桑弘羊经济立法思想探微

西汉中期,时为掌管封建中央财政事务大臣的桑弘羊在坚持先秦法家思想的基础上,先后推行和提出了大力发展官商,打击私商,实施盐铁专卖,均输平准等一系列的经济立法措施和财政政策,它是汉王朝社会经济方式由自由放任转向国家干预控制的重要转折,其思想对加强封建中央财政管理,充实封建国家财政收入和缓解社会财政危机发挥了重要的作用,其许多首创的理论和实践被后代各封建王朝的理财大臣看作是可望不可及的成功的财政典型,且为当时世界上不少国家所推崇和采用。研究这一中国古代法制史上的重要成果,对思考我们现实社会财政经济的改革发展有宝贵的借鉴意义。     

高精度渗碳控制方法

在采用电阻法直接测控碳势的方法中,提出了一种分段参数调节增量式PID算法,通过实际调试和理论推导表明,渗碳工艺过程控制具有控制超调量小、过渡时间短、精度高、软件实现方便等优点,稳定后碳势控制精度可达±0.03%。     

谈歌唱教学中的气息运用

歌唱教学中呼吸的运用十分重要,本文集作者多年教学经验,从正确运用呼吸控制音准及呼吸与情感变化,呼吸与歌曲内容的转化等几方面作以论述。     

Analytical approximations for iterated bootstrap confidence intervals

Standard algorithms for the construction of iterated bootstrap confidence intervals are computationally very demanding, requiring nested levels of bootstrap resampling. We propose an alternative approach to constructing double bootstrap confidence intervals that involves replacing the inner level of resampling by an analytical approximation. This approximation is based on saddlepoint methods and a tail probability approximation of DiCiccio and Martin (1991). Our technique significantly reduces the computational expense of iterated bootstrap calculations. A formal algorithm for the construction of our approximate iterated bootstrap confidence intervals is presented, and some crucial practical issues arising in its implementation are discussed. Our procedure is illustrated in the case of constructing confidence intervals for ratios of means using both real and simulated data. We repeat an experiment of Schenker (1985) involving the construction of bootstrap confidence intervals for a variance and demonstrate that our technique makes feasible the construction of accurate bootstrap confidence intervals in that context. Finally, we investigate the use of our technique in a more complex setting, that of constructing confidence intervals for a correlation coefficient.     

语言多样性、信息获取与分析师盈余预测质量

考察了语言多样性对分析师盈余预测质量的影响,以及这种影响如何因员工教育水平的不同而变化.基于中国上市公司的实证检验结果显示,语言多样性显著降低了分析师盈余预测质量,但是随着公司员工受教育水平提高,语言多样性对分析师盈余预测质量的负面影响有所减弱.进一步研究发现,分析师与CEO间的校友关系增强了员工教育水平对语言多样性与分析师盈余预测准确性之间关系的正向调节作用.研究结论一定程度上丰富了分析师私有信息获取及其影响机理以及社会关系等方面的文献,而且还可帮助投资者、监管者等利益相关方更好地理解分析师行为,促进资源合理配置,增强资本市场的有效性等方面具有一定的启示意义.     

Comparison of the effectiveness of forecasts obtained by means of selected probability functions with respect to forecast error distributions

The forecasting of sales in a company is one of the crucial challenges that must be faced. Nowadays, there is a large spectrum of methods that enable making reliable forecasts. However, sometimes the nature of time series excludes many well-known and widely used forecasting methods (e.g., econometric models). Therefore, the authors decided to forecast on the basis of a seasonally adjusted median of selected probability distributions. The obtained forecasts were verified by means of distributions of the Theil U² coefficient and unbiasedness coefficient.     

Estimation and Inference Procedures for Semiparametric Distribution Models with Varying Linear‐Index

More flexible semiparametric linear‐index regression models are proposed to describe the conditional distribution. Such a model formulation captures varying effects of covariates over the support of a response variable in distribution, offers an alternative perspective on dimension reduction and covers a lot of widely used parametric and semiparameteric regression models. A feasible pseudo likelihood approach, accompanied with a simple and easily implemented algorithm, is further developed for the mixed case with both varying and invariant coefficients. By justifying some theoretical properties on Banach spaces, the uniform consistency and asymptotic Gaussian process of the proposed estimator are also established in this article. In addition, under the monotonicity of distribution in linear‐index, we develop an alternative approach based on maximizing a varying accuracy measure. By virtue of the asymptotic recursion relation for the estimators, some of the achievements in this direction include showing the convergence of the iterative computation procedure and establishing the large sample properties of the resulting estimator. It is noticeable that our theoretical framework is very helpful in constructing confidence bands for the parameters of interest and tests for the hypotheses of various qualitative structures in distribution. Generally, the developed estimation and inference procedures perform quite satisfactorily in the conducted simulations and are demonstrated to be useful in reanalysing data from the Boston house price study and the World Values Survey.     

平稳性检验方法的有效性研究

平稳性检验是时间序列分析的重要研究内容,现有检验方法的性能缺乏系统的比较分析。文章从样本长度的视角研究平稳性检验方法的性能,采用ADF检验、PP检验、KPSS检验和LMC检验四种方法展开实证研究。仿真实验结果表明:时间序列数据长度会对检验方法的准确率产生明显的影响,数据长度较小时检验准确率偏低;数据长度增大时可以提升检验方法的准确率,但仍未能达到100%的上限值。当样本长度较小时,这些方法的检验统计量的渐进分布难以满足,因此其实际检验效果值得探究。样本长度是有限的,因此渐进分布检验方式的改进空间有限,新的检验方式值得探究。     

Combining forecasts of electricity consumption in China with time-varying weights updated by a high-order Markov chain model

Electricity consumption forecasting has been always playing a vital role in power system management and planning. Inaccurate prediction may cause wastes of scarce energy resource or electricity shortages. However, forecasting electricity consumption has proven to be a challenging task due to various unstable factors. Especially, China is undergoing a period of economic transition, which highlights this difficulty. This paper proposes a time-varying-weight combining method, i.e. High-order Markov chain based Time-varying Weighted Average (HM-TWA) method to predict the monthly electricity consumption in China. HM-TWA first calculates the in-sample time-varying combining weights by quadratic programming for the individual forecasts. Then it predicts the out-of-sample time-varying adaptive weights through extrapolating these in-sample weights using a high-order Markov chain model. Finally, the combined forecasts can be obtained. In addition, to ensure that the sample data have the same properties as the required forecasts, a reasonable multi-step-ahead forecasting scheme is designed for HM-TWA. The out-of-sample forecasting performance evaluation shows that HM-TWA outperforms the component models and traditional combining methods, and its effectiveness is further verified by comparing it with some other existing models.