中国县级政府间财力差距：1993-2003年

 摘　　要:本文利用1993-2003年中国县级地区的财政数据，借鉴收入分配文献中发展出来的地区子集和收入来源不平等分解法，对县级政府财力差距进行了分析，发现中国县级政府财力差距十分悬殊，且财力不均等存在上升趋势；大部分财力不均等是由组内差异解释的，地区间差距对不均等的贡献相对较小；上级财政转移支付不但没有起到均等县级财力的作用，反而拉大了财力差异，特别是在分税制改革后，转移支付造成了近一半的县级财力差异     

Interpretation of the coefficient of determination of an ANOVA model as a measure of polarization

In this paper, it is demonstrated that coefficient of determination of an ANOVA linear model provides a measure of polarization. Taking as the starting point the link between polarization and dispersion, we reformulate the measure of polarization of Zhang and Kanbur using the decomposition of the variance instead of the decomposition of the Theil index. We show that the proposed measure is equivalent to the coefficient of determination of an ANOVA linear model that explains, for example, the income of the households as a function of any population characteristic such as education, gender, occupation, etc. This result provides an alternative way to analyse polarization by sub-populations characteristics and at the same time allows us to compare sub-populations via the estimated coefficients of the ANOVA model.     

On the Multivariate Upcrossings Index

The multivariate extremal index function is a measure of the clustering among the extreme values of a multivariate stationary sequence. In this article, we introduce a measure of the degree of clustering of upcrossings in a multivariate stationary sequence, called multivariate upcrossings index, which is a multivariate generalization of the concept of upcrossings index. We derive the main properties of this function, namely the relations with the multivariate extremal index and the clustering of upcrossings.

Imposing general local and asymptotic dependence restrictions on the sequence or on its marginals we compute the multivariate upcrossings index from the marginal upcrossings indices and from the joint distribution of a finite number of variables. A couple of illustrative examples are exploited.     

中国农村地区间收入极化及构成变动——一个新的动态分解公式及其应用

对新发展的极化测度指标及其分解公式做进一步的分解,并分析了中国农村地区间人均纯收入的极化及其变动。结果表明:2006年之前极化程度波动上升,随后逐年下降;从收入来源的角度来看,工资性收入对极化程度的贡献最大,而财产性收入和转移性收入对极化程度的贡献逐年提高;收入变动的结构效应会导致极化程度的提高,而集中效应会导致极化程度的降低。     

Inequality indices and the starshaped principle of transfers

The evaluation of income distributions is usually based on the Pigou-Dalton (PD) principle which says that a transfer from any people to people who have less decreases economic inequality, i.e., increases the social evaluation index. We introduce two weaker principles of transfers which refer to a parameter θ. With the new principles, only those PD transfers increase the social evaluation index which take from the class of incomes above θ and give to the class below θ. The relative positions of individuals remain unchanged, and either no individual may cross the line θ (principle of transfers about θ) or some may do who have been situated next to it (starshaped principle of transfers at θ). θ may be a given constant, a function of mean income, or a quantile of the income distribution. The classes of indices which are consistent with these transfers are completely characterized, and examples are given.     

Accent on Teaching Materials

Estimation of covariance components in the multivariate random-effect model with nested covariance structure is discussed. There are two covariance matrices to be estimated, namely, the between-group and the within-group covariance matrices. These two covariance matrices are most often estimated by forming a multivariate analysis of variance and equating mean square matrices to their expectations. Such a procedure involves taking the difference between the between-group mean square and the within-group mean square matrices, and often produces an estimated between-group covariance matrix that is not nonnegative definite. We present estimators of the two covariance matrices that are always proper covariance matrices. The estimators are the restricted maximum likelihood estimators if the random effects are normally distributed. The estimation procedure is extended to more complicated models, including the twofold nested and the mixed-effect models. A numerical example is presented to illustrate the use of the estimation procedure.     

Asymptotic Confidence Intervals for a New Inequality Measure

This work aims at assessing, by simulation methods, the performance of asymptotic confidence intervals for Zenga's new inequality measure. The results are compared with those obtained on Gini's measure, perhaps the most widely used index for measuring inequality in income and wealth distributions. Our findings show that the coverage accuracy and the size of the confidence intervals for the two measures are very similar in samples from economic size distributions.     

