中国农村居民消费倾向的区域特征分析

文章对我国东部、东北、中部、西部农村居民人均纯收入和消费的关系运用最小二乘法和广义最小二乘法进行了实证分析,结果表明我国农村居民的消费倾向具有较强的区域特征,并遵守边际消费倾向和平均消费倾向递减规律,总体上农村居民边际消费倾向呈"多U型"变动趋势,不同地区农村居民边际消费倾向变化有一定的差异.为扩大消费、促进区域经济均衡协调快速发展,针对不同地区的特点,应制定和实施刺激消费的区域性政策.     

农村居民边际消费倾向与其影响因素关系的实证分析

文章以持久收入假说为基础,构建状态空间模型估计了中国农村居民的消费函数并从中估算出了时变边际消费倾向序列。对农村居民边际消费倾向与其影响因素关系进行实证分析的结果表明,消费习惯、实际收入增长率、不确定性和流动性约束是农村居民边际消费倾向的主要影响因素。因此,解决农村消费不足问题应从提高农民收入增长率、完善消费信贷制度着手。     

基于ELES模型的城镇居民收入与消费关系探析

本文通过对2012年上海市闵行区城镇居民可支配收入和消费情况进行详细和深入分析,利用ELES模型（扩展线性支出系统模型）,计算城镇居民消费投向、基本消费需求支出和需求收入弹性,按边际消费倾向、各项消费支出排序分析,总结闵行区城镇居民消费领域倾向特点,得出结论,并提出建议.     

齐齐哈尔市城镇居民消费倾向与消费弹性实证分析

消费倾向是反映居民生活质量变化和社会经济状况改善的一个重要指标,能够较为准确地反映居民消费结构和消费需求的变化趋势。本文利用扩展线性支出系统模型对2012年齐齐哈尔市城镇居民消费结构截面数据进行系统分析,量化边际消费倾向,精确计算消费相对人均可支配收入和商品价格的弹性,分析其对居民消费的影响。     

城镇居民消费行为的生命周期变异——来自微观面板数据的证据

利用国家统计局山东调查总队城镇住户调查2005年1月至2006年12月的月度数据,通过建立面板数据模型对生命周期假说的推论进行实证检验发现：中国城镇居民的消费行为并不完全符合生命周期假说的预期;其中城镇居民在其生命周期的早期确实有着较高的消费倾向,而在随后一段时间也有较低的边际消费倾向;在退休前阶段城镇居民的消费倾向会较高,而处在退休后生命周期晚期的城镇居民则有着较低的狭义边际消费倾向（不包括医疗和教育支出）和较高的广义边际消费倾向（tg括医疗和教育支出）。     

中国城乡居民消费需求差异问题研究

文章探讨了通货膨胀及收入水平对中国城乡居民消费需求差异影响的问题.误差修正模型表明通货膨胀差异和收入水平差异对总消费水平有正向作用,但同时会拉大城乡间的消费差距.分位数协整回归模型显示通货膨胀抑制了农村居民的消费,但对城镇居民具有财富效应.而且,城镇居民的边际消费倾向要高于农村居民的边际消费倾向.     

我国城镇居民消费函数的均值结构变化模型分析

文章利用均值结构变化模型,建立我国城镇居民的消费函数,经对比发现,均值结构变化模型比使用普通最小二乘法建立的线性回归模型有更高拟合精度。实证研究发现,我国城镇居民的自主性消费显现逐步上升趋势,而边际消费倾向则显现逐步下降趋势,这与我国经济体制改革和社会保障制度不健全有很大的关系。     

