政府支出结构的国际比较

政府支出影响着一国社会的发展路径 ,因此探求一国政府支出的决定因素或规律有助于科学地确定政府支出结构 ,从而从政府支出角度给社会有序地推动。文章在占有大量数据及进行深入分析基础上 ,对此作了系统的探讨。     

Empirical Performance and Asset Pricing in Hidden Markov Models

Abstract

To improve the empirical performance of the Black-Scholes model, many alternative models have been proposed to address leptokurtic feature, volatility smile, and volatility clustering effects of the asset return distributions. However, analytical tractability remains a problem for most alternative models. In this article, we study a class of hidden Markov models including Markov switching models and stochastic volatility models, that can incorporate leptokurtic feature, volatility clustering effects, as well as provide analytical solutions to option pricing. We show that these models can generate long memory phenomena when the transition probabilities depend on the time scale. We also provide an explicit analytic formula for the arbitrage-free price of the European options under these models. The issues of statistical estimation and errors in option pricing are also discussed in the Markov switching models.     

A Procedure for Identification of Principal Variables by Least Generalized Dependence

Principal components are often used for reducing dimensions in multivariate data, but they frequently fail to provide useful results and their interpretation is rather difficult. In this article, the use of entropy optimization principles for dimensional reduction in multivariate data is proposed. Under the assumptions of multivariate normality, a four-step procedure is developed for selecting principal variables and hence discarding redundant variables. For comparative performance of the information theoretic procedure, we use simulated data with known dimensionality. Principal variables of cluster bean (Guar) are identified by applying this procedure to a real data set generated in a plant breeding experiment.     

Power and Sample Size for Fixed-Effects Inference in Reversible Linear Mixed Models

ABSTRACT

Despite the popularity of the general linear mixed model for data analysis, power and sample size methods and software are not generally available for commonly used test statistics and reference distributions. Statisticians resort to simulations with homegrown and uncertified programs or rough approximations which are misaligned with the data analysis. For a wide range of designs with longitudinal and clustering features, we provide accurate power and sample size approximations for inference about fixed effects in the linear models we call reversible. We show that under widely applicable conditions, the general linear mixed-model Wald test has noncentral distributions equivalent to well-studied multivariate tests. In turn, exact and approximate power and sample size results for the multivariate Hotelling–Lawley test provide exact and approximate power and sample size results for the mixed-model Wald test. The calculations are easily computed with a free, open-source product that requires only a web browser to use. Commercial software can be used for a smaller range of reversible models. Simple approximations allow accounting for modest amounts of missing data. A real-world example illustrates the methods. Sample size results are presented for a multicenter study on pregnancy. The proposed study, an extension of a funded project, has clustering within clinic. Exchangeability among the participants allows averaging across them to remove the clustering structure. The resulting simplified design is a single-level longitudinal study. Multivariate methods for power provide an approximate sample size. All proofs and inputs for the example are in the supplementary materials (available online).     

企业集群与贵州中药、民族药业的健康发展

企业集群是发达国家在产业结构调整、资源整合过程中普遍存在的一种经济现象,它不仅是产业发展成长过程中的一种必然结果,而且凸显出了现代产业发展过程中的某些特征。改革开放的20多年间,我国东部地区的经济发展也呈现了“集群成长”态势,并已经成为东部地区经济快速发展的主要因素之一。近年来,我国西部地区也可以看到一些初步具备集群成长特征的企业网络,但与国际上以及我国东部地区中小企业聚集区域相比,准确的说,我国西部地区目前还没有出现真正意义上的中小企业集群。针对企业集群现象及如何采取有效措施,积极推进西部地区企业集群,促进贵州中药、民族药业健康发展进行探讨。     

地理集群的企业竞争研究

地理集群是近年来学术界的一个热门话题。人们对集群企业间的合作已经进行了深入的研究,并取得了丰硕的成果;相比之下,对集群的企业竞争的研究则比较零散。本文对地理集群的企业竞争研究进行了介绍与分析,以图抛砖引玉,引起人们对地理集群的企业竞争研究的重视。     

A simple approach to analyzing clustered longitudinal data

When modeling correlated binary data in the presence of informative cluster sizes, generalized estimating equations with either resampling or inverse-weighting, are often used to correct for estimation bias. However, existing methods for the clustered longitudinal setting assume constant cluster sizes over time. We present a subject-weighted generalized estimating equations scheme that provides valid parameter estimation for the clustered longitudinal setting while allowing cluster sizes to change over time. We compare, via simulation, the performance of existing methods to our subject-weighted approach. The subject-weighted approach was the only method that showed negligible bias, with excellent coverage, for all model parameters.     

Modelling impact heterogeneity

Summary.  The treatments embodied in social interventions are characterized by their heterogeneity, delivered as they often are by different individuals operating in different social and geographical contexts. One implication of this heterogeneity is that average treatment effects will often be less useful than estimates of differential impacts across contexts. The paper shows how multilevel models can be used to estimate variability of impact and to account for systematic effects. These models are specified for multisite interventions, for studies using cluster allocation and for designs that incorporate matching. The paper indicates how qualitative and quantitative approaches to evaluation could be linked.     

DGM（1，1）模型的改进与高校毕业生的供求预测

一、序言高等教育人才总需求是指各部门、单位和厂商等对高等学校应届毕业生的总体需求。近年来我国大学毕业生就业问题凸现,引起了社会各方面的广泛关注,2005年大学毕业生的就业问题更为突出。事实上,社会对大学毕业生的需求所反映出的主要问题是高等教育办学规模和专业结构的     

Analyzing multivariate longitudinal binary data: A generalized estimating equations approach

The authors consider regression analysis for binary data collected repeatedly over time on members of numerous small clusters of individuals sharing a common random effect that induces dependence among them. They propose a mixed model that can accommodate both these structural and longitudinal dependencies. They estimate the parameters of the model consistently and efficiently using generalized estimating equations. They show through simulations that their approach yields significant gains in mean squared error when estimating the random effects variance and the longitudinal correlations, while providing estimates of the fixed effects that are just as precise as under a generalized penalized quasi‐likelihood approach. Their method is illustrated using smoking prevention data.