Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models

In this paper we describe the use of modern numerical integration methods for making posterior inferences in composed error stochastic frontier models for panel data or individual cross- sections. Two Monte Carlo methods have been used in practical applications. We survey these two methods in some detail and argue that Gibbs sampling methods can greatly reduce the computational difficulties involved in analyzing such models.     

钢铁企业三类含铁物料的协同采购研究

钢铁企业生产中,需要三种含铁物料精矿粉、富矿粉和块矿。以降低含铁物料采购成本为目标,建立了基于性能和价格的含铁物料采购模型。模型主要约束包括：铁量约束,各类含铁物料用量约束,高炉碱度约束,以及采购数量约束。数值模拟中要求含铁物料含铁量应该满足企业铁产量要求,各类含铁物料采购量控制在基准期钢铁企业实际采购量的5%以内,高炉碱度约束转化为基准期CaO,MgO,SiO2的数量约束。通过实际月度数据的模拟计算,能够为企业降低采购成本23.3万元,取得了明显经济效益。     

全站仪在工程测量中的精度与误差分析

电子全站仪是光电测距仪、电子经纬仪和微处理器的集成,它能在测站上同时测量、计算显示及记录各种测量数据,在工程测量中得到广泛应用。本文结合全站仪在工程测量中的应用,谈谈降低测量误差的几种方法。     

Does the Capitalization of Development Costs Improve Analyst Forecast Accuracy? Evidence from the UK

It has been documented that investments in Research and Development (R&D) are associated with increased errors and inaccuracy in earnings forecasts made by financial analysts. These deficiencies have been generally attributed to information complexity and the uncertainty of the future benefits of R&D. This paper examines whether the capitalization of development costs can reduce analyst uncertainty about the future economic outcome of R&D investments, provide outsiders with a better matching of future R&D‐related revenues and costs, and therefore promote accuracy in analyst forecasts. UK data is used, because accounting rules in the United Kingdom permitted firms to conditionally capitalize development costs even before the introduction of the International Financial Reporting Standards. The choice to expense R&D rather than conditionally capitalize development costs is found to relate positively to signed analyst forecast errors. This finding is robust to controlling for the influence of other factors that may affect errors, as well as for the influence of R&D investments on forecast errors. The decision to capitalize versus expense is not observed to have a significant influence on analyst forecast revisions. The findings are interpreted as evidence that the choice to capitalize as opposed to expense may help to reduce deficiencies in analyst forecasts; hence, is informative for users of financial statements. Increased informativeness is expected to have repercussions for the effectiveness with which analysts produce earnings forecasts, and, as a result, market efficiency.     

Extrapolation‐based Bandwidth Selectors: A Review and Comparative Study with Discussion on Bivariate Applications

Cross‐validation is a widely used tool in selecting the smoothing parameter in a non‐parametric procedure. However, it suffers from large sampling variation and tends to overfit the data set. Many attempts have been made to reduce the variance of cross‐validation. This paper focuses on two recent proposals of extrapolation‐based cross‐validation bandwidth selectors: indirect cross‐validation and subsampling‐extrapolation technique. In univariate case, we notice that using a fixed value parameter surrogate for indirect cross‐validation works poorly when the true density is hard to estimate, while the subsampling‐extrapolation technique is more robust to non‐normality. We investigate whether a hybrid bandwidth selector could benefit from the advantages of both approaches and compare the performance of different extrapolation‐based bandwidth selectors through simulation studies, real data analyses and large sample theory. A discussion on their extension to bivariate case is also presented.     

Effects of Using Mean Scores in Regression Models: An Example From Environmental Psychology

Multiple regression analysis with grouped data is often used as a method for exploring environmental preferences, the preferred unit for measurement in such analyses is mean scores rather than individual scores.Although this procedure allows us to reduce the potential for error in measuring different variables and, as a consequence of this, improves the reliability of the technique, it also produces some additional, undesirable effects. The latter include artificial increases in R² values which give the impression that a high degree of fit has been achieved for the regression model. Indeed, this goodness fit often appears to be better than that which could have been achieved by using individual scores. Further, given that different studies operate with differing numbers of subjects in their groups, the R² scores which result from the analyses of these groups are not directly comparable.In the following discussion, we demonstrate how any value, other than zero for correlations between variables, can be increased, at will, by simply expanding the number of subjects in each group. We present the specialised formulae used for quantifying this increase and offer a warning about the purely relative nature of any study which bases its conclusions on models of regression analysis using grouped data.     

