Compulsory Income Management in the Northern Territory – evaluating its impact

Australia has been experimenting with constraining the ways in which welfare recipients can spend their income support payments, limiting their ability to access cash and purchase some products. The policy objectives include to reduce spending on alcohol, gambling, pornography and tobacco in favour of meeting ‘basic’ family needs, especially for children, to limit the scope for financial harassment, encourage pro‐social behaviours, and build financial capabilities. In the logic of the programs these outcomes are expected to be manifest at the individual, family and community levels. The policy has primarily impacted on Indigenous Australians as a result of its geographic targeting, although a recent report has recommended a more stringent version of the program be introduced universally to all welfare recipients other than the aged. The largest of these experiments is ‘New Income Management’ in the Northern Territory, which has had more than 35,000 participants since its introduction in 2010. This article reports on the key findings of the major independent evaluation of New Income Management commissioned by the Australian Government.     

Computationally simple estimation and improved efficiency for special cases of double truncation

Doubly truncated survival data arise when event times are observed only if they occur within subject specific intervals of times. Existing iterative estimation procedures for doubly truncated data are computationally intensive (Turnbull 38:290–295, 1976; Efron and Petrosian 94:824–825, 1999; Shen 62:835–853, 2010a). These procedures assume that the event time is independent of the truncation times, in the sample space that conforms to their requisite ordering. This type of independence is referred to as quasi-independence. In this paper we identify and consider two special cases of quasi-independence: complete quasi-independence and complete truncation dependence. For the case of complete quasi-independence, we derive the nonparametric maximum likelihood estimator in closed-form. For the case of complete truncation dependence, we derive a closed-form nonparametric estimator that requires some external information, and a semi-parametric maximum likelihood estimator that achieves improved efficiency relative to the standard nonparametric maximum likelihood estimator, in the absence of external information. We demonstrate the consistency and potentially improved efficiency of the estimators in simulation studies, and illustrate their use in application to studies of AIDS incubation and Parkinson’s disease age of onset.     

The deterministic EPQ with partial backordering: A new approach

Several authors have developed models for the EOQ when only a percentage of stockouts will be backordered. Most of these models are complicated, with equations unlike those for the EOQ with full backordering. In this paper we extend work by Pentico and Drake [The deterministic EOQ with partial backordering: a new approach. European Journal of Operational Research 2008; in press] that developed equations for the EOQ with partial backordering that are more like those for the EOQ with full backordering to develop a comparable model for the EPQ with partial backordering.     

The moderating effects of home region orientation on R&D investment and international SME performance: Lessons from Korea

Drawing from the resource-based view, we investigate how firm and country combinations affect international SME performance. Using a sample of 2676 international Korean SMEs, we explore the relationships among SME R&D investment, home region orientation and financial performance. Results show that R&D investment has a horizontally inverted S-shaped relationship with performance reflecting cost leadership, stuck in the middle, and differentiation strategies. We also find that a home region orientation moderates the relationship between R&D investment and performance. Home region orientation positively moderates the relationship when R&D investment reflects cost leadership or differentiation but negatively moderates a stuck in the middle strategy.     

An Economic Model of Friendship: Homophily,Minorities, and Segregation

We develop a model of friendship formation that sheds light on segregation patterns observed in social and economic networks. Individuals have types and see type‐dependent benefits from friendships. We examine the properties of a steady‐state equilibrium of a matching process of friendship formation. We use the model to understand three empirical patterns of friendship formation: (i) larger groups tend to form more same‐type ties and fewer other‐type ties than small groups, (ii) larger groups form more ties per capita, and (iii) all groups are biased towards same‐type relative to demographics, with the most extreme bias coming from middle‐sized groups. We show how these empirical observations can be generated by biases in preferences and biases in meetings. We also illustrate some welfare implications of the model.     

老龄工人在组织变革期间的管理:三种模型的应用

基于西方相关文献,本文讨论了组织性结构变革与老龄工人的健康之间的关系.通过对三个健康模型的分析—失去工作模型、付出-回报模型和工作控制模型,探讨了组织性结构变革是否会对老龄工人的健康造成影响,并进一步解释了在不同模型下组织性结构变革通过什么样的方式影响老龄工人的身心健康.文章还分析了三种模型之间的关系和应用,描述了政府和雇主在工作场所发生变化的时候,可以采取的减轻老龄员工健康风险的三个不同方法.最后针对中国现状,提出通过工作岗位支持来帮助老龄员工延缓与年龄相关的工作方面的及来自养老金和劳动力市场方面的压力的建议.     

Spectral estimation for locally stationary time series with missing observations

Time series arising in practice often have an inherently irregular sampling structure or missing values, that can arise for example due to a faulty measuring device or complex time-dependent nature. Spectral decomposition of time series is a traditionally useful tool for data variability analysis. However, existing methods for spectral estimation often assume a regularly-sampled time series, or require modifications to cope with irregular or ‘gappy’ data. Additionally, many techniques also assume that the time series are stationary, which in the majority of cases is demonstrably not appropriate. This article addresses the topic of spectral estimation of a non-stationary time series sampled with missing data. The time series is modelled as a locally stationary wavelet process in the sense introduced by Nason et al. (J. R. Stat. Soc. B 62(2):271–292, 2000) and its realization is assumed to feature missing observations. Our work proposes an estimator (the periodogram) for the process wavelet spectrum, which copes with the missing data whilst relaxing the strong assumption of stationarity. At the centre of our construction are second generation wavelets built by means of the lifting scheme (Sweldens, Wavelet Applications in Signal and Image Processing III, Proc. SPIE, vol. 2569, pp. 68–79, 1995), designed to cope with irregular data. We investigate the theoretical properties of our proposed periodogram, and show that it can be smoothed to produce a bias-corrected spectral estimate by adopting a penalized least squares criterion. We demonstrate our method with real data and simulated examples.     

Moderators of the Relationship Between Physical Activity and Alcohol Consumption in College Students

Abstract

Objective: Among college students, several studies have found a positive relationship between physical activity and alcohol use. The current study tested gender, Greek status, and ethnicity as potential moderators of the physical activity-alcohol use relationship. Participants: Participants were college freshmen (n = 310) endorsing alcohol/drug use. Methods: Students completed questionnaires assessing a number of health behaviors. Results: Results indicated that gender and Greek status were significant moderators of the relationship between physical activity and alcohol consumption. There was a positive relationship between physical activity and alcohol use for men and Greeks, but not for females and non-Greeks. Conclusions: These findings suggest that exercise does not serve as a protective factor for any of the subgroups of college students studied and is positively associated with drinking among college students who are men and/or involved with the Greek system.     

Measuring precautionary wealth using cross-sectional data: the case of farm households

This study models and investigates the presence of precautionary wealth among farm households, something few studies have attempted. Using pooled farm-level data, we find that self-employed farm households accumulate more wealth. Precautionary savings is about 8% of total household wealth. In addition, we find that age, education, occupation, and operation size are important factors influencing wealth accumulation by US farm households.