论法治与澳门博彩业之理性预期

将新制度经济学关于制度与时间进程的分析方法,引入对＂赌权开放＂后的澳门博彩业对于澳门经济活动影响的考察,具有特殊意义。通过讨论博彩制度与财富增长之间的关系,可以看到,澳门博彩业在打破垄断引入竞争后,目前澳门博彩业带来的＂经济神话＂必然会破灭,因此关键仍然是需要加强＂法治＂,将这一产业纳入法律监管的轨道。     

救助、就业与福利依赖——兼论关于中国低保制度“养懒汉”的担忧

西方关于福利依赖及其对就业的负面影响的讨论从1980年起成为热点,主流观点认为救助对于贫富差距的调节作用有限,且可能造成福利依赖,不利于就业甚至影响经济发展。受其影响,近年来中国学界和公共平台也出现了关于低保这项救助制度"养懒汉"的担忧。文章通过回顾国内外现有的理论和经验研究,分析了救助是否必然导致福利依赖、就业是否能避免福利依赖以及中国的低保制度是否存在"养懒汉"问题这三个议题,提出救助、就业和福利依赖的关系是复杂的,它并非通常认为的"救助会导致福利依赖,而就业能避免福利依赖"。救助和就业并非"对立"或简单的替代关系,应从"协调"的角度来重新认识二者关系。     

On Sharp Jensen's Inequality and Some Unusual Applications

The purpose of this article is two-fold. First, we find it very interesting to explore a kind of notion of optimality of the customary Jensen-bound among all Jensen-type bounds. Without this result, the customary Jensen-bound stood alone simply as just another bound. The proposed notion and the associated optimality are important given that in some situations the Jensen's inequality does leave us empty handed.

When it comes to highlighting Jensen's inequality, unfortunately only a handful of nearly routine applications continues to recycle time after time. Such encounters rarely produce any excitement. This article may change that outlook given its second underlying purpose, which is to introduce a variety of unusual applications of Jensen's inequality. The collection of our important and useful applications and their derivations are new.     

On the Asymmetric Marcinkiewicz-Zygmund Strong Law of Large Numbers for Linear Random Fields

In this article, the asymmetric Marcinkiewicz-Zygmund strong law of large numbers for linear random field under negative association is obtained. Our result generalizes a result in Gut and Studtmüller (2009 Gut , A. , Studtmüller , U. ( 2009 ) An asymmetric Marcinkiewicz-Zygmund LLN for random fields . Statist. Probab. Lett. 79 : 1016 – 1020 .[Crossref], [Web of Science ®] , [Google Scholar]). An asymmetric Marcinkiewicz-Zygmund LLN for random fields to the linear random field by using the Beverige-Nelson decomposition.     

Flexible Bivariate INAR(1) Processes Using Copulas

Multivariate count time series data occur in many different disciplines. The class of INteger-valued AutoRegressive (INAR) processes has the great advantage to consider explicitly both the discreteness and autocorrelation characterizing this type of data. Moreover, extensions of the simple INAR(1) model to the multi-dimensional space make it possible to model more than one series simultaneously. However, existing models do not offer great flexibility for dependence modelling, allowing only for positive correlation. In this work, we consider a bivariate INAR(1) (BINAR(1)) process where cross-correlation is introduced through the use of copulas for the specification of the joint distribution of the innovations. We mainly emphasize on the parametric case that arises under the assumption of Poisson marginals. Other marginal distributions are also considered. A short application on a bivariate financial count series illustrates the model.     

On the Bayes estimators of the parameters of size-biased generalized power series distributions

ABSTRACT

In this paper, we derive the Bayes estimators of functions of parameters of the size-biased generalized power series distribution under squared error loss function and weighted square error loss function. The results of size-biased GPSD are then used to obtain particular cases of the size-biased negative binomial, size-biased logarithmic series, and size-biased Poisson distributions. These estimators are better than the classical minimum variance unbiased estimators in the sense that they increase the range of the estimation. Finally, an example is provided to illustrate the results and a goodness of fit test is done using the maximum likelihood and Bayes estimators.     

Some concepts of mult1variate dependence

Several types of positive dependence are shown to be equiv-alent to the concept of a distribution with a density which is TP₂ in pairs. Among these is the concept of m^?-positive depend-ence of Alam and Wallenius. Using this result, all relationships among many of the most important concepts of positive dependence are determined. Furthermore, an application of the equivalences of these types of positive dependence yields a results of Ahmed, Langberg, Leon and Proschan.     

A note on positive dependence im multivariate distributioms

I counterexample is presented to the result by Alam and Malleolus asserting that if Y is stochastically increasing in a random vector X, then Y is stochastically increasing in a subvector of X. Their result concerning m*-positive dependence, whose proof relies on the erroneous result, is still true.