各省区季度GDP数据质量评估

  国内外学者对我国GDP数据质量的质疑重点已从年度数据转到季度数据,从全国数据转向地方数据。本文通过设计一套较为系统且可操作性强的季度GDP评估指标体系,运用空间面板数据模型对各省区的季度GDP数据质量进行了实证检验。结果表明,整体来看,中国各省区季度GDP同各经济指标的匹配性较好,数据质量较高,并不存在明显的失真现象;从时间上来看,每年一、二季度的GDP存在一定程度的高估,而每年三、四季度的GDP则存在一定程度的低估,但是这种偏差在统计上不显著;分地区来看,尽管一半省区的季度GDP存在一定程度的高估,另一半省区存在一定程度的低估,但大部分省区高估或低估的程度在统计上不显著。文章进一步分析了其中的原因。     

A Multivariate Synthetic Control Chart for Monitoring the Process Mean Vector of Skewed Populations Using Weighted Standard Deviations

This article proposes a multivariate synthetic control chart for skewed populations based on the weighted standard deviation method. The proposed chart incorporates the weighted standard deviation method into the standard multivariate synthetic control chart. The standard multivariate synthetic chart consists of the Hotelling's T ² chart and the conforming run length chart. The weighted standard deviation method adjusts the variance–covariance matrix of the quality characteristics and approximates the probability density function using several multivariate normal distributions. The proposed chart reduces to the standard multivariate synthetic chart when the underlying distribution is symmetric. In general, the simulation results show that the proposed chart performs better than the existing multivariate charts for skewed populations and the standard T ² chart, in terms of false alarm rates as well as moderate and large mean shift detection rates based on the various degrees of skewnesses.     

Lag Length Selection in DF-GLS Unit Root Tests

We reinvestigate the empirical problem of lag length selection in unit root tests when using the augmented Dickey–Fuller test based on GLS-detrending. We extend the Ng and Perron (1995 Ng , S. , Perron , P. ( 1995 ). Unit root tests in ARMA models with data-dependent methods for the selection of the truncation lag . Journal of American Statistical Association 90 : 268 – 281 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) work on this issue by applying the finite sample critical values calculated using the formulae proposed by Cheung and Lai (1995 Cheung , Y. W. , Lai , K. S. ( 1995 ). Lag order and critical values of a modified Dickey–Fuller test . Oxford Bulletin of Business and Economics 57 : 411 – 418 .[Crossref] , [Google Scholar]). Unlike Ng and Perron (2001 Ng , S. , Perron , P. (2001). Lag length selection and the construction of unit root tests with good size and power. Econometrica 69:1519–1554.[Crossref], [Web of Science ®] , [Google Scholar]) we find through simulation studies that the method of selecting lag length using the sequential t-test in the ADF regression of GLS-detrended series performs the best in most cases.     

Variable Selection in Joint Location and Scale Models of the Skew-t-Normal Distribution

Variable selection is an important issue in all regression analysis, and in this article, we investigate the simultaneous variable selection in joint location and scale models of the skew-t-normal distribution when the dataset under consideration involves heavy tail and asymmetric outcomes. We propose a unified penalized likelihood method which can simultaneously select significant variables in the location and scale models. Furthermore, the proposed variable selection method can simultaneously perform parameter estimation and variable selection in the location and scale models. With appropriate selection of the tuning parameters, we establish the consistency and the oracle property of the regularized estimators. These estimators are compared by simulation studies.     

Zone control charts with estimated parameters for detecting prespecified changes in linear profiles

ABSTRACT

In profile monitoring, control charts are proposed to detect unanticipated changes, and it is usually assumed that the in-control parameters are known. However, due to the characteristics of a system or process, the prespecified changes would appear in the process. Moreover, in most applications, the in-control parameters are usually unknown. To overcome these issues, we develop the zone control charts with estimated parameters to detect small shifts of these prespecified changes. The effects of estimation error have been investigated on the performance of the proposed charts. To account for the practitioner-to-practitioner variability, the expected average run length (ARL) and the standard deviation of the average run length (SDARL) is used as the performance metrics. Our results show that the estimation error results in the significant variation in the ARL distribution. Furthermore, in order to adequately reduce the variability, more phase I samples are required in terms of the SDARL metric than that in terms of the expected ARL metric. In addition, more observations on each sampled profile are suggested to improve the charts' performance, especially for small phase I sample sizes. Finally, an illustrative example is given to show the performance of the proposed zone control charts.     