基于3PL_Hub的电信运营商库存管理技术研究

随着电信运营商之间的竞争逐渐加剧,为取得竞争优势,电信运营商也已开始与供应商、物流企业合作,采用3PL_Hub模式进行库存管理,降低供应链成本。但因行业不同,电信运营商基于3PL_Hub的库存管理运作模式与技术都与传统制造业有所不同。为此作者研究了电信运营商基于3PL_HUB的协同物流组织与运作模式构建、基于3PL_HUB协同运作下补货决策技术及3PL_Hub协同下IT支撑系统构建等用以支承电信运营商基于3PL_Hub库存管理的关键技术,并在中国电信部分省公司的协同物流建设应用。     

基于Mediator/Wrapper的VMI系统的研究

供应商管理库存（VMI）是一种新的供应链库存管理方法,通过应用VMI,可以提高企业的运作水平,降低供应商和生产商、零售商的成本.然而,在电子商务环境下,供应商与生产商或零售商是多对多的关系,VMI系统的数据间的通信变得十分庞大复杂,信息的管理也变得很困难.为此,本文提出使用Java和XML开发基于Mediator/Wrapper的VMI系统,通过Mediator构建一个以客户应用层、中介器层和数据源层三层VMI系统,使用XML作为中介器层的数据的标准以及客户应用层和中介器层的接口,并提供统一的描述数据的结构的框架,以便在Web上部署,同时Wrapper可以解决多个供应商和零售商之间的信息异构问题.     

Utilising Recent Advancements in Techniques for the Analysis of Incomplete Multivariate Data to Improve the Data Quality Management of Current Academic Research

This paper discusses the importance of managing data quality in academic research in its relation to satisfying the customer. This focus is on the data completeness objectivedimension of data quality in relation to recent advancements which have been made in the development of methods for analysing incomplete multivariate data. An overview and comparison of the traditional techniques with the recent advancements are provided. Multiple imputation is also discussed as a method of analysing incomplete multivariate data, which can potentially reduce some of the biases which can occur from using some of the traditional techniques. Despite these recent advancements in the analysis of incomplete multivariate data, evidence is presented which shows that researchers are not using these techniques to manage the data quality of their current research across a variety of academic disciplines. An analysis is then provided as to why these techniques have not been adopted along with suggestions to improve the frequency of their use in the future. Source-Reference. The ideas for this paper originated from research work on David J. Fogarty's Ph.D. dissertation. The subject area is the use of advanced techniques for the imputation of incomplete multivariate data on corporate data warehouses.     

清单计价模式下的工程造价控制

随着工程项目竞争压力的逐步扩大,很多的企业开始寻求工程造价控制的新方法,在保障工程质量的前提下最大限度的降低成本,提高企业竞争力和经济效益。清单计价模式下的工程造价控制有效控制了工程的造价,开始广泛应用于工程造价控制管理。     

电网无功补偿装置的应用

在电力系统中,电压问题不仅是一个供电质量问题,而且是关系到系统安全和经济运行的重要问题。近年来企业普遍利用电线网的无功补偿,提高电网的功率因数,降低供电线路的电流,减少了线损,取得了较好的效果。但不同的补偿方式,在实际中的补偿装置仍有所差异。本文对此进行了探讨。     

风险评估——我国消费品安全管理新趋势

消费品安全事关人民身心健康,风险评估作为一种能有效降低消费品安全风险的方法,已经在国外得到了运用。本文通过分析消费品安全风险评估的必要性、原则和基本内容,提出了推进我国消费品安全风险评估的对策。     

Robust forecast combinations

Forecast outliers commonly occur in economic, financial, and other areas of forecasting applications. In the literature of forecast combinations, there have been only a few studies exploring how to deal with outliers. In this work, we propose two robust combining methods based on the AFTER algorithm (Yang, 2004a). Our approach utilizes robust loss functions in order to reduce the influence of outliers. Oracle inequalities for certain versions of these methods are obtained, which show that the combined forecasts automatically perform as well as the best individual among the pool of original forecasts. Systematic simulations and data examples show that the robust methods outperform the AFTER algorithm when outliers are likely to occur and perform on par with AFTER when there are no outliers. Comparison of the robust AFTERs with some commonly used combining methods also shows their potential advantages.     

Do city climate plans reduce emissions?

More than 600 local governments in the US are developing climate action plans that lay out specific measures to reduce emissions from municipal operations, households and firms. To date, however, it is unclear whether these plans are being implemented or have any causal effects on emissions. Using data from California, I provide the first quantitative analysis of the impacts of climate plans. I find that cities with climate plans have had far greater success in implementing strategies to reduce greenhouse gas emissions than their counterparts without such plans. For example, they have more green buildings, spend more on pedestrian and bicycle infrastructure, and have implemented more programs to divert waste from methane-generating landfills. I find little evidence, however, that climate plans play any causal role in this success. Rather, citizens’ environmental preferences appear to be a more important driver of both the adoption of climate plans and the pursuit of specific emission reduction measures. Thus, climate plans are largely codifying outcomes that would have been achieved in any case.     

