Evaluating economic theories of NPOs: A survey, a case study and some new directions for socio-economics

The contribution economists have made to the multidisciplinary field of non-profit studies is remarkable when one considers that non-profit organizations (NPOs) have traditionally been regarded as “non-economic” institutions that lie outside the scope of economic analysis. However, despite its achievements there has been concern about the emergence of “theoretical inertia” in the economics of NPOs. This paper suggests some ways in which the revisionist approach reflected in economic theories of the supply-side of the voluntary sector could be augmented. In particular it focuses on the emotional basis for stakeholder commitments and the consequent dependence NPOs have on their organizational leadership to foster the development of shared hopes that can sustain these commitments in the face of disappointments. These ideas are discussed in relation to the provision by NPOs of supported employment services to the disabled.     

Robust kernel estimators for additive models with dependent observations

Robust nonparametric estimators for additive regression or autoregression models under an α-mixing condition are proposed. They are based on local M-estimators or local medians with kernel weights, and their asymptotic behaviour is studied. Moreover, diese local M-estimators achieve the same univariate rate of convergence as their linear relatives.     

On the margin? Residential child care in Scotland and Finland

Situated on the margins of Europe, Scotland and Finland are small countries which share similar demographic and economic profiles. In many European countries, residential child care can also be considered to be ‘on the margin’ of child care provision; there is ambivalence about residential care and a view that it should be used as a last resort. This paper examines systems and practices of residential care in Scotland and Finland, locating these in the context of wider child welfare policy in both countries. The underpinning principles of child welfare provision in both countries are similar—based on children's rights and primarily family-focused. In both countries there are also similar concerns about the fragmentation of child care provision and the cost of residential services. However, there are also important differences relating to child welfare provision and the use of residential care. In Finland, overall numbers of children in residential care are much greater than in Scotland; the age profile of these children and young people is very different; and the two countries vary markedly in the use of secure accommodation and custody. This comparative analysis suggests new ways of understanding the similarities and difference in the use of residential care in the two countries. It highlights the continuing challenge to develop residential care as a positive and integral part of a continuum of care services.     

Flexible mixture modeling via the multivariate t distribution with?the?Box-Cox transformation: an?alternative to?the?skew-t distribution

Cluster analysis is the automated search for groups of homogeneous observations in a data set. A popular modeling approach for clustering is based on finite normal mixture models, which assume that each cluster is modeled as a multivariate normal distribution. However, the normality assumption that each component is symmetric is often unrealistic. Furthermore, normal mixture models are not robust against outliers; they often require extra components for modeling outliers and/or give a poor representation of the data. To address these issues, we propose a new class of distributions, multivariate t distributions with the Box-Cox transformation, for mixture modeling. This class of distributions generalizes the normal distribution with the more heavy-tailed t distribution, and introduces skewness via the Box-Cox transformation. As a result, this provides a unified framework to simultaneously handle outlier identification and data transformation, two interrelated issues. We describe an Expectation-Maximization algorithm for parameter estimation along with transformation selection. We demonstrate the proposed methodology with three real data sets and simulation studies. Compared with a wealth of approaches including the skew-t mixture model, the proposed t mixture model with the Box-Cox transformation performs favorably in terms of accuracy in the assignment of observations, robustness against model misspecification, and selection of the number of components.     

Long-term Care in China: Issues and Prospects

One of the major socioeconomic challenges China faces is the rapid aging of its population. China is now an aging society, even though it is still regarded as a middle-income economy. Coupled with the market-driven reform of social services and rapid erosion of family support, the provision of affordable and accessible social care services to older people has already become an urgent issue for the government to address. Looking into the future, the formulation of a sustainable position on long-term care (LTC) will increasingly become the major focus of social policy. This article sets out the background to the demographic shifts resulting in the emerging need for LTC in China. It analyzes the issues facing LTC services and reviews their prospects, including the structure, operation, financing, and interfacing of residential and community-based home care services.     

Negative binomial time series models based on expectation thinning operators

The study of count data time series has been active in the past decade, mainly in theory and model construction. There are different ways to construct time series models with a geometric autocorrelation function, and a given univariate margin such as negative binomial. In this paper, we investigate negative binomial time series models based on the binomial thinning and two other expectation thinning operators, and show how they differ in conditional variance or heteroscedasticity. Since the model construction is in terms of probability generating functions, typically, the relevant conditional probability mass functions do not have explicit forms. In order to do simulations, likelihood inference, graphical diagnostics and prediction, we use a numerical method for inversion of characteristic functions. We illustrate the numerical methods and compare the various negative binomial time series models for a real data example.     

Tail Behavior of the Failure Rate Functions of Mixtures

The tail behavior of the failure rate of mixtures of lifetime distributions is studied. A typical result is that if the failure rate of the strongest component of the mixture decreases to a limit, then the failure rate of the mixture decreases to the same limit. For a class of distributions containing the gamma distributions this result can be improved in the sense that the behavior of the failure rate of the mixture asymptotically mirrors that of the strongest component in whether it decreases or increases to a limit. This revised version was published online in July 2006 with corrections to the Cover Date.