Facing the Bullet? Non-Governmental Organisations’ (NGOs’) Responses to the Changing Aid Landscape in Ghana

There is growing evidence suggesting that non-governmental organisations (NGOs) in lower-middle-income countries and emerging economies are facing challenges about their sustainability due to changing aid patterns for development. While the changing development context and the challenges posed to NGOs are increasingly receiving research attention, an understanding of how organisations are responding remains very limited. This article draws on 65 qualitative interviews and presents findings about how NGOs in Ghana, West Africa, are responding to the emerging concerns about their sustainability in the context of the changing aid landscape. Findings suggest that NGOs in Ghana are combining at least six main strategies to attain sustainability. We have categorised these as: (1) eggs-in-multiple-baskets; (2) cost-cutting; (3) strength-in-numbers; (4) security-under-partnership; (5) credibility-building; and (6) visibility-enhancing strategies.     

AN EVALUATION OF FORECAST ERROR IN MASTER PRODUCTION SCHEDULING FOR MATERIAL REQUIREMENTS PLANNING SYSTEMS.

Typical forecast-error measures such as mean squared error, mean absolute deviation and bias generally are accepted indicators of forecasting performance. However, the eventual cost impact of forecast errors on system performance and the degree to which cost consequences are explained by typical error measures have not been studied thoroughly. The present paper demonstrates that these typical error measures often are not good predictors of cost consequences in material requirements planning (MRP) settings. MRP systems rely directly on the master production schedule (MPS) to specify gross requirements. These MRP environments receive forecast errors indirectly when the errors create inaccuracies in the MPS. Our study results suggest that within MRP environments the predictive capabilities of forecast-error measures are contingent on the lot-sizing rule and the product components structure When forecast errors and MRP system costs are coanalyzed, bias emerges as having reasonable predictive ability. In further investigations of bias, loss functions are evaluated to explain the MRP cost consequences of forecast errors. Estimating the loss functions of forecast errors through regression analysis demonstrates the superiority of loss functions as measures over typical forecast error measures in the MPS.     

Common Challenges in Conducting Prolonged Exposure Therapy With Active Duty Service Members: Case Discussion and Strategies for Intervention

Prolonged Exposure (PE) Therapy receives most of its empirical support from trials conducted with civilian posttraumatic stress disorder (PTSD) populations. There has been only limited research on its use with military personnel with combat-related PTSD, and as a consequence, there has been less clinical discussion detailing its application with active duty service members. The purpose of this paper is to highlight two challenges that commonly arise when conducting PE with active duty service members: 1) selecting the most appropriate index event to focus on in imaginal exposure out of the numerous traumas an active duty patient is likely to have experienced, and 2) patients’ tendency to engage in “safety behaviors,” which undermine the effectiveness of in vivo exposure. The nature of these challenges is explored from a theoretical perspective, along with two case examples to illustrate their presentation in treatment. Specific strategies for addressing them are reviewed.     

School,Social-Communicative,and Academic Challenges Among Delinquents and Juvenile Sexual Offenders

This study explores the association between student factors and delinquency by comparing two groups of adjudicated youth in six Midwestern residential facilities: 331 young men committed for a sexual offense, and 171 committed for a nonsexual offense. Statistically significant findings include juvenile sexual offenders exhibiting a greater number of delinquent behaviors and greater academic and social difficulties compared with their counterparts adjudicated for a nonsexual offense. Additionally, path analysis revealed that school experience was negatively associated with delinquency for both groups. For juvenile sexual offenders, academic difficulties were associated with delinquency through their school experience. Among general delinquents, delinquency was directly associated with social difficulties and school experience. Implications for interventions and future research are discussed.     

‘We are not anything alike’: marginalization of health professionals with disabilities

Despite inclusive rhetoric, disabled peoples’ participation in the Health and Human Service (HHS) professions remains limited. This study explores the perspectives of individuals in the HHS sector regarding inclusion-related barriers and facilitators. We found three mechanisms that marginalize disabled people in HHS education and professions: dominant disabling discourses; discriminatory design within programmes and universities; and oppressive interactions. The inclusion of disabled individuals is vital for ensuring HHS professionals represent the populations they serve. By challenging the views of educators, professionals, and scholars, these findings may become part of the foundation upon which change can be created.     