Do Better Wages Reduce Crime? A Research Note

A bstract . Recent research has called into question theoretical and empirical findings demonstrating a deterrent effect of punishment. Also challenged has been the view that improved employment opportunities help to reduce participation in illegitimate activities. This research note summarizes newly published econometric findings revealing that better wages and employment indeed do appear to reduce individual recidivism rates, at least in the major data set studied. The data are drawn from the Baltimore LIFE experiment. Maximum likelihood methods are used to estimate the probability of recidivism one year after release from prison and the probability of avoiding rearrest or "survival" each month after release from prison. It is found that higher average weekly wages are associated with lower recidivism and higher survival rates. In contrast, no evidence is found to confirm a deterrent effect of punishment. [Complete documentation is published in S. L. Myers, Jr "Estimating the Economic Model of Crime: Employment vs. Punishment Effects,".     

基于PLC和组态王的水塔水位自动监控系统

水位的测量和控制在日常生活中有着广泛的应用。本文采用PLC实现信号的采集与控制,应用组态王软件对接收到的信号进行数据处理,实现水塔水位显示、报警信息显示、实时曲线、历史曲线显示,使得水泵在水塔水位过低的时候自动工作抽水,水位到达上限值时自动停止抽水。该系统在提高劳动生产率,降低能耗等方面具有重要的现实意义。     

基于GPS的司机运行行为管理系统

目前,GPS系统已经广泛应用于监控运输中的物流车辆定位,但因为路况环境复杂,GPS系统传回的信息无法记录车辆运输途中的真实行驶行为。文章以运输车司机的行驶行为为研究对象,借助GPS系统传回的大量数据,应用数据仓库技术和数据挖掘思想,通过对司机运行路线、使用燃油量与路径上的行驶行为、实际路线与计划路线的挖掘分析,提取评价测量行驶行为的指标体系,以实现对司机运输行为的激励,降低物流企业运作成本。     

Wealth dynamics: reducing noise in panel data

Although the asset data from the Health and Retirement Study (HRS) is of very high quality, there is sufficient noise to frustrate attempts to study saving behaviour by examining wave‐to‐wave change in wealth. In this research, we attempt to reduce noise by means of reactive‐dependent interviewing in which respondents with large inexplicable changes in assets between 1998 and 2000 are called back by HRS interviewers, presented with their prior reports and asked to reconcile the data. We achieved reconciliation for 1255 households (2479 net‐worth components) and, as a result, the variance in measured change for the entire sample of 11,583 households with the same financial respondents in both waves was cut in half. The empirical validity of the data also appears to have been improved. The correlation of gross change in net worth and income, for instance, increased from an insignificant negative to a highly significant positive value. Although reconciliation of large asset changes marginally improves the goodness of fit of multivariate models, there remains sufficient noise in the asset‐change data to require analysts to employ additional methods to reduce the influence of outliers. Copyright © 2006 John Wiley & Sons, Ltd.     

Nonparametric independence feature screening for ultrahigh-dimensional survival data

With the explosion of digital information, high-dimensional data is frequently collected in prevalent domains, in which the dimension of covariates can be much larger than the sample size. Many effective methods have been developed to reduce the dimension of such data recently, however, few methods might perform well for survival data with censoring. In this article, we develop a novel nonparametric feature screening procedure based on ultrahigh-dimensional survival data by incorporating the inverse probability weighting scheme to tackle the issue of censoring. The proposed method is model-free and hence can be implemented for extensive survival models. Moreover, it is robust to heterogeneity and invariant to monotone increasing transformations of the response. The sure screening property and ranking consistency property are also established under mild conditions. The competence and robustness of our method is further confirmed through comprehensive simulation studies and an analysis of a real data example.     

基于大数据时代下企业推进财务信息化的研究

目前,计算机技术及信息统计技术已经得到了广泛的应用,并且大数据统计分析技术逐渐完善,也广泛应用在各行各业当中。对于财务管理工作来说,信息化技术以及大数据技术的应用,为预算编制、成本控制提供了十分丰富的数据资源,也有效减少了信息统计分析的工作量,数据分析的准确性也得到了有效的提升。大数据技术的应用,进一步推进了财务精细化管理的应用与发展。