Averaging Lorenz curves

A large number of functional forms has been suggested in the literature for estimating Lorenz curves that describe the relationship between income and population shares. The traditional way of overcoming functional-form uncertainty when estimating a Lorenz curve is to choose the function that best fits the data in some sense. In this paper we describe an alternative approach for accommodating functional-form uncertainty, namely, how to use Bayesian model averaging to average the alternative functional forms. In this averaging process, the different Lorenz curves are weighted by their posterior probabilities of being correct. Unlike a strategy of picking the best-fitting function, Bayesian model averaging gives posterior standard deviations that reflect the functional-form uncertainty. Building on our earlier work (Chotikapanich and Griffiths, 2002), we construct likelihood functions using the Dirichlet distribution and estimate a number of Lorenz functions for Australian income units. Prior information is formulated in terms of the Gini coefficient and the income shares of the poorest 10% and poorest 90% of the population. Posterior density functions for these quantities are derived for each Lorenz function and are averaged over all the Lorenz functions.     

劳动能力丧失损害赔偿的理论依据问题

劳动能力本质上属于健康权人格利益,不是独立的人格权。劳动能力的丧失是原来具有劳动能力的自然人受到他人的侵害后而致使身体残疾的结果。劳动能力丧失赔偿的所得丧失说、劳动能力丧失说、生活来源丧失说,都存在缺陷,应当予以重构。在确定我国丧失劳动能力损害赔偿制度的理论论据时,应当采用一种更为科学的理论,即以劳动能力为基础的收入丧失说。在实践中,则要以此为依据来确定劳动收入赔偿金、残疾用具费、生活上增加的必需支出、特殊医疗费、被扶养人生活费、精神抚慰金等内容。     

南非种族冲突的化解与现代化之路

南非种族隔离制度未能消弭种族间的尖锐矛盾,反而引发激烈的种族冲突。在镇压无法奏效的情况下,南非政府开始了民主改革的进程,历经沃斯特的政策调整、博塔的改革总战略和德克勒克的改革三个阶段,较成功地用民主改革的方式化解了南非的种族冲突,极大地推动了南非的现代化。南非民主改革和现代化进程表明:各种族间的宽容和解精神是南非民主改革取得成功的关键;种族关系应当建立在平等的基础之上;领袖人物的个人作用在此过程中相当突出和关键;民主与法制是现代化的根本保证;各种族文化应当兼容并蓄,全盘照搬和彻底排斥都是不可取的。     

"民官比"不是影响政治体制改革的重要因素

在政治体制改革中,公务员或国家干部人数的多少并不是一个关键因素,重要的是必须把政府的社会定位(包括角色、权力和责任)划分清楚。与世界各国相比较,我国197.69∶1(或116.27∶1)的“民官比”并不高,因此,今后的政治体制改革不需要再把精力集中在“精简”上,而应按邓小平的部署,首先把党政分开和权力下放的工作做好。毕竟“小政府”是指“政府权力受限制”,而非“人数更少”;“大社会”是指“社会权利更广泛”,而非“人数更多”。     

中国出入境管理体制的抉择

近年来,出入中国边境口岸的人员和货物陡增,与国际社会出入境管理体制相比较,中国的出入境管理体制还欠完善.具体表现为专属中央管理的出入境事务由各级公安部门代为管理,公安部门的属地管辖、多层管理导致区域化壁垒、政令不畅;同时,公安、外交部门在护照管理上信息不通,多头执法,易产生管理漏洞.为与国际移民法接轨构建科学的出入境管理体制,中国应尽早出台<出入境法>;改革现有的多头管理体制,争取在北京奥运会前,逐步将全国出入境管理统一置于中央政府监管之下;利用<护照法>刚刚出台之契机,统一出入境证件种类和发放程序,增加并细化签证类别,简化出入境手续;重视人员素质提升,实现从管理职能向服务职能的目标转变.     

Generalized additive models for location, scale and shape

Summary.  A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y , as parametric and/or additive nonparametric (smooth) functions of explanatory variables and/or random-effects terms. Maximum (penalized) likelihood estimation is used to fit the (non)parametric models. A Newton–Raphson or Fisher scoring algorithm is used to maximize the (penalized) likelihood. The additive terms in the model are fitted by using a backfitting algorithm. Censored data are easily incorporated into the framework. Five data sets from different fields of application are analysed to emphasize the generality of the GAMLSS class of models.     

改革开放——中华民族的复兴之路

建国以来，中国的发展以1978年为界分为前后两个30年。前30年，中国在计划经济体制下，顺利完成了国民经济的恢复任务、社会主义改造，并建立起比较完善的国民经济体系。后30年，中国通过改革开放，走上了一条中国特色社会主义发展道路，初步实现了国家的繁荣强盛，但是也面临着发展的困境。如果说，正是通过30年的改革开放，使中国真正跻身世界大国行列，那么中国在今后的发展中解决一系列发展难题，也必然要靠继续深化改革扩大开放。因此，认真总结中国改革开放的经验教训，为实现中华民族的伟大复兴就是我们必须要做的重要工作。     

Bayesian analysis of a marked point process: Application in seismic hazard assessment

Point processes are the stochastic models most suitable for describing physical phenomena that appear at irregularly spaced times, such as the earthquakes. These processes are uniquely characterized by their conditional intensity, that is, by the probability that an event will occur in the infinitesimal interval (t, t+Δt), given the history of the process up tot. The seismic phenomenon displays different behaviours on different time and size scales; in particular, the occurrence of destructive shocks over some centuries in a seismogenic region may be explained by the elastic rebound theory. This theory has inspired the so-called stress release models: their conditional intensity translates the idea that an earthquake produces a sudden decrease in the amount of strain accumulated gradually over time along a fault, and the subsequent event occurs when the stress exceeds the strength of the medium. This study has a double objective: the formulation of these models in the Bayesian framework, and the assignment to each event of a mark, that is its magnitude, modelled through a distribution that depends at timet on the stress level accumulated up to that instant. The resulting parameter space is constrained and dependent on the data, complicating Bayesian computation and analysis. We have resorted to Monte Carlo methods to solve these problems.     

Real nonparametric regression using complex wavelets

Summary.  Wavelet shrinkage is an effective nonparametric regression technique, especially when the underlying curve has irregular features such as spikes or discontinuities. The basic idea is simple: take the discrete wavelet transform of data consisting of a signal corrupted by noise; shrink or remove the wavelet coefficients to remove the noise; then invert the discrete wavelet transform to form an estimate of the true underlying curve. Various researchers have proposed increasingly sophisticated methods of doing this by using real-valued wavelets. Complex-valued wavelets exist but are rarely used. We propose two new complex-valued wavelet shrinkage techniques: one based on multiwavelet style shrinkage and the other using Bayesian methods. Extensive simulations show that our methods almost always give significantly more accurate estimates than methods based on real-valued wavelets. Further, our multiwavelet style shrinkage method is both simpler and dramatically faster than its competitors. To understand the excellent performance of this method we present a new risk bound on its hard thresholded coefficients.     

大学生学习观现状及其改革与对策

正确的学习观,既对大学生的知识学习和能力培养有重要的指导作用,也对促进学校的教育、教学改革和做好学校的学生教育与管理工作具有积极的意义。这里针对目前大学生学习观的现状进行分析,并就其主要问题和产生这些问题的原因进行探讨,进而阐释了引导大学生改革学习观的必要性,提出了用全面性、自主性、选择性、创造性、终身性的学习理念来引导大学生的学习,使大学生树立正确学习观。