Estimation for seasonal fractional ARIMA with stable innovations via the empirical characteristic function method

Seasonal fractional ARIMA (ARFISMA) model with infinite variance innovations is used in the analysis of seasonal long-memory time series with large fluctuations (heavy-tailed distributions). Two methods, which are the empirical characteristic function (ECF) procedure developed by Knight and Yu [The empirical characteristic function in time series estimation. Econometric Theory. 2002;18:691–721] and the Two-Step method (TSM) are proposed to estimate the parameters of stable ARFISMA model. The ECF method estimates simultaneously all the parameters, while the TSM considers in the first step the Markov Chains Monte Carlo–Whittle approach introduced by Ndongo et al. [Estimation of long-memory parameters for seasonal fractional ARIMA with stable innovations. Stat Methodol. 2010;7:141–151], combined with the maximum likelihood estimation method developed by Alvarez and Olivares [Méthodes d'estimation pour des lois stables avec des applications en finance. Journal de la Société Française de Statistique. 2005;1(4):23–54] in the second step. Monte Carlo simulations are also used to evaluate the finite sample performance of these estimation techniques.     

A figurational approach to understanding school climate and peer harassment: Possibilities from Norbert Elias’s work

Although psychological approaches have been the mainstay of scholarly research on school climate, offering state-of-the-art measurements and methodologies, sociological perspectives remain essential perspectives because violence is essentially a social phenomenon. This paper offers a theoretical consideration of contributions to this field, focusing specifically on those that provide a critical historical lens. I suggest that while Foucault's approach to the disciplining of docile bodies and self-restraint offers crucial conceptual tools, Norbert Elias's work—which is scarce in scholarly research on school climate—provides a complementary but necessary framework for understanding emotional and relational aspects of peer harassment.     

Bayesian estimation of reliability using time-to-failure distribution of parametric degradation models

This paper focusses on computing the Bayesian reliability of components whose performance characteristics (degradation – fatigue and cracks) are observed during a specified period of time. Depending upon the nature of degradation data collected, we fit a monotone increasing or decreasing function for the data. Since the components are supposed to have different lifetimes, the rate of degradation is assumed to be a random variable. At a critical level of degradation, the time to failure distribution is obtained. The exponential and power degradation models are studied and exponential density function is assumed for the random variable representing the rate of degradation. The maximum likelihood estimator and Bayesian estimator of the parameter of exponential density function, predictive distribution, hierarchical Bayes approach and robustness of the posterior mean are presented. The Gibbs sampling algorithm is used to obtain the Bayesian estimates of the parameter. Illustrations are provided for the train wheel degradation data.     

Measuring stakeholder identification with nonprofit causes: the development and validation of the identification with social causes scale

Nonprofit organizations (NPOs) achieve desired outcomes by fostering organizational identification. However, little research has explored how identification with the cause or the recipients of support relates to identification with the NPO. This study developed the Identification with Social Causes Scale as a mechanism for distinguishing organizational identification from identification with a social group or cause. Data were collected using two groups: the homeless (n = 318) and HIV positive (n = 314) individuals. Exploratory factor analysis and multigroup confirmatory factor analysis yielded a 9-item scale measuring two dimensions: attachment and consubstantiality. Initial construct validity of the scale was established.     

The beta generalized linear exponential distribution

In this paper, a new five-parameter lifetime distribution called beta generalized linear exponential distribution (BGLED) is introduced. It includes at least 17 popular sub-models as special cases such as the beta linear exponential, the beta generalized exponential, and the exponentiated generalized linear distributions. Mathematical and statistical properties of the proposed distribution are discussed in details. In particular, explicit expression for the density function, moments, asymptotics distributions for sample extreme statistics, and other statistical measures are obtained. The estimation of the parameters by the method of maximum-likelihood is discussed and the finite sample properties of the maximum-likelihood estimators (MLEs) are investigated numerically. A real data set is used to demonstrate its superior performance fit over several existing popular lifetime models.     

Measuring Organizational Performance: A Case for Subjective Measures

We review the organizational performance (OP) measurement literature highlighting the limitations of both objective and subjective measures of performance. We argue that, with careful planning, subjective measures can be successfully employed to assess OP. This is because often consistent, reliable and comparable compatible objective data on OP measures – particularly across countries and sectors – is difficult to come by. Considering that an inflated OP measure can be cross‐checked with the use of secondary data, managers have little incentive to report such figures. As a result, when quizzed over the stand‐alone performance measures of their organizations or vis‐à‐vis their rivals, managers accurately assess and respond to questions on the performance of their organizations. An in‐depth statistical exercise conducted on the subjective measures of OP as reported by managers of four sets of companies in four separate countries, show consistent results, thus lending support to this premise.     

Happy People Have Children: Choice and Self-Selection into Parenthood

There is mixed evidence in the existing literature on whether children are associated with greater subjective well-being, with the correlation depending on which countries and populations are considered. We here provide a systematic analysis of this question based on three different datasets: two cross-national and one national panel. We show that the association between children and subjective well-being is positive only in developed countries, and for those who become parents after the age of 30 and who have higher income. We also provide evidence of a positive selection into parenthood, whereby happier individuals are more likely to have children.