益贫式增长与社会机会分配

 目前的益贫式增长测度方法局限于从收入或支出角度考察增长是否益贫,没有足够重视教育、医疗、保险等社会服务机会分配的益贫性。本文用基于社会机会函数（SOF）构造机会指数（OI）和机会益贫指数（PIO）的方法测度中国教育和医疗服务机会分配的益贫性及其动态变化,采用CHNS住户调查数据（2000-2009年）进行了实证研究,以此作为考察增长益贫性以及制订和执行更具针对性的益贫策略的有力依据。     

An asymptotic confidence interval for the process capability index Cpm

Abstract

The use of indices as an estimation tool of process capability is long-established among the statistical quality professionals. Numerous capability indices have been proposed in last few years. C_pm constitutes one of the most widely used capability indices and its estimation has attracted much interest. In this paper, we propose a new method for constructing an approximate confidence interval for the index C_pm. The proposed method is based on the asymptotic distribution of the index C_pm obtained by the Delta Method. Under some regularity conditions, the distribution of an estimator of the process capability index C_pm is asymptotically normal.     

A hypothesis testing procedure for the evaluation on the lifetime performance index of products with Burr XII distribution under progressive type I interval censoring

ABSTRACT

It is a very important topic these days to assessing the lifetime performance of products in manufacturing or service industries. Lifetime performance indices C_L is used to measure the larger-the-better type quality characteristics to evaluate the process performance for the improvement of quality and productivity. The lifetimes of products are assumed to have Burr XII distribution. The maximum likelihood estimator is used to estimate the lifetime performance index based on the progressive type I interval censored sample. The asymptotic distribution of this estimator is also developed. We use this estimator to build the new hypothesis testing algorithmic procedure with respect to a lower specification limit. Finally, two practical examples are given to illustrate the use of this testing algorithmic procedure to determine whether the process is capable.     

Average kappa coefficient: a new measure to assess a binary test considering the losses associated with an erroneous classification

The weighted kappa coefficient of a binary diagnostic test (BDT) is a measure of performance of a BDT, and is a function of the sensitivity and the specificity of the diagnostic test, of the disease prevalence and the weighting index. Weighting index represents the relative loss between the false positives and the false negatives. In this study, we propose a new measure of performance of a BDT: the average kappa coefficient. This parameter is the average function of the weighted kappa coefficients and does not depend on the weighting index. We have studied three asymptotic confidence intervals (CIs) for the average kappa coefficient, Wald, logit and bias-corrected bootstrap, and we carried out some simulation experiments to study the asymptotic coverage of each of the three CIs. We have written a program in R, called ‘akcbdt’, to estimate the average kappa coefficient of a BDT. This program is available as supplementary material. The results were applied to two examples.     

A note on the asymptotic distribution of the process capability index C pmk

Process capability indices have been widely used to evaluate the process performance to the continuous improvement of quality and productivity. The distribution of the estimator of the process capability index C _pmk is very complicated and the asymptotic distribution is proposed by Chen and Hsu [The asymptotic distribution of the processes capability index C _pmk , Comm. Statist. Theory Methods 24(5) (1995), pp. 1279–1291]. However, we found a critical error for the asymptotic distribution when the population mean is not equal to the midpoint of the specification limits. In this paper, a correct version of the asymptotic distribution is given. An asymptotic confidence interval of C _pmk by using the correct version of asymptotic distribution is proposed and the lower bound can be used to test if the process is capable. A simulation study of the coverage probability of the proposed confidence interval is shown to be satisfactory. The relation of six sigma technique and the index C _pmk is also discussed in this paper. An asymptotic testing procedure to determine if a process is capable based on the index of C _pmk is also given in this paper.     

Weak Instrumental Variables Models for Longitudinal Data

This article considers the estimation and testing of a within-group two-stage least squares (TSLS) estimator for instruments with varying degrees of weakness in a longitudinal (panel) data model. We show that adding the repeated cross-sectional information into a regression model can improve the estimation in weak instruments. Moreover, the consistency and limiting distribution of the TSLS estimator are established when both N and T tend to infinity. Some asymptotically pivotal tests are extended to a longitudinal data model and their asymptotic properties are examined. A Monte Carlo experiment is conducted to evaluate the finite sample performance of the proposed estimators.     

中国居民收入分布专题实证研究——居民收入分布变迁测度及其影响因素分解

基于核密度估计方法,给出居民收入分布变迁测度及其影响因素分解的相对收入分布方法。使用中国健康和营养调查的微观居民收入数据,实证分析中国居民收入分布及其变迁的特征、过程及其影响因素。实证结果显示:中国居民收入分布变迁的速度与经济体制改革进程相对应;经济增长因素是引起居民收入分布变迁的主要因素,在提高总体居民收入水平的同时加剧了居民收入分布的极化程度;收入分配因素对居民收入分布变迁的作用相对较弱,但有一定的减贫或缩小居民收入差距作用。     

Analysis of Double Single Index Models

Motivated from problems in canonical correlation analysis, reduced rank regression and sufficient dimension reduction, we introduce a double dimension reduction model where a single index of the multivariate response is linked to the multivariate covariate through a single index of these covariates, hence the name double single index model. Because nonlinear association between two sets of multivariate variables can be arbitrarily complex and even intractable in general, we aim at seeking a principal one‐dimensional association structure where a response index is fully characterized by a single predictor index. The functional relation between the two single‐indices is left unspecified, allowing flexible exploration of any potential nonlinear association. We argue that such double single index association is meaningful and easy to interpret, and the rest of the multi‐dimensional dependence structure can be treated as nuisance in model estimation. We investigate the estimation and inference of both indices and the regression function, and derive the asymptotic properties of our procedure. We illustrate the numerical performance in finite samples and demonstrate the usefulness of the modelling and estimation procedure in a multi‐covariate multi‐response problem concerning concrete.     