One stage multiple comparisons of k-1 treatment mean lifetimes with the control for exponential distributions under heteroscedasticity

Abstract

In survival or reliability data analysis, it is often useful to estimate the quantiles of the lifetime distribution, such as the median time to failure. Different nonparametric methods can construct confidence intervals for the quantiles of the lifetime distributions, some of which are implemented in commonly used statistical software packages. We here investigate the performance of different interval estimation procedures under a variety of settings with different censoring schemes. Our main objectives in this paper are to (i) evaluate the performance of confidence intervals based on the transformation approach commonly used in statistical software, (ii) introduce a new density-estimation-based approach to obtain confidence intervals for survival quantiles, and (iii) compare it with the transformation approach. We provide a comprehensive comparative study and offer some useful practical recommendations based on our results. Some numerical examples are presented to illustrate the methodologies developed.     

Combining Univariate Tests for Multivariate Location Problem

In this article, three methods of combining dependent univariate tests are studied. The Bahadur approximate efficiencies are derived under the asymptotic normal assumption. These procedures are applied to the multivariate location problem and compared with two Hotelling-type tests. A Monte Carlo study indicates that in certain cases the powers of the combination methods are much better than Hotelling's T ² and other multivariate nonparametric tests.     

Developing a variables repetitive group sampling plan based on process capability index C pk with unknown mean and variance

In this paper, variables repetitive group sampling plans are developed based on the process capability index C _pk when the quality characteristic follows a normal distribution with unknown mean and variance. The sampling plan parameters such as the sample size and the acceptance constant are determined to minimize the average sample number. Symmetric and asymmetric cases, in percent defectives due to two specification limits, are dealt with for specified combinations of acceptable quality level and limiting quality level. Tables are provided and examples are given to use proposed plans in practice.     

生产环节外包能否助力中国粮食安全？——来自粮食主产区的证据

在中国大力扶持和推进生产环节外包服务业发展的现实背景下,系统评估生产环节外包对中国粮食安全的影响具有重要的现实意义。聚焦粮食安全数量目标与环境目标两个维度,从农户是否参与外包、农户的外包横向参与度与农户的外包纵深参与度三个层面,理论剖析生产环节外包影响中国粮食安全的逻辑机理,并使用中国粮食主产区1211户农户的抽样调查数据和CMP方法进行实证检验。研究发现：①从三大主粮的总体估计来看,生产环节外包有助于中国粮食安全数量目标的实现,但不利于中国粮食安全环境目标的达成。在解决潜在的内生性问题后,这一结论依然成立;②从玉米、小麦和水稻的分样本估计来看,生产环节外包对中国粮食安全的多维影响在玉米和水稻生产中仍较为稳健,但对小麦的增产效果并不明显;从黑龙江、河南和湖南的分样本估计来看,生产环节外包对中国粮食安全的多维影响在三大粮食主产省均较为稳健。目前,从服务视角破解资源环境约束与农户行为约束暂未成为解决中国粮食安全环境问题的有效途径,仍需进一步推动生产环节外包服务市场的发育与完善,鼓励并引导外包供给主体的绿色生产导向。     

卓越教师评价标准比较及启示

卓越教师评价标准的建立与实施对教师专业发展起着重要的引导作用。美国、英国、澳大利亚、中国香港等国家或地区的卓越教师评价体系,在教师的知识结构、能力结构、教学成果、社区服务等方面具有一些共同特征,同时在教师能力结构、价值导向等方面又有各自的侧重。卓越教师评价标准应进一步体现卓越教师的实践专长,突出卓越教师作为教学变革的领导者,强化其对卓越教师培养过程的助推功能。