Trait Mindfulness,Problem-Gambling Severity,Altered State of Awareness and Urge to Gamble in Poker-Machine Gamblers

In Australia, poker-machine gamblers represent a disproportionate number of problem gamblers. To cultivate a greater understanding of the psychological mechanisms involved in poker-machine gambling, a repeated measures cue-reactivity protocol was administered. A community sample of 38 poker-machine gamblers was assessed for problem-gambling severity and trait mindfulness. Participants were also assessed regarding altered state of awareness (ASA) and urge to gamble at baseline, following a neutral cue, and following a gambling cue. Results indicated that: (a) urge to gamble significantly increased from neutral cue to gambling cue, while controlling for baseline urge; (b) cue-reactive ASA did not significantly mediate the relationship between problem-gambling severity and cue-reactive urge (from neutral cue to gambling cue); (c) trait mindfulness was significantly negatively associated with both problem-gambling severity and cue-reactive urge (i.e., from neutral cue to gambling cue, while controlling for baseline urge); and (d) trait mindfulness did not significantly moderate the effect of problem-gambling severity on cue-reactive urge (from neutral cue to gambling cue). This is the first study to demonstrate a negative association between trait mindfulness and cue-reactive urge to gamble in a population of poker-machine gamblers. Thus, this association merits further evaluation both in relation to poker-machine gambling and other gambling modalities.     

Comparison of asymmetric stochastic volatility models under different correlation structures

This paper conducts simulation-based comparison of several stochastic volatility models with leverage effects. Two new variants of asymmetric stochastic volatility models, which are subject to a logarithmic transformation on the squared asset returns, are proposed. The leverage effect is introduced into the model through correlation either between the innovations of the observation equation and the latent process, or between the logarithm of squared asset returns and the latent process. Suitable Markov Chain Monte Carlo algorithms are developed for parameter estimation and model comparison. Simulation results show that our proposed formulation of the leverage effect and the accompanying inference methods give rise to reasonable parameter estimates. Applications to two data sets uncover a negative correlation (which can be interpreted as a leverage effect) between the observed returns and volatilities, and a negative correlation between the logarithm of squared returns and volatilities.     

Parameter Estimation Robust to Low-Frequency Contamination

We provide methods to robustly estimate the parameters of stationary ergodic short-memory time series models in the potential presence of additive low-frequency contamination. The types of contamination covered include level shifts (changes in mean) and monotone or smooth time trends, both of which have been shown to bias parameter estimates toward regions of persistence in a variety of contexts. The estimators presented here minimize trimmed frequency domain quasi-maximum likelihood (FDQML) objective functions without requiring specification of the low-frequency contaminating component. When proper sample size-dependent trimmings are used, the FDQML estimators are consistent and asymptotically normal, asymptotically eliminating the presence of any spurious persistence. These asymptotic results also hold in the absence of additive low-frequency contamination, enabling the practitioner to robustly estimate model parameters without prior knowledge of whether contamination is present. Popular time series models that fit into the framework of this article include autoregressive moving average (ARMA), stochastic volatility, generalized autoregressive conditional heteroscedasticity (GARCH), and autoregressive conditional heteroscedasticity (ARCH) models. We explore the finite sample properties of the trimmed FDQML estimators of the parameters of some of these models, providing practical guidance on trimming choice. Empirical estimation results suggest that a large portion of the apparent persistence in certain volatility time series may indeed be spurious. Supplementary materials for this article are available online.     

A note on a makespan minimization problem with a multi-ability learning effect

In the scheduling literature the learning effect is perceived as a process of acquiring experience by a processor (e.g. a human worker) in one ability. However, in many real-life problems the processor, during execution of jobs, increases its experience in different, very often independent, abilities (skills). In consequence, it causes the overall growth of the efficiency of the processor. According to this observation, in this paper, we bring into scheduling a new approach called multi-ability learning that generalizes the existing ones and models more precisely real-life settings. On this basis, we focus on a makespan minimization problem with the proposed learning model and provide optimal polynomial time algorithms for its special cases, which often occur in management.     

Asymptotic properties of kernel estimates of a regression function

The consistency of the Parzen kernel-type as well as recursive kernel estimates of a regression function is shown. The rates of the convergence are studied and compared. Moreover, the problem of selecting asymptotically optimal kernels is discussed.