Testing symmetry based on empirical likelihood

In this paper, we propose a general kth correlation coefficient between the density function and distribution function of a continuous variable as a measure of symmetry and asymmetry. We first propose a root-n moment-based estimator of the kth correlation coefficient and present its asymptotic results. Next, we consider statistical inference of the kth correlation coefficient by using the empirical likelihood (EL) method. The EL statistic is shown to be asymptotically a standard chi-squared distribution. Last, we propose a residual-based estimator of the kth correlation coefficient for a parametric regression model to test whether the density function of the true model error is symmetric or not. We present the asymptotic results of the residual-based kth correlation coefficient estimator and also construct its EL-based confidence intervals. Simulation studies are conducted to examine the performance of the proposed estimators, and we also use our proposed estimators to analyze the air quality dataset.     

社会审计功能发挥对企业稳健运营影响研究

社会审计有助于提高公司治理水平,治理水平高的公司其运营的稳健性水平也高。以2003-2014年沪、深两市A股上市公司为样本,利用主成分分析法合成了企业稳健运营的综合性指标,并在审计意见的基础上构建了社会审计功能发挥的代理变量,考察社会审计对企业稳健运营的影响。研究发现,社会审计有助于提高企业运营的稳健性。通过替换指标和改变估计方法后重新回归,研究结果依然不变。     

Large sample results for permutation tests of association

This paper deals with the asymptotics of permutation tests based on a certain rather general class of measures of association for R by C contingency tables, given marginal totals. This class includes the classical chi-square test, the T _b and γ indices of Goodman and Kruskall (1954) and the popular Rand (1971) index. The asymptotic distribution of this class of permutation tests for association is a weighted sum of non-central (gen-erally speaking) chi-squares. The formulae for the asymptotic moments of such tests are also given. If non-centrality holds under the null hypothe-sis of independence, the distribution in question converges to the normal distribution. The efficacies for such measures of association are obtained. Several applications are analysed in detail, including the above mentioned indices. Approximations to the permutation distribution are also discussed.     

Problems in estimating non-linear Engel parameters in the absence of appropriate grouped means and average elasticity of variable elasticity Engel functions

Household Expenditure Survey (HES) data are widely reported in grouped form for a number of reasons. Only within-group arithmetic means (AMs) of the household expenditures on various consumption items, total expenditure, income . and other variables are reported in the tabular form. However, the use of such within-group AMs introduces biases when the parameters of various commonly used non-linear Engel functions are estimated by the Aitken's generalized least squares (GLS) method. This is because the within-group geometric means (GMs)/harmonic means (HMs) are needed in order to estimate unbiased parameters of those non-linear Engel functions. Kakwani (1977) estimated the within-group GMs/HMs from the Kakwani-Podder (1976) Lorenz curve for Indonesian data. We have extended his method to estimate within-group GMs/HMs to a set of variables, based on a general type of concentration curve. It is shown that our estimated within-group GMs/HMs based on concentration curves are not entirely suitable for the Australian HES data. However, these GMs/HMs are then used to estimate Engel parameters for various non-linear Engel functions and it is seen that these elasticities are different for some items of certain non-linear Engel functions than those when the reported within-group AMs are used as proxies for within-group GMs/HMs in order to estimate those non-linear Engel functions. The concept of the average elasticity of a variable elasticity Engel function is discussed and computed for various Australian household consumption items. It is empirically demonstrated that the average elasticities are more meaningful than the traditional elasticity estimates computed at some representative values for certain functions.     

Extremal memory of stochastic volatility with an application to tail shape inference

We characterize joint tails and tail dependence for a class of stochastic volatility processes. We derive the exact joint tail shape of multivariate stochastic volatility with innovations that have a regularly varying distribution tail. This is used to give four new characterizations of tail dependence. In three cases tail dependence is a non-trivial function of linear volatility memory parametrically represented by tail scales, while tail power indices do not provide any relevant dependence information. Although tail dependence is associated with linear volatility memory, tail dependence itself is nonlinear. In the fourth case a linear function of tail events and exceedances is linearly independent. Tail dependence falls in a class that implies the celebrated Hill (1975) tail index estimator is asymptotically normal, while linear independence of nonlinear tail arrays ensures the asymptotic variance is the same as the iid case. We illustrate the latter finding by simulation.