消费者信心的测量方法解析

消费者信心是消费者的一种主观心理状态。对消费者信心的度量借用了心理学研究中的测量量表工具和方法。不同的理论假设产生了不同的量表题项内容和规则。     

基于消费者信心指数的消费行为特征分析

消费者信心指数反映的是消费者对于国家经济环境的主观感受.文章使用LASSO算法,以消费者信心指数为影响因素,建立社会消费品零售总额等宏观销售额指标的回归分析模型,分析了消费者信心指数对其的影响.分析结果显示,消费者对于物价、房价、生活状况和股市状况等方面的主观感受对于其消费行为以及消费品的销售额有显著影响.     

论成都市消费者信心指数的建立

消费者信心指数主要是为了解消费者对经济环境的信心强弱程度,透过抽样调查,反应消费者对目前及往后六个月的经济景气、就业情况与个人财务状况的感受和看法。该指数在一定程度上能够为政府及社会各界了解经济景气变动提供比较科学和直观的时效指标,从而便于各类经济主体的有关经济决策。本文利用计算机辅助电话调查系统对成都市居民进行了消费者信心指数调查,并在此基础上尝试建立成都市消费者信心指数。     

物价因素对消费者信心影响的实证分析

物价是最受普通消费者关注的经济指标,物价水平的波动会对消费者信心产生诸多影响。文章使用按收入水平分组的消费者信心指数数据,分析当消费者具有不同收入水平时,其对于生活状况的信心受物价因素影响的差异;并且作为对比,同时分析了其对于物价状况本身的信心受物价因素影响的差异。     

海峡两岸四地消费者信心指数的比较分析

文章以2009年1、2季度中国大陆、香港、澳门和台湾地区的消费者信心调查数据为依据,从消费者对经济形势、就业状况、物价水平、生活状况、购房时机和投资时机六个方面对海峡两岸四地消费者的信心进行了比较分析.分析结果认为2009年上半年两岸四地消费者对经济的走势仍然存在着不同程度的担忧,但经济形势的积极变化提高了消费者的信心,两岸消费者的信心比年初有了普遍的提升,而消费者信心的提升又会促使经济形势向更好的方向发展.     

对消费者信心指数的质疑

因为要质疑用简单平均法测算的消费者信心指数算法的合理性,所以研究消费者信心指数的二级构成指数间的相互关系,研究发现,各二级指数间相互影响,二级指数间有信息重复。这会导致简单平均算法计算的信心指数放大了某些因素的影响,会产生系统性偏差,导致信心指数的失真。因此,用因子分析方法对消费者信心指数进行修正,研究发现修正后的信心指数与宏观经济变量的相关程度更高。     

洛阳市消费者信心指数调杏一报告

为了解洛阳市居民消费信心变化情况，我们于2011年12月末开展了消费者信心指数调查，此次调查对象为300位城乡居民。调查结果显示，消费者对洛阳市当前经济总体状况和未来经济走势预期评价较为乐观，对收入增长和物价总水平持正面看法的比例明显增加，消费者消费意愿有所增强。我们对调查结果作了进一步分析解读，以期为政府决策和社会公众提供较有价值的居民消费意愿变动信息。     

消费者信心指数与消费需求关系研究——以南京市居民消费需求为例

传统消费理论主要是注重对消费者收入与消费支出的关系研究,而新的西方消费者信心指数理论指出,消费者信心指数对消费支出有重要影响,特别是在当前国内消费需求增长缓慢的情况下,如何提高居民消费信心对刺激居民消费支出的增长有着重要的现实意义。运用计量经济模型,并结合南京市居民消费支出增长与消费者信心指数的数量关系,通过实证研究印证了两者间存在紧密相关性,从而建立南京市居民消费函数的主观因素拓展模型,并进而提出提高居民消费需求的政策建议,即在注重对影响消费的客观因素——收入的研究外,还要注重对影响消费的主观因素——消费者信心指数的研究。     

消费者信心指数的理论背景与实际意义

在许多国家,消费者信心的测度被认为是消费总量的必要补充,消费者信心指数成为重要的领先指标之一,是监测经济周期变化不可缺少的依据。本文从消费者信心指数的创建出发,阐述该指数的作用以及对宏观经济的意义。     

收入预期增长 通胀担忧减弱——河南省消费者信心指数回暖

今年以来,河南省经济延续了平稳较快的增长态势,而且内生动力有所增强,实现了“十二五”的良好开局。城乡居民当前及预期收入的增长和对就业形势的看好、对未来通胀担忧的减弱提升了消费者的信心,推动全省消费者信心指数回暖。河南省地方经济社会调查队对18个省辖市市区和18个县（市、区）及农村的调查结果显示：6月份,全省消费者信心指数为102．4,     

Conditional interval estimation of the exponential location parameter following rejection of a pre-test

The conditional confidence interval for the location parameter of an exponential distribution following a preliminary test is investigated. The conditional confidence interval (CCI) may be shorter than the unconditional confidence interval (UCI) in contrast to the findings for the mean of a normal distribution by Meeks and D'Agostino (1983). The conditional coverage probability of the UCI is obtained by computing the coverage probability under the conditional probability density function. It is shown that the conditional coverage probability of the UCI is not uniformly greater than or less than the nominal level.     

