产品质量国家免检制度与驰名商标法律保护制度的暗合与制度假设

制度经济学理论对制度建构的刚性需求和法学理论对制度结构的宏观整合是完善现代社会法律制度的基础与内在动力。当前我国的产品质量国家免检制度存在着较大的制度缺陷和规范盲区,它与驰名商标法律保护制度在深层次上存在着制度价值上的暗合。＂价值—致归—理论＂的提出为这两种制度的整合与重构提供了理论基础。在这种制度需求下,逐步全面取消产品质量国家免检制度,代之以完善的驰名商标法律保护制度刻不容缓。     

On ridge parameter estimators under stochastic subspace hypothesis

This paper considers several estimators for estimating the restricted ridge parameter estimators. A simulation study has been conducted to compare the performance of these estimators. Based on the simulation study we found that, increasing the correlation between the independent variables has positive effect on the mean square error (MSE). However, increasing the value of ρ has negative effect on MSE. When the sample size increases, the MSE decreases even when the correlation between the independent variables is large. Two real life examples have been considered to illustrate the performance of the estimators.     

消费函数理论的发展及在中国的运用

在西方经济学中，消费函数理论一直处于学科前沿，它的发展与许多大师和诺贝尔奖得主的名字相联系，如凯思斯、库兹涅茨、萨缪尔森、莫迪利安尼、弗里德曼等。它属于宏观经济学，但实际上它的成就却是在微观领域取得的，在它试图从总体上把握国民消费时，它显得缺乏批判精神和前瞻性。中国经济学界最初对消费函数理论持排斥态度，以后转向宽容、验证，也有些研究者作出了有益的探讨。现在要考虑的问题是怎样使消费函数理论与可持续发展的思路相对接?     

论“议程设置”在国家形象塑造中的舆论导向作用

"议程设置"是由美国传播学者提出的理论假设,它提示人们,在有媒介居间的大众传播活动中,媒介议题直接影响受众议题。文本认为,既然受众对客观事物和问题的看法带有媒介引导的色彩,那么国际社会对一个国家的认知与评价也就脱离不了这个框架。文章进而指出,中国的国家形象(即外部公众对中国的印象)是由西方发达国家的媒介所设置的,其中充满了"固定的成见"。中国要想突破西方国家既有的认知、评价藩篱,就必须参与到国际舆论的议程设置中去。     

Hypothesis Testing in Two-Stage Cluster Sampling

Correlated observations often arise in complex sampling schemes such as two-stage cluster sampling. The resulting observations from this sampling scheme usually exhibit certain positive intracluster correlation, as a result of which the standard statistical procedures for testing hypotheses concerning linear combinations of the parameters may lack some of the optimal properties that these possess when the data are uncorrelated. The aim of this paper is to present exact methods for testing these hypotheses by combining within and between cluster information much as in Zhou & Mathew (1993).     

Testing for lack of dependence in the functional linear model

The authors consider the linear model Y_n = ψX_n + ?_n relating a functional response with explanatory variables. They propose a simple test of the nullity of ψ based on the principal component decomposition. The limiting distribution of their test statistic is chi‐squared, but this distribution is also an excellent approximation in finite samples. The authors illustrate their method using data from terrestrial magnetic observatories.     

浙江制造业发展的重点与思路——基于主导产业倒U型演进假说的分析

 本文根据1991-2004浙江、上海和中国相关统计数据，运用制造业占全国份额、产业部门增长率等方法分析了浙江省制造业发展在全国的基本情况，提出并验证了反映区域主导产业演进特征和过程的主导产业倒U型演进假说。结合浙江省经济发展的实际，确定了作为浙江当前产业发展重点的主导产业和支柱产业，提出了浙江省制造业发展的基本思路是资金密集、技术密集型产业优先发展，劳动密集型产业规划发展。浙江当前制造业发展的具体战略是“外引内孵”、“东扩西进”，注重择商引资，加强自主创新，实现区域产业的合理升级和转移。     

Evaluation of a weighted multiple comparison procedure

We consider the problem of accounting for multiplicity for two correlated endpoints in the comparison of two treatments using weighted hypothesis tests. Various weighted testing procedures are reviewed, and a more powerful method (a variant of the weighted Simes test) is evaluated for the general bivariate normal case and for a particular clinical trial example. Results from these evaluations are summarized and indicate that the weighted methods perform in a manner similar to unweighted methods. Copyright © 2005 John Wiley & Sons, Ltd.     

Using a sequence of point optimal tests to select a varying coefficient model

Recent literature in empirical finance has strongly considered the possibility of varying coefficient specifications and has utilised sequences of tests to select a particular varying coefficient model for the data.This paper explores the use of a sequence of point optimal tests in this context and finds power to be the driving factor in correct model selection.     

Testing for additivity and joint effects in multivariate nonparametric regression using Fourier and wavelet methods

We consider the problem of testing for additivity and joint effects in multivariate nonparametric regression when the data are modelled as observations of an unknown response function observed on a d-dimensional (d 2) lattice and contaminated with additive Gaussian noise. We propose tests for additivity and joint effects, appropriate for both homogeneous and inhomogeneous response functions, using the particular structure of the data expanded in tensor product Fourier or wavelet bases studied recently by Amato and Antoniadis (2001) and Amato, Antoniadis and De Feis (2002). The corresponding tests are constructed by applying the adaptive Neyman truncation and wavelet thresholding procedures of Fan (1996), for testing a high-dimensional Gaussian mean, to the resulting empirical Fourier and wavelet coefficients. As a consequence, asymptotic normality of the proposed test statistics under the null hypothesis and lower bounds of the corresponding powers under a specific alternative are derived. We use several simulated examples to illustrate the performance of the proposed tests, and we make comparisons with other tests available in the literature.