The inverse weighted Lindley distribution: Properties,estimation and an application on a failure time data

In this paper a new distribution is proposed. This new model provides more flexibility to modeling data with upside-down bathtub hazard rate function. A significant account of mathematical properties of the new distribution is presented. The maximum likelihood estimators for the parameters in the presence of complete and censored data are presented. Two corrective approaches are considered to derive modified estimators that are bias-free to second order. A numerical simulation is carried out to examine the efficiency of the bias correction. Finally, an application using a real data set is presented in order to illustrate our proposed distribution.     

Particle learning for Bayesian semi-parametric stochastic volatility model

This article designs a Sequential Monte Carlo (SMC) algorithm for estimation of Bayesian semi-parametric Stochastic Volatility model for financial data. In particular, it makes use of one of the most recent particle filters called Particle Learning (PL). SMC methods are especially well suited for state-space models and can be seen as a cost-efficient alternative to Markov Chain Monte Carlo (MCMC), since they allow for online type inference. The posterior distributions are updated as new data is observed, which is exceedingly costly using MCMC. Also, PL allows for consistent online model comparison using sequential predictive log Bayes factors. A simulated data is used in order to compare the posterior outputs for the PL and MCMC schemes, which are shown to be almost identical. Finally, a short real data application is included.     

Residual variance estimation in moving average models

We consider time series models of the MA (moving average) family, and deal with the estimation of the residual variance. Results are known for maximum likelihood estimates under normality, both for known or unknown mean, in which case the asymptotic biases depend on the number of parameters (including the mean), and do not depend on the values of the parameters. For moment estimates the situation is different, because we find that the asymptotic biases depend on the values of the parameters, and become large as they approach the boundary of the region of invertibility. Our approach is to use Taylor series expansions, and the objective is to obtain asymptotic biases with error of o(l/T), where T is the sample size. Simulation results are presented, and corrections for bias suggested.     

Human Resource Management as a Field of Research*

Drawing on Snow and Thomas's (Journal of Management Studies, 31 (1994), pp. 457–480) matrix, we empirically explore the state of the art in human resource management (HRM) research. The data were obtained through a questionnaire directed to HRM scholars all over the world, in which they were asked about their particular theoretical and methodological approaches. The evidence obtained shows clearly that HRM scholars are progressively abandoning the universalistic perspective and completing their models with contingent and contextual variables. Trying to classify the different contributions proposed and discuss their integration, HRM is described as a field of research with three dimensions: subfunctional, strategic and international. The paper concludes that to provide reliable explanations and valid responses to professional problems, HRM research must advance simultaneously in these three dimensions. As follows from our analysis, there are certain HR issues that still need to be addressed: (1) the strategic use of HR practices, (2) their international applicability, (3) global HR strategies and (4) the synergic integration of HR activities. Nevertheless, to advance our knowledge in these issues, it seems necessary to integrate previous research in subfunctional, strategic and international aspects of HRM.     

Shaping emotional reactions to ethical behaviors: Proactive personality as a substitute for ethical leadership

Due to ethical lapses of leaders, interest in ethical leadership has grown, raising important questions about the responsibility of leaders in ensuring moral and ethical conduct. However, research on ethical leadership has failed to examine the active role that followers' attributes play in enhancing or minimizing the influence of ethical leadership in organizational outcomes. We applied the substitutes for leadership approach (Kerr & Jermier, 1978) to ethical leadership and predicted that proactive personality acts as substitute in the relationship between ethical leadership, workplace emotions and organizational citizenship behaviors (OCBs). Data from two distinct samples offered strong support for the hypotheses. Specifically, we found that ethical leadership was significantly and negatively related to negative workplace emotions when subordinate proactive personality was low, but not when it was high, with consequences for OCBs. These findings suggest that proactive personality constitutes an important moderator on the impact of low ethical leadership on workplace emotions, with consequences for OCBs.     

Ownership structure and board composition in a high ownership concentration context

Few articles have addressed the relation between the ownership structure and the composition of the boards. The results of the analysis performed on a sample of Spanish listed companies for the period 2004–2011, show that in markets where corporate ownership is highly concentrated, it is necessary to devote special attention to blockholders and to differentiate the figure of the independent directors from the group of outsiders. The results confirm a negative and decreasing relation between blockholders and the percentage of independents while insiders’ ownership is only significant if one looks at the percentage of outsiders as a whole, in which case it shows a U-shaped quadratic relation.     

Immigrant perceptions of ethnic and racial discrimination: patterns and singularities in a municipality in the Lisbon Metropolitan Area

In Portugal, studies on discrimination against immigrants have focused almost exclusively either on the indigenous population, or on the foreign population. The former have tended to deploy quantitative and extended methodologies, while the latter studies have opted predominantly for qualitative or intensive methodologies, focusing on particular groups. There are few studies in which the immigrant population is extensively surveyed, covering its diverse origins, life trajectories, and social position in the host society.

In this analysis we examine the main factors that shape the perceptions of ethnic and racial discrimination among immigrant groups living in the Oeiras municipality in the Lisbon Metropolitan Area. This analysis is based on a quantitative analysis of a survey of 422 immigrants, of whom approximately half reported having been discriminated against since their arrival in Portugal. The study is focused on three main explanations related to predictive variables: sociographic, acculturation/cultural proximity, and opportunities for contact with the autochthonous population. A multivariate logistic regression demonstrates that there is a statistically significant relationship between perceived discrimination and some sociographic variables including cultural proximity, especially for Brazilians.     

A Dyadic Approach to Understanding the Link Between Sexual Functioning and Sexual Satisfaction in Heterosexual Couples

Researchers have demonstrated that several dimensions of sexual functioning (e.g., sexual desire, arousal, orgasm) are associated with the sexual satisfaction of individuals in a committed mixed-sex (male–female) relationship. We extended this research by comparing a dyadic model that included both own (i.e., actor effect) and partner (i.e., partner effect) domains of sexual functioning to an individual model that included only actor effects. Participants were 124 mixed-sex couples who completed online measures of sexual functioning and sexual satisfaction. Data analysis using the actor–partner interdependence model (APIM) and structural equation modeling (SEM) indicated that the dyadic model had a better fit than the individual model. Women’s sexual desire and orgasm and men’s erectile functioning were significant positive predictors of both own and partner’s sexual satisfaction. These results are discussed in terms of the importance of taking a dyadic approach to research and clinical work related to sexual satisfaction.     

Inheritances and wealth inequality: a machine learning approach

This paper explores the relationship between received inheritances and the distribution of wealth (financial, non-financial and total) in four developed countries: the United States, Canada, Italy and Spain. We follow the inequality of opportunity (IOp) literature and???considering inheritances as the only circumstance? we show that traditional IOp approaches can lead to non-robust and arbitrary measures of IOp depending on discretionary cut-off choices of a continuous circumstance such as inheritances. To overcome this limitation, we apply Machine Learning methods (‘random forest’ algorithm) to optimize the choice of cut-offs and we find that IOp explains over 60% of wealth inequality in the US and Spain (using the Gini coefficient), and more than 40% in Italy and Canada. Including parental education as an additional circumstance ?available for the US and Italy? we find that inheritances are still the main contributor. Finally, using the S-Gini index with different parameters to weight different parts of the distribution, we find that the effect of inheritances is more prominent at the middle of the wealth distribution, while parental education is more important for the asset-poor.