Automobile prices and protection: The U.S.-Japan trade restraint

We examine the effects of the U.S.-Japan trade restraint on automobile prices and quality upgrading, for both Japanese imports and American small cars. From April 1981 to April 1984 the suggested retail price of all Japanese models increased by 15.8 percent, or 5.3 percent per year. We find that nearly the entire amount of this rise can be explained by the upgrading of individual models. This upgrading may benefit consumers who would purchase a luxury import in any case, but harms those who desire the basic imports. In addition to upgrading, we conclude that a second cost of the trade restraint has been to prevent the yen depreciation from being passed onto American consumers, in terms of lower imported auto prices. For U.S. small cars we find a 9.1 percent rise in the suggested retail price, or 3 percent per year, with a fraction of this amount due to model upgrading. If the yen depreciation had led to lower import prices without the trade restraint, then we expect that U.S. auto prices would have been lower, too.     

神性、人性和理性--略论艺术形态与时代精神

艺术的本质在于其精神性,从艺术和时代精神的相互关系中去确立划分艺术形态的标准是符合艺术本质的.按照艺术所包含的精神内容的不同,艺术形态可分为神性艺术、人性艺术和理性艺术,以丰富的艺术史例可以说明其特征.     

Diagnostics for dependence within time series extremes

Summary. The analysis of extreme values within a stationary time series entails various assumptions concerning its long- and short-range dependence. We present a range of new diagnostic tools for assessing whether these assumptions are appropriate and for identifying structure within extreme events. These tools are based on tail characteristics of joint survivor functions but can be implemented by using existing estimation methods for extremes of univariate independent and identically distributed variables. Our diagnostic aids are illustrated through theoretical examples, simulation studies and by application to rainfall and exchange rate data. On the basis of these diagnostics we can explain characteristics that are found in the observed extreme events of these series and also gain insight into the properties of events that are more extreme than those observed.     

大学研究院管理体制与运行机制创新研究

创新大学研究院管理体制和运行机制，对于推动大学知识和科技创新、加速科技成果产业化和社会化具有重要作用。为此，大学研究院在管理体制方面要实行理事会领导下的院长负责制和虚实结合的矩阵式组织模式。在运行机制方面应建立稳定有力的政策支持体系和科学民主的战略决策制度，建立以团队合作为主的科研队伍体系，建立以竞争为核心的人员聘用体系，建立科学的业绩考评和高效的人才激励制度，建立长效完备的投资渠道，建立积极有效的成果转化机制。     

宪法全面修改与部分修改的比较

宪法修改可分为全面修改和部分修改两种主要方式.全面修改和部分修改除了形式上的差别外,二者还存在认识论、修改评价等方面的重大区别.     

和谐发展:“人的全面发展”理论的时代主题

在专业、集约化生产越来越发达的条件下,人的全面发展如何可能?马克思"人的全面发展"理论的深层旨趣不仅仅是指能力的发展,更是追求社会的和谐.针对资本主义早期发展阶段劳动异化的状况,马克思主义经典作家强调变革旧的生产关系,促进人的发展.在现代化向纵深发展的当今时代,人的和谐发展则成为"人的全面发展"理论的主题.     

Goodness of fit for the inverse Gaussian distribution

For testing the fit of the inverse Gaussian distribution with unknown parameters, the empirical distribution-function statistic A² is studied. Two procedures are followed in constructing the test statistic; they yield the same asymptotic distribution. In the first procedure the parameters in the distribution function are directly estimated, and in the second the distribution function is estimated by its Rao-Blackwell distribution estimator. A table is given for the asymptotic critical points of A². These are shown to depend only on the ratio of the unknown parameters. An analysis is provided of the effect of estimating the ratio to enter the table for A². This analysis enables the proposal of the complete operating procedure, which is sustained by a Monte Carlo study.     

A Bayesian method for classification and discrimination

We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of exact analyses over traditional classification and discrimination techniques, including the ease with which such analyses may be performed in a quite general setting, with possibly several normal-mixture components having different covariance matrices, the computation of exact posterior classification probabilities for observed data and for future cases to be classified, and posterior distributions for these probabilities that allow for assessment of second-level uncertainties in classification.     

LENGTH-BIASING, CHARACTERIZATIONS OF LAWS AND THE MOMENT PROBLEM

A positive random variable X with a finite mean has an induced length-biased law represented by Y, and Y is stochastically larger than X. An independent uniform random contraction of Y, UY, has the same law as X if and only if the latter is exponential. This property is extended to non-uniform contractions and a more general notion of length-biasing. The distributional equality of X and W leads to a functional equation for the moment function of X, which has either Infinitely many solutions or none. When U is constant, X can have a log-normal law, but it can also have laws with the same moment sequence as this log-nod law. The case where U has a certain beta, or generalized beta, law give t3 characterizations of generalized gamma laws, or to products of independent copies of them. This occurs even when these laws are not determined by their moment sequences.     

Deconvolution with supersmooth distributions

Nonparametric deconvolution problems require one to recover an unknown density when the data are contaminated with errors. Optimal global rates of convergence are found under the weighted L_p-loss (1 ≤ p ≤ ∞). It appears that the optimal rates of convergence are extremely low for supersmooth error distributions. To resolve this difficulty, we examine how high the noise level can be for deconvolution to be feasible, and for the deconvolution estimate to be as good as the ordinary density estimate. It is shown that if the noise level is not too high, nonparametric Gaussian deconvolution can still be practical. Several simulation studies are also presented.