房产免税立法与税收公平的归位

房产税法律制度的改革折射的是社会演进与经济发展的必然趋势。经济发展加剧了社会成员间资源占有的不公平,但是房产税法律制度的发展却并没有弥合资源分配的不公平,反而在多元利益的指导下出现了三种维度的不公平：政府与市场之间的不公平、中央与地方之间的不公平以及居住者和投机者之间的不公平。刚性的税法常常为社会、经济所不融,免税的设计恰好可以弥补税法柔性的不足,在确保财政收入的情况下兼顾社会公平的维护,这也是深化财税体制改革背景下税法变革的秩序要求。房产税法律制度的变革应以量能课征为依据,以税收中性为准绳,区分房产的普遍性与特殊性,达成税收公平的改革效果。     

New Ridge Regression Estimator in Semiparametric Regression Models

In the context of ridge regression, the estimation of shrinkage parameter plays an important role in analyzing data. Many efforts have been put to develop the computation of risk function in different full-parametric ridge regression approaches using eigenvalues and then bringing an efficient estimator of shrinkage parameter based on them. In this respect, the estimation of shrinkage parameter is neglected for semiparametric regression model. Not restricted, but the main focus of this approach is to develop necessary tools for computing the risk function of regression coefficient based on the eigenvalues of design matrix in semiparametric regression. For this purpose the differencing methodology is applied. We also propose a new estimator for shrinkage parameter which is of harmonic type mean of ridge estimators. It is shown that this estimator performs better than all the existing ones for the regression coefficient. For our proposal, a Monte Carlo simulation study and a real dataset analysis related to housing attributes are conducted to illustrate the efficiency of shrinkage estimators based on the minimum risk and mean squared error criteria.     

An exploratory data analysis in scale-space for interval-valued data

We propose an exploratory data analysis approach when data are observed as intervals in a nonparametric regression setting. The interval-valued data contain richer information than single-valued data in the sense that they provide both center and range information of the underlying structure. Conventionally, these two attributes have been studied separately as traditional tools can be readily used for single-valued data analysis. We propose a unified data analysis tool that attempts to capture the relationship between response and covariate by simultaneously accounting for variability present in the data. It utilizes a kernel smoothing approach, which is conducted in scale-space so that it considers a wide range of smoothing parameters rather than selecting an optimal value. It also visually summarizes the significance of trends in the data as a color map across multiple locations and scales. We demonstrate its effectiveness as an exploratory data analysis tool for interval-valued data using simulated and real examples.     

税收筹划税法规制的适度性

税收筹划中各方主体复杂利益的并存、冲突和变易,集中体现为国家财政权与国民财产权的对立和协调,并往往导致税收筹划税法规制中的法律"失度,"进而激发税法制度及其运行由"失度"走向"适度"的变革需求。从总体上看,税法对税收筹划的规制呈现"失度-适度"的二元化状态;从税法理论上分析,这一规制状态根源于"个人营利性"与"社会公共性"的基本矛盾。国家追求税法对税收筹划规制的适度性,就是要平衡协调各方利益主体之间的复杂利益关系,尽量缓解和消除这一基本矛盾,以期实现税法对国家财政权和国民财产权的均衡保护。惟其如此,才能构建起新的税收筹划规制分析模式,方才推动中国税收筹划规制制度不断创新。     

税收筹划在我国的发展现状及对策分析

目前企业税收筹划在我国方兴未艾,它不仅引起了理论界的重视,也引起了税务部门的关注。文章在阐述我国税收筹划发展现状的基础上,分析了其发展的制约因素,并提出了政府及税务机关、企业、税务代理中介机构、税收筹划理论研究工作者等四类主体在促进税收筹划业务发展的对策建议。     

Analysis of Competing Risks by Using Bayesian Smoothing

We consider the competing risks set-up. In many practical situations, the conditional probability of the cause of failure given the failure time is of direct interest. We propose to model the competing risks by the overall hazard rate and the conditional probabilities rather than the cause-specific hazards. We adopt a Bayesian smoothing approach for both quantities of interest. Illustrations are given at the end.     

Penalized Pseudolikelihood Inference in Spatial Interaction Models with Covariates

Given spatially located observed random variables ( x , z = {( x _i , z _i )} _i , we propose a new method for non-parametric estimation of the potential functions of a Markov random field p ( x | z ), based on a roughness penalty approach. The new estimator maximizes the penalized log-pseudolikelihood function and is a natural cubic spline. The calculations involved do not rely on Monte Carlo simulation. We suggest the use of B-splines to stabilize the numerical procedure. An application in Bayesian image reconstruction is described.     

Differential equation models for statistical functions

Differential equations have been used in statistics to define functions such as probability densities. But the idea of using differential equation formulations of stochastic models has a much wider scope. The author gives several examples, including simultaneous estimation of a regression model and residual density, monotone smoothing, specification of a link function, differential equation models of data, and smoothing over complicated multidimensional domains. This paper aims to stimulate interest in this approach to functional estimation problems, rather than provide carefully worked out methods.     

Smoothed bootstrap bandwidth selection for nonparametric hazard rate estimation

A smoothed bootstrap method is presented for the purpose of bandwidth selection in nonparametric hazard rate estimation for iid data. In this context, two new bootstrap bandwidth selectors are established based on the exact expression of the bootstrap version of the mean integrated squared error of some approximations of the kernel hazard rate estimator. This is very useful since Monte Carlo approximation is no longer needed for the implementation of the two bootstrap selectors. A simulation study is carried out in order to show the empirical performance of the new bootstrap bandwidths and to compare them with other existing selectors. The methods are illustrated by applying them to a diabetes data set.