On a clear day you might see an environmental Kuznets curve

We shed some new light on the Environmental Kuznets curve (EKC) and show how it can be viewed as a particular form of equilibrium relationship, where technology and preference parameters determine the shape of the curve. In contrast to most of the literature on the EKC, we estimate a theoretically consistent model on long-run data (Swedish sulfur emission, covering the period 1900–2002). Furthermore, we test and date structural change. The model suggests four regimes, 1900–1918, 1919–1933, 1934–1967 and 1968–2002, generating four rather different patterns for pollution over time. The policy-conclusions are consonant with Pearce’s general view about the EKC: there is no theoretical presumption that it has an inverted U shape, nor should any country try to “grow out of the environmental problems” without analyzing the benefits and costs of so doing.     

宏观投资的影响因素与实证分析

在界定宏观投资的基础上，选择储蓄、价格、利润和利率等影响因素的代表变量，建立固定资产投资的理论模型；以1985－1999年为样本区间，采用SPSS统计分析软件包，对变量数据进行相关性分析和主成分分析，构建我国固定资产投资的回归模型；通过实证分析得出我国固定资产投资各影响因素的结论并给出相应的政策含义。     

基于主成分分析的多元线性回归用水量模型研究——以安徽省为例

用水量的准确预测对水资源规划具有重要意义。根据统计资料,选取了八项主要影响用水量变化的指标。按照主成分分析法原理,运用少数综合因子对影响用水量变化的原有八项指标进行了综合和简化,并研究其贡献率及综合效应;分析了用水量增长的特点,选用Logistic方程对综合因子进行回归分析;结合多元线性回归方法,建立了安徽省用水量模型;拟合结果表明,模型具有较高的精度;运用该模型,对安徽省2010年的用水量进行了预测;为水资源规划与管理提供参考依据。     

ML– and semiparametric estimation in logistic models with incomplete covariate data

ML–estimation of regression parameters with incomplete covariate information usually requires a distributional assumption regarding the concerned covariates that implies a source of misspecification. Semiparametric procedures avoid such assumptions at the expense of efficiency. In this paper a simulation study with small sample size is carried out to get an idea of the performance of the ML–estimator under misspecification and to compare it with the semiparametric procedures when the former is based on a correct assumption. The results show that there is only a little gain by correct parametric assumptions, which does not justify the possibly large bias when the assumptions are not met. Additionally, a simple modification of the complete case estimator appears to be nearly semiparametric efficient.     

玻壳合格率及质量成本对策

本文从数理统计入手，给出了玻壳生产中更换产品前后合格率的关系公式，并和实际统计值进行了比较，有较好的符合，为科学量化分析提供了工具。并据此分析，不同尺寸的玻壳产品，当池炉系统的质量水平下降时，它们的合格率的差别也在扩大，并量可能会使得原先利润相对高的产品变得利润相对低。通过合理地计划产品品种的生产，可以获得更多的利润，降低单位成本。同时也阐明原有的新产品质量目标设定方法的不合理性，给出了质量目标设定的科学依据。     

企业集团母子公司财务控制系统构建研究

企业集团是以产权关系为纽带 ,由众多企业法人共同组成的联合体。企业集团母子公司财务控制系统是企业集团核心管理内容之一。笔者通过自身的工作经验并结合理论研究认为 :企业集团母子公司财务控制系统是由财务人员控制系统、财务制度控制系统、财务目标控制系统和财务信息控制系统等构建的有机整体 ,企业集团管理当局应提供良好的人文环境和机制环境 ,保证其高效、及时、完整、良好地运行 ,保持企业集团的可持续发展 ,才能实现企业集团价值最大化     

Seasonal decomposition and forecasting of telecommunication data: A comparative case study

In this paper, forecasting models for the monthly outgoing telephone calls in a University Campus are presented. The data have been separated in the categories of international and national calls as well as calls to mobile phones. The total number of calls has also been analyzed. Three different methods, namely the Seasonal Decomposition, Exponential Smoothing Method and SARIMA Method, have been used. Forecasts with 95% confidence intervals were calculated for each method and compared with the actual data. The outcome of this work can be used to predict future demands for the telecommunications network of the University.     

An effective going concern prediction model for the sustainability of enterprises and capital market development

The purpose of this study is to construct a two-stage effective and innovative going concern prediction model to predict going concern doubt for the sustainability of enterprises and capital market development. Samples of this study are the companies listed on the Taiwan Stock Exchange or the Taipei Exchange, totalling 196 companies and including 49 companies with going concern doubt and 147 normal companies (with no going concern doubt). The data are taken from the Taiwan Economic Journal (TEJ) and the Market Observation Post System during the period from 2001 to 2016 (totalling 16 years). This study adopts a two-stage way to construct the going concern prediction models. In Stage I, the traditional statistical method of stepwise regression (SR) and the data mining technique artificial neural network (ANN) are applied to select the important variables. In Stage II, two decision tree algorithms (data mining techniques): classification and regression tree (CART) and C5.0 are used to establish the prediction models. The results show that the SR + CART model has the highest going concern prediction accuracy, with an overall accuracy of 87.42%.     

Bayesian assessment of dimensionality in reduced rank regression

We consider Bayesian inference about the dimensionality in the multivariate reduced rank regression framework, which encompasses several models such as MANOVA, factor analysis and cointegration models for multiple time series. The fractional Bayes approach is used to derive a closed form approximation to the posterior distribution of the dimensionality and some asymptotic properties of the approximation are proved. Finite sample properties are studied by simulation and the method is applied to growth curve data and cointegrated multivariate time series.     

Web数据挖掘中XML技术的应用研究

随着网络技术的发展,网上的信息资源越来越丰富,怎样对Web上海量的数据信息进行深层次的应用成了当今数据库技术的研究热点。文章针对Web上数据的特点和目前Web数据挖掘存在的挑战,结合XML语言的技术特点,主要探讨了XML技术在Web数据挖掘中的重要应用。