工业化、服务业化与政府作为:理论总结与实践改进

从增长的成分看,中国经济30多年的快速发展,更主要地来源于工业化。但是,由于政策的偏向和结构的失衡,中国现行的工业化模式日益遇到越来越多的问题和挑战。这些问题在很大的程度上来源于第三产业滞后于第二产业的发展,城市化或服务业化滞后于工业化的进程。化解当前所遇到的系列经济及社会问题,根本措施在于通过深度改革,促进现代服务业和第三产业的发展,使服务业与工业产业能够良性互动。     

我国财政支出对居民消费扩张的效应分析

财政支出作为财政政策的重要组成部分,体现了一国政府职能的内在要求。现阶段,如何合理安排财政支出以有效刺激居民消费,已经成为我国经济政策的重要内容。通过建立财政支出与居民消费的向量误差修正模型(VEC模型),可以发现财政支出部分"挤出"居民消费,居民收入无论短期还是长期均是居民消费增长的重要因素。     

Estimates based on preliminary data from a specific subsample and from respondents not included in the subsample

Various approaches to obtaining estimates based on preliminary data are outlined. A case is then considered which frequently arises when selecting a subsample of units, the information for which is collected within a deadline that allows preliminary estimates to be produced. At the moment when these estimates have to be produced it often occurs that, although the collection of data on subsample units is still not complete, information is available on a set of units which does not belong to the sample selected for the production of the preliminary estimates. An estimation method is proposed which allows all the data available on a given date to be used to the full-and the expression of the expectation and variance are derived. The proposal is based on two-phase sampling theory and on the hypothesis that the response mechanism is the result of random processes whose parameters can be suitably estimated. An empirical analysis of the performance of the estimator on the Italian Survey on building permits concludes the work. The Sects. 1,2,3,4 and the technical appendixes have been developed by Giorgio Alleva and Piero Demetrio Falorsi; Sect. 5 has been done by Fabio Bacchini and Roberto Iannaccone. Piero Demetrio Falorsi is chief statisticians at Italian National Institute of Statistics (ISTAT); Giorgio Alleva is Professor of Statistics at University “La Sapienza” of Rome, Fabio Bacchini and Roberto Iannaccone are researchers at ISTAT.     

关于扩大内需的几点思考

当前扩大内需、拉动经济增长已成为社会各界关注的焦点。本文对其中的几个主要问题阐述了自己的看法     

浅谈大众文化的兴起对经典美学的挑战

进入 90年代 ,美学研究的转型问题成为学术界的一大热点 ,本文基于当下文化现状 ,分析这种转型的表现 ,指出其发生的原因及合理性。     

Optimal Bootstrap Sample Size in Construction of Percentile Confidence Bounds

In traditional bootstrap applications the size of a bootstrap sample equals the parent sample size, n say. Recent studies have shown that using a bootstrap sample size different from n may sometimes provide a more satisfactory solution. In this paper we apply the latter approach to correct for coverage error in construction of bootstrap confidence bounds. We show that the coverage error of a bootstrap percentile method confidence bound, which is of order O ( n ^−2/2) typically, can be reduced to O ( n ⁻¹) by use of an optimal bootstrap sample size. A simulation study is conducted to illustrate our findings, which also suggest that the new method yields intervals of shorter length and greater stability compared to competitors of similar coverage accuracy.     

On Comparison of Stopping Times in Sequential Procedures for Exponential Families of Stochastic Processes

For curved ( k + 1), k -exponential families of stochastic processes a natural and often studied sequential procedure is to stop observation when a linear combination of the coordinates of the canonical process crosses a prescribed level. For such procedures the model is, approximately or exactly, a non-curved exponential family. Subfamilies of these stopping rules defined by having the same Fisher (expected) information are considered. Within a subfamily the Bartlett correction for a point hypothesis is also constant. Methods for comparing the durations of the sampling periods for the stopping rules in such a subfamily are discussed. It turns out that some stopping times tend to be smaller than others. For exponential families of diffusions and of counting processes the probability that one such stopping time is smaller than another can be given explicity. More generally, an Edgeworth expansion of this probability is given     

On cornish-fisher expansions as a ratio of determinants without cumulants

A new method of approximating one quantile of a distribution function in terms of the corresponding quantile of another distribution function is introduced. The method utilizes the Cornish-Fisher expansion so as to eliminate the requirement for knowing the cumulants while at the same time retaining the desired simplicity as well as the property of not affecting the order of the error of the approximation.     

On the convergence rate of model selection criteria

The goal of the current paper is to compare consistent and inconsistent model selection criteria by looking at their convergence rates (to be defined in the first section). The prototypes of the two types of criteria are the AIC and BIC criterion respectively. For linear regression models with normally distributed errors, we show that the convergence rates for AIC and BIC are 0(n^-1) and 0((n log n)^-1/2) respectively. When the error distributions are unknown, the two criteria become indistinguishable, all having convergence rate O(n^-1/2). We also argue that the BIC criterion has nearly optimal convergence rate. The results partially justified some of the controversial simulation results in which inconsistent criteria seem to outperform consistent ones.     

随机网络瓶颈容量扩张相关机会规划模型

文章研究的问题为,在不确定环境中,怎样去增加网络中一组边的容量到一个指定的容量,以至于网络瓶颈扩张的费用不超过给定的总费用上限的概率尽可能的大.本文假定每一条边的单位扩张费用Wi是一个随机的变量,它服从一定的概率分布.带有随机单位扩张费用W的网络瓶颈容量扩张问题可以根据一些规则,列出它的相关机会规划模型的通用表达式.随后,本文将网络瓶颈容量算法、随机模拟方法和遗传算法合成在一起,设计出该问题的混合智能通用算法.最后,给出数值算例.