Our findings suggest that GMOs are perceived as having a non-neutral impact on the environmental and social life and that as hypothesized there is evidence of social ambivalence, which appears to be more significant when environmental effects of GM foods are taken into account. Consistently with the hypothesis of interplay between rational and normative models of behaviour, respondents perceive some risks while benefits are not perceived by the public and moral concerns regarding technologies being developed by international corporations are important. A specific type of social ambivalence is found, namely GMO are not accepted for Europeans but they are in less developed countries.     

A non-parametric regression approach to repeated measures analysis in cancer experiments

The validity conditions for univariate or multivariate analyses of repeated measures are highly sensitive to the usual assumptions. In cancer experiments, the data are frequently heteroscedastic and strongly correlated with time, and standard analyses do not perform well. Alternative non-parametric approaches can contribute to an analysis of these longitudinal data. This paper describes a method for such situations, using the results from a comparative experiment in which tumour volume is evaluated over time. First, we apply the non-parametric approach proposed by Raz in constructing a randomization Ftest for comparing treatments. A local polynomial fit is conducted to estimate the growth curves and confidence intervals for each treatment. Finally, this technique is used to estimate the velocity of tumour growth.     

Predicting integrals of diffusion processes

Consider predicting the integral of a diffusion process Z in a bounded interval A, based on the observations Z(t_1n),…,Z(t_nn), where t_1n,…,t_nn is a dense triangular array of points (the step of discretization tends to zero as n increases) in the bounded interval. The best linear predictor is generally not asymptotically optimal. Instead, we predict using the conditional expectation of the integral of the diffusion process, the optimal predictor in terms of minimizing the mean squared error, given the observed values of the process. We obtain that, conditioning on the observed values, the order of convergence in probability to zero of the mean squared prediction error is O_p(n⁻²). We prove that the standardized conditional prediction error is approximately Gaussian with mean zero and unit variance, even though the underlying diffusion is generally non-Gaussian. Because the optimal predictor is hard to calculate exactly for most diffusions, we present an easily computed approximation that is asymptotically optimal. This approximation is a function of the diffusion coefficient.