我国城乡居民消费行为差异研究

本文使用1978-2014年我国居民消费数据,研究城乡居民的消费总量、收支结构、平均消费倾向、边际消费倾向和恩格尔系数等差异,并选取31个省市的面板数据构建城乡消费模型进行分析。结果表明：①城乡居民消费行为可分三个阶段,城乡差距经历两个轮回,现在第二轮扩张期。②相对而言,农村居民收入低消费率高支出结构固化,对物价变动有滞后性和拖尾性,近期在城镇居民平均消费倾向持续走低时平稳走高。③城镇居民自发消费与边际消费倾向大致呈反比,同一城市的城乡居民自发消费与边际消费倾向相关性不强。文章建议,降低城乡交通通信类支出,扩大城乡家庭设备及用品类市场和农村文教娱乐类市场,提高农村居民健康及医疗保障水平。     

中国城镇消费的二次支出系统估计与分析

在消费需求分析中常用到线性支出系统 ,但由于线性支出系统假定居民边际消费倾向不变 ,而实际上不同收入层次的城镇居民对同类消费品的边际消费倾向不可能完全相同 ,所以存在着一定的局限性。本文主要利用二次支出系统来估计分析中国城镇居民的消费需求 ,以克服这种局限性 ,从而深入地探讨了需求与收入的关系     

我国城镇和农村居民信息消费的比较分析

作为消费热点之一的信息消费,其规模在一定程度上受居民收入规模的影响.在弗里德曼持久收入理论的基础上建立回归方程,进行回归分析,得出我国城镇居民信息消费边际倾向大于农村居民信息消费边际倾向的结果.因此,我国现阶段应该优先在城镇培育信息消费.     

GARCH-Type Models and Performance of Information Criteria

This article discusses the ability of information criteria toward the correct selection of different especially higher-order generalized autoregressive conditional heteroscedasticity (GARCH) processes, based on their probability of correct selection as a measure of performance. Each of the considered GARCH processes is further simulated at different parameter combinations to study the possible effect of different volatility structures on these information criteria. We notice an impact from the volatility structure of time series on the performance of these criteria. Moreover, the influence of sample size, having an impact on the performance of these criteria toward correct selection, is observed.     

The construction of multi-factor crossover designs in animal husbandry studies

For ethical reasons it is important to try to obtain as much useful information as possible from an animal experiment whilst minimizing the number of animals used. Crossover designs, where applicable, provide an ideal framework for achieving this. If two or more treatment factors are included in the crossover design then the reduction in total animal usage can be considerable. In this paper we consider such designs, defined as multi-factor crossover designs. The designs are applicable when there are several different treatment factors, each at t levels, to be applied to the experimental units. The motivation for investigating these designs was a study conducted at GlaxoSmithKline to determine the preference of male and female dogs for t=5 different types of bed and t=5 different bedding conditions. A construction method is given for forming universally optimal designs for t not too large. Also given is an example for the special case where the number of treatment levels t=6.     

异方差White检验应用的几个问题

White检验通常由LM检验来完成,现实中也可以使用更简单的F检验来替代LM检验;White检验过程中需要构筑辅助回归模型,它可以有不同的形式以应对实际问题的需要;讨论了四类不同的辅助回归模型,理论分析表明,它们在应用中各有所长;最后通过一个实际例子,验证了理论分析的结论,展示了White检验应用的灵活性。     

A statistical test for detecting discordance in rankings between k groups

In several research areas such as psychology, social science, and medicine, studies are conducted in which objects should be ranked by different judges/raters and the concordance of the different rankings is then analyzed. In such studies, it is also frequently of interest to compare the rankings between different groups of judges, e.g. female vs. male judges or judges from different professions. In the two-group case, the two-group concordance test of Schucany & Frawley can be employed for such a comparison. In this article, we propose an extension of this test enabling the comparison of rankings from more than two groups of judges. This test aims to detect disagreement in the average rankings of the objects between k groups with an at least moderate intra-group concordance. We evaluate this test in an extensive simulation study and in an application to data from an aesthetics study. This simulation study shows that the proposed test is able to detect differences between average rankings and performs well even in situations in which the disagreement is comparably small or the intra-group concordance is inhomogeneous.     

