Flexible Bivariate Count Data Regression Models

The article develops a semiparametric estimation method for the bivariate count data regression model. We develop a series expansion approach in which dependence between count variables is introduced by means of stochastically related unobserved heterogeneity components, and in which, unlike existing commonly used models, positive as well as negative correlations are allowed. Extensions that accommodate excess zeros, censored data, and multivariate generalizations are also given. Monte Carlo experiments and an empirical application to tobacco use confirms that the model performs well relative to existing bivariate models, in terms of various statistical criteria and in capturing the range of correlation among dependent variables. This article has supplementary materials online.     

Modified ridge analyses under nonstandard

A well-known procedure for the optimization of a second-degree response function over a spherical region of interest is that of ridge analysis. Khuri and Myers (1979) introduced a modification of this procedure by incorporating a certain constraint on the prediction variance. Both procedures, however, assume that the response variable has a constant variance throughtout the experimental region. In the present article, we consider two extensions to Khuri and Myers modifioed ridge analysis. The first extension relaxes the constant variance assumption. In the second extension. generalised linear models are used instead of the trasitional linear model. which are commenly used in responce variables that are not necessaily continusly distribution, including these have discreate distributions, Two examples are presented to illustrate the implementation of the proposed extensions.     

Heterogeneity and study size in random-effects meta-analysis

It is well known that heterogeneity between studies in a meta-analysis can be either caused by diversity, for example, variations in populations and interventions, or caused by bias, that is, variations in design quality and conduct of the studies. Heterogeneity that is due to bias is difficult to deal with. On the other hand, heterogeneity that is due to diversity is taken into account by a standard random-effects model. However, such a model generally assumes that heterogeneity does not vary according to study-level variables such as the size of the studies in the meta-analysis and the type of study design used. This paper develops models that allow for this type of variation in heterogeneity and discusses the properties of the resulting methods. The models are fitted using the maximum-likelihood method and by modifying the Paule–Mandel method. Furthermore, a real-world argument is given to support the assumption that the inter-study variance is inversely proportional to study size. Under this assumption, the corresponding random-effects method is shown to be connected with standard fixed-effect meta-analysis in a way that may well appeal to many clinicians. The models and methods that are proposed are applied to data from two large systematic reviews.     

Classification with minimum ambiguity under distribution heterogeneity

The traditional classification is based on the assumption that distribution of indicator variable X in one class is homogeneous. However, when data in one class comes from heterogeneous distribution, the likelihood ratio of two classes is not unique. In this paper, we construct the classification via an ambiguity criterion for the case of distribution heterogeneity of X in a single class. The separated historical data in each situation are used to estimate the thresholds respectively. The final boundary is chosen as the maximum and minimum thresholds from all situations. Our approach obtains the minimum ambiguity with a high classification accuracy allowing for a precise decision. In addition, nonparametric estimation of the classification region and theoretical properties are derived. Simulation study and real data analysis are reported to demonstrate the effectiveness of our method.     

Entrenchment in publicly traded family firms: Evidence from the S&P 500

Family involvement in corporate governance through ownership, management, and board membership presents a unique dilemma for understanding the strategic impetus and costs of entrenchment decisions. The presence of shared family ties and the family-centered goals of firm principals call to question the applicability of extant agency arguments regarding the nature and antecedents of managerial entrenchment. Exploring this, we develop and test a model of family firm-specific determinants (i.e., family ownership and family's involvement in management and governance) of entrenchment in publicly traded firms by drawing upon principal-principal agency theory. Findings of the empirical analysis of family owned S&P 500 firms suggest family firms are motivated to entrench managers when doing so supports the pursuit of family-centric goals. However, the extent to which entrenchment supports such goals varies at different levels of family ownership.     

A Comment on Salamon and Anheier's “Social Origins of Civil Society”

In this paper we examine Salamon and Anheier's characterization and testing of alternative theories of the size and scope of the nonprofit sector in different countries. We identify various nuances and refinements of these theories, and we suggest ways in which their validation through statistical testing can be extended and improved. Finally, we offer additional avenues of research that could productively exploit the important cross-national data set assembled by the Johns Hopkins Project.     

新农保对中国农村家庭收入的促进效应

基于微观调查数据,对新农保制度能否促进农村家庭的收入进行了实证分析。研究表明：参加新农保和参保人数越多都会使得中国农村家庭的纯收入与人均收入显著增加。基于异质性考虑的研究发现,无论是纯收入还是人均收入,收入越低的家庭,参保对家庭收入的促进效应就越大;而且参加新农保缩小了不同收入家庭的收入差距。     

农民工务工地公共服务感知状况测度

基于微观调查数据,运用模糊数学方法测度农民工对务工地公共服务的感知状况,并分析了异质要素对农民工公共服务感知差异的影响。研究显示,农民工务工地公共服务感知状况的总模糊指数为0.134,反映出该群体在务工地的公共服务体验较差,尤其是在就业服务、社会服务、社会保障上的感知体验仍远低于预期。同时,农民工群体内部出现了基于个体特征和经济地位区分而形成的公共服务感知上的分异。为此政策层面应客观认识农民工在不同维度公共服务上的差异体验,兼顾不同特征农民工的公共服务需求,推动针对这一群体在城市务工地的公共服务的有效供给。