A Bias–Reduced Log–Periodogram Regression Estimator for the Long–Memory Parameter

In this paper, we propose a simple bias–reduced log–periodogram regression estimator, ^d_r, of the long–memory parameter, d, that eliminates the first– and higher–order biases of the Geweke and Porter–Hudak (1983) (GPH) estimator. The bias–reduced estimator is the same as the GPH estimator except that one includes frequencies to the power 2k for k=1,…,r, for some positive integer r, as additional regressors in the pseudo–regression model that yields the GPH estimator. The reduction in bias is obtained using assumptions on the spectrum only in a neighborhood of the zero frequency. Following the work of Robinson (1995b) and Hurvich, Deo, and Brodsky (1998), we establish the asymptotic bias, variance, and mean–squared error (MSE) of ^d_r, determine the asymptotic MSE optimal choice of the number of frequencies, m, to include in the regression, and establish the asymptotic normality of ^d_r. These results show that the bias of ^d_r goes to zero at a faster rate than that of the GPH estimator when the normalized spectrum at zero is sufficiently smooth, but that its variance only is increased by a multiplicative constant. We show that the bias–reduced estimator ^d_r attains the optimal rate of convergence for a class of spectral densities that includes those that are smooth of order s≥1 at zero when r≥(s−2)/2 and m is chosen appropriately. For s>2, the GPH estimator does not attain this rate. The proof uses results of Giraitis, Robinson, and Samarov (1997). We specify a data–dependent plug–in method for selecting the number of frequencies m to minimize asymptotic MSE for a given value of r. Some Monte Carlo simulation results for stationary Gaussian ARFIMA (1, d, 1) and (2, d, 0) models show that the bias–reduced estimators perform well relative to the standard log–periodogram regression estimator.     

Robustness to non-normality and autocorrelation of individuals control charts

This paper studies the effects of non-normality and autocorrelation on the performances of various individuals control charts for monitoring the process mean and/or variance. The traditional Shewhart X chart and moving range (MR) chart are investigated as well as several types of exponentially weighted moving average (EWMA) charts and combinations of control charts involving these EWMA charts. It is shown that the combination of the X and MR charts will not detect small and moderate parameter shifts as fast as combinations involving the EWMA charts, and that the performana of the X and MR charts is very sensitive to the normality assumption. It is also shown that certain combinations of EWMA charts can be designed to be robust to non-normality and very effective at detecting small and moderate shifts in the process mean and/or variance. Although autocorrelation can have a significant effect on the in-control performances of these combinations of EWMA charts, their relative out-of-control performances under independence are generally maintained for low to moderate levels of autocorrelation.     

Aggregation of isotropic autoregressive fields

This note constitutes a corrigendum to the article of Azomahou [2009, Memory properties and aggregation of spatial autoregressive models. J. Statist. Plann. Inference, 139, 2581-2597]. The aggregation of isotropic four nearest neighbors autoregressive models on the lattice Z², with random coefficient, is investigated. The spectral density of the resulting random field is studied in details for a large class of law of the AR coefficient. Depending on this law, the aggregated field may exhibit short memory or isotropic long memory.     

我国工业污染物的影子价格估计

 污染物的影子价格体现了污染物的边际减排成本。本文采用二次型方向性距离函数和 2003-2008年我国284个地级及以上城市工业部门数据,对废水、SO2和烟尘等三种污染物的影子价格进行了估计。结果发现,2003-2008年期间,废水、SO2、烟尘的影子价格或边际减排成本分别为0.0178万元/吨、5.158万元/吨和4.597万元/吨。SO2排污权交易价格相比污染减排成本偏低,影响了排污权交易市场的有效运作。污染物的影子价格在不同城市具有较大差异,这种差异性能够在一定程度上被污染排放规模、监管强度和污染治理的规模经济性等因素所解释。     

基于SFA的中国银行业成本效率实证研究

本文基于随机边界模型,假定成本误差项服从截断正态分布的前提下,估算我国18家银行2001-2007年的成本效率。结果显示我国商业银行成本效率总体偏低,经营绩效落后于美国银行业,且在观测期内没有明显改善;样本银行成本效率与资产规模等因素没有显著联系,国有银行平均效率水平与股份制银行大致持平,均低于合资银行;各银行成本效率随时间推移而趋同,集中化趋势明显。     

Efficient ascertainment schemes for maximum likelihood estimation

While well chosen sampling schemes may substantially increase efficiency of observational studies, some sampling schemes may instead decrease efficiency. Rules of thumb how to choose sampling schemes are only available for some special cases. In this paper we provide tools to compare efficiencies, and cost adjusted efficiencies, of different sampling schemes, in order to facilitate this choice. The method can be used for both categorical and continuous outcome variables. Some examples are presented, focusing on data from ascertainment sampling schemes. A Monte Carlo method is used to overcome computational issues wherever needed. The results are illustrated in graphs.     

总体分高低成本下的复合多目标抽样方案的设计与应用

文章依据复合多目标抽样的基本原理,提出了高低成本指标广义相关下的多目标复合抽样方法的设计方案,探讨了依广义相关性进行分类的抽样方案在精度和成本方面的优良性,并进行了实际比较与应用。     

加强高职院校成本会计实践教学的几点思考

成本会计是高职高专院校会计电算化、财务管理等经济管理类专业的职业核心课程,作为会计学科体系中的一个子系统,有着相对独立的理论和方法体系,是一门集理论性和实践操作性都较强的学科。高职院校在教学中虽然重视了实践教学环节,但由于缺乏一套较完善的实践教学方案和创新实施手段,实践教学流于形式,效果不佳。因此不断强化、创新实践教学,使其更加科学、规范,应成为提高成本会计实践教学质量的当务之急。     

我国刑事法律援助制度的几个问题及完善——以国际刑事司法准则为视角

法律援助制度是法律程序公正的体现,通过实证考察法律援助的实施状况,从立法方面提出了法律援助范围过窄、可能判处死刑案件的援助阶段缺失以及实践中法律援助的责任主体不适当三个问题,继而研究国际刑事司法准则在这三个问题上设立的国际标准,通过比较提出对我国刑事法律援助制度改善的一些建议。