Statistical Analyses and Modelling of the Mixing Process of Euro Coins in Germany and Europe

This paper reports on the mixing of Euro coins from different countries of origin in Europe, which started on 1 January 2002. There is an interesting conclusion: that the mobility of small and large denominations is different. The long‐term behaviour of the mixing process is studied using a simple deterministic model and data from Germany, France and the Netherlands. The analysis leads to predictions about the future progress of the mixing process.     

On the merging of quoted survival rates to obtain an overall rate

Frequently in a review paper on treatment or management of a disease, various papers, each quoting different measures of survival, are reviewed. Assuming a common underlying distribution an overall death rate can be estimated. This paper describes the maximum likelihood estimation of the rate and an asymptotic test for its homogeneity among different investigations. An example is given of the methodfs use in analysis of published results on survival from salivary gland tumours.     

春节模型的设计与应用

 季节调整是经济数据预处理中非常重要的一个步骤。现有的主流季节调整方法X-12-ARIMA 和TRAMO/SEATS中都包含节假日因素的调整。由于不同的国家节假日一般不同,因此各国在进行经济数据的季节调整时,都需要结合本国的假日对季节调整方法进行修正。春节是中国最为重要而且持续时间最长的节日,具体日期可以出现在一月也可以在二月。本文基于X-12-ARIMA方法,同时考虑春节对经济指标的正负性影响效应、春节影响的变化速率以及春节效应的时长三个因素,设计了十二个不同类型的春节模型。本文应用Eviews软件和Demetra软件,采集不同的经济指标,对所设计的春节模型进行了应用研究,并根据异常值改善标准,对最佳的春节模型进行了选择与比较分析。     

Modelling of connected processes

The problem of comparing, contrasting and combining information from different sets of data is an enduring one in many practical applications of statistics. A specific problem of combining information from different sources arose in integrating information from three different sets of data generated by three different sampling campaigns at the input stage as well as at the output stage of a grey-water treatment process. For each stage, a common process trend function needs to be estimated to describe the input and output material process behaviours. Once the common input and output process models are established, it is required to estimate the efficiency of the grey-water treatment method. A synthesized tool for modelling different sets of process data is created by assembling and organizing a number of existing techniques: (i) a mixed model of fixed and random effects, extended to allow for a nonlinear fixed effect, (ii) variogram modelling, a geostatistical technique, (iii) a weighted least squares regression embedded in an iterative maximum-likelihood technique to handle linear/nonlinear fixed and random effects and (iv) a formulation of a transfer-function model for the input and output processes together with a corresponding nonlinear maximum-likelihood method for estimation of a transfer function. The synthesized tool is demonstrated, in a new case study, to contrast and combine information from connected process models and to determine the change in one quality characteristic, namely pH, of the input and output materials of a grey-water filtering process.     

Identification and Efficient Estimation of Simultaneous Equations Network Models

This article considers identification and estimation of social network models in a system of simultaneous equations. We show that, with or without row-normalization of the social adjacency matrix, the network model has different equilibrium implications, needs different identification conditions, and requires different estimation strategies. When the adjacency matrix is not row-normalized, the variation in the Bonacich centrality across nodes in a network can be used as an IV to identify social interaction effects and improve estimation efficiency. The number of such IVs depends on the number of networks. When there are many networks in the data, the proposed estimators may have an asymptotic bias due to the presence of many IVs. We propose a bias-correction procedure for the many-instrument bias. Simulation experiments show that the bias-corrected estimators perform well in finite samples. We also provide an empirical example to illustrate the proposed estimation procedure.     

Meta-analysis using multilevel models with an application to the study of class size effects

Meta-analysis is formulated as a special case of a multilevel (hierarchical data) model in which the highest level is that of the study and the lowest level that of an observation on an individual respondent. Studies can be combined within a single model where the responses occur at different levels of the data hierarchy and efficient estimates are obtained. An example is given from studies of class sizes and achievement in schools, where study data are available at the aggregate level in terms of overall mean values for classes of different sizes, and also at the student level.