食品标签信息对消费者购买决策的影响研究——以婴幼儿食品为例

基于Hicks消费者剩余的CV形式,构建信息关注度、信息源信任度、信息充分度的Logit食品标签信息影响决策模型.通过在北京市发放问卷并回收、统计数据及分析,研究发现:消费者在购买婴幼儿食品时,对食品标签上的食品生产日期和保质期、营养成分、配料清单、食用指导注意等信息的关注度高,影响显著;对食品品牌、生产厂家及厂址、使用方法及贮藏、安全标识等信息关注度低,影响不显著;消费者对政府机构、婴幼儿医师和学者、亲朋及名人代言等信息源的信任度高,对购买决策影响显著;消费者对非政府机构和食品企业等信息源的信任度低,对购买决策影响不显著;食品标签信息充分度对消费者获得高质量信息、降低风险和提高决策准确度等起到的作用很大;消费者的性别、年龄、收入、受教育程度等对购买决策影响显著;相对于女性而言,食品标签信息对男性消费者的购买决策更有影响.     

Interval estimation for the Pareto distribution based on the progressive Type II censored sample

For the complete sample and the right Type II censored sample, Chen [Joint confidence region for the parameters of Pareto distribution. Metrika 44 (1996), pp. 191–197] proposed the interval estimation of the parameter θ and the joint confidence region of the two parameters of Pareto distribution. This paper proposed two methods to construct the confidence region of the two parameters of the Pareto distribution for the progressive Type II censored sample. A simulation study comparing the performance of the two methods is done and concludes that Method 1 is superior to Method 2 by obtaining a smaller confidence area. The interval estimation of parameter ν is also given under progressive Type II censoring. In addition, the predictive intervals of the future observation and the ratio of the two future consecutive failure times based on the progressive Type II censored sample are also proposed. Finally, one example is given to illustrate all interval estimations in this paper.     

Prediction intervals for the random intercept linear model

Our main purpose is to give a method of constructing prediction intervals for the mean of us future observations in the random intercept linear model, A method is also indicated for constructing exact confidence intervals on the expected value of a future observation.     

Calibration Intervals in Linear Regression Models

Many of the existing methods of finding calibration intervals in simple linear regression rely on the inversion of prediction limits. In this article, we propose an alternative procedure which involves two stages. In the first stage, we find a confidence interval for the value of the explanatory variable which corresponds to the given future value of the response. In the second stage, we enlarge the confidence interval found in the first stage to form a confidence interval called, calibration interval, for the value of the explanatory variable which corresponds to the theoretical mean value of the future observation. In finding the confidence interval in the first stage, we have used the method based on hypothesis testing and percentile bootstrap. When the errors are normally distributed, the coverage probability of resulting calibration interval based on hypothesis testing is comparable to that of the classical calibration interval. In the case of non normal errors, the coverage probability of the calibration interval based on hypothesis testing is much closer to the target value than that of the calibration interval based on percentile bootstrap.     

Forecasting electricity consumption with extra-model information provided by consumers

SUMMARY Univariate time series models make efficient use of available historical records of electricity consumption for short-term forecasting. However, the information (expectations) provided by electricity consumers in an energy-saving survey, even though qualitative, was considered to be particularly important, because the consumers' perception of the future may take into account the changing economic conditions. Our approach to forecasting electricity consumption combines historical data with expectations of the consumers in an optimal manner, using the technique of restricted forecasts. The same technique can be applied in some other forecasting situations in which additional information-besides the historical record of a variable-is available in the form of expectations.     

SHRINKAGE PREDICTION IN THE EXPONENTIAL DISTRIBUTION WITH A PRIOR INTERVAL FOR THE SCALE PARAMETER

The author proposes the best shrinkage predictor of a preassigned dominance level for a future order statistic of an exponential distribution, assuming a prior estimate of the scale parameter is distributed over an interval according to an arbitrary distribution with known mean. Based on a Type II censored sample from this distribution, we predict the future order statistic in another independent sample from the same distribution. The predictor is constructed by incorporating a preliminary confidence interval for the scale parameter and a class of shrinkage predictors constructed here. It improves considerably classical predictors for all values of the scale parameter within its dominance interval containing the confidence interval of a preassigned level.     

Confidence and prediction intervals based on interpolated records

In several statistical problems, nonparametric confidence intervals for population quantiles can be constructed and their coverage probabilities can be computed exactly, but cannot in general be rendered equal to a pre-determined level. The same difficulty arises for coverage probabilities of nonparametric prediction intervals for future observations. One solution to this difficulty is to interpolate between intervals which have the closest coverage probability from above and below to the pre-determined level. In this paper, confidence intervals for population quantiles are constructed based on interpolated upper and lower records. Subsequently, prediction intervals are obtained for future upper records based on interpolated upper records. Additionally, we derive upper bounds for the coverage error of these confidence and prediction intervals. Finally, our results are applied to some real data sets. Also, a comparison via a simulation study is done with similar classical intervals obtained before.     

电子商务中的税收问题研究

21世纪电子商务已呈全球迅速发展之势,电子商务中的诸多涉税问题,已越来越引起世界各国和税务当局以及消费者的广泛关注。电子商务在全球的迅速发展,对现行的税收体系产生了很大的影响.本文阐明了我国电子商务应坚持的基本原则,电子税务是未来税收征管的必由之路。