Three Corrected Score Tests for Generalized Linear Models with Dispersion Covariates

We develop three corrected score tests for generalized linear models with dispersion covariates, thus generalizing the results of Cordeiro , Ferrari and Paula (1993) and Cribari-Neto and Ferrari (1995) . We present, in matrix notation, general formulae for the coefficients which define the corrected statistics. The formulae only require simple operations on matrices and can be used to obtain analytically closed-form corrections for score test statistics in a variety of special generalized linear models with dispersion covariates. They also have advantages for numerical purposes since our formulae are readily computable using a language supporting numerical linear algebra. Two examples, namely, iid sampling without covariates on the mean or dispersion parameter oand one-way classification models, are given. We also present some simulations where the three corrected tests perform better than the usual score test, the likelihood ratio test and its Bartlett corrected version. Finally, we present a numerical example for a data set discussed by Simonoff and Tsai (1994) .     

会计师事务所与客户的双边匹配

以2013年至2018年A股上市公司及为其提供审计服务的国内会计师事务所为研究样本,基于双边匹配理论探讨了审计市场中会计师事务所与企业之间的匹配情况对审计质量和审计风险的影响。研究结果表明,综合实力较强的会计师事务所倾向于与综合实力较强的企业进行匹配,呈现出审计双方综合实力相当的一种正向类聚匹配：当双方匹配程度越高时,企业可操纵性应计利润较少,审计质量越高;同时,当审计双方匹配度越高时,审计风险越低。上述结果证实了审计市场上会计师事务所与客户匹配的有效性和重要性,并对通过双边匹配提高会计师事务所的审计质量、降低审计风险,为审计市场资源优化配置提供了理论指导。     

支撑战略转型的财务管理体系——以电信业为例

作为一种企业的战略,转型成功与否关键在于执行。财务管理是战略管理的执行层,支撑战略转型的财务管理体系必须上承企业宏观的战略规划目标,下达企业具体的作业实施。为此,以电信业的转型为例,指出财务管理体系首先要借助战略地图从企业愿景或战略目标出发,并以此为核心提出整合企业资源的财务目标,形成财务管理的行动方案;以作业成本管理为工具,正确反映不同成本核算对象对提升企业价值的贡献;最后通过平衡计分卡进行绩效衡量,找出能创造未来财务成果的关键性"绩效驱动因素",创建出相对于财务成果而言的所谓"领先引导指标",使财务管理跨越绩效衡量层次,直接进入了战略衡量层次。     

An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.     

基于管理有效性的物流企业绩效评价研究

鉴于传统绩效评价的局限性,在建立物流企业绩效评价体系的基础上,通过管理有效性的方法对我国27家物流企业2011-2012年间的数据进行管理绩效的实证分析,根据评价结果使企业认识到管理的差距与不足,同时验证了管理有效性的评价方法是对传统绩效评价的有效补充。     

Construction of D-optimal s 1 × s 2 × s 3 factorial designs using graph theory

In this paper, the maximum determinant of the associated 0-1 matrix in D-Optimal saturated main effect plans for 3× s_2 × s_3 factorials, is derived by the use of Graph theory and Combinatorics. The present work is related to a problem suggested by Chatterjee and Narasimhan (2002). Using the theoretical results, we also give the designs for s₃≥s₂ + 1. This research was supported by the State Scholarships Foundation of Greece.     

The impact of production offshoring on the skill composition of manufacturing firms: evidence from Italy

In this work we explore how the international outsourcing of production impacts the skill composition of employment within Italian manufacturing firms. In particular, our aim is to assess whether the choice to offshore production activities to cheap‐labour countries implies a bias in the employment of skilled workers relative to unskilled ones.

Using a balanced panel of firms covering the period 1995–2003, we set up a counterfactual analysis in which, by using a difference‐in‐differences propensity score matching estimator, we compare the dynamics of skill demand for treated and control firms while addressing the possible problem of selection bias.

Our results identify a ‘potential’ skill bias effect of production offshoring. In particular, we find that treated firms tend to show an upward shift in the skill ratio with respect to the counterfactual sample, but coefficients are not significantly different from zero. When we look at the elements of the skill ratio separately, we find that the skill bias is driven by a fall in the employment of production workers (blue collars), rather than by the increase in the employment of non‐production workers (white collars), thus providing further evidence on the unskilled labour‐saving nature of international outsourcing.     

社交指数、风险倾向与创业

创业不仅是经济持续增长的动力,也是新常态下我国经济增长方式转变的重要源泉。从个人社交指数和风险倾向着手,分析其对个人创业的影响,同时考虑政府干预、市场成熟度和产权保护水平对社交指数和风险倾向与创业之间的调节作用,并将个人特质和区域因素作为控制变量纳入分析框架,运用CGSS 3年的数据进行实证分析。结果表明,个人社交指数对创业具有正向影响,个人风险倾向对创业的影响存在区域异质性。在农村地区,个人风险倾向对创业活动具有正向影响,即风险倾向越高,创业概率越大;而在城镇,个人风险倾向对创业的影响为负。在制度环境层面,政府干预和市场成熟度对创业具有负向影响,产权保护水平与创业之间存在“倒U型”关系,制度环境对社交指数与创业之间的关系具有调节作用,较高政府干预力度和较低市场成熟度使社交指数与创业负相关,而产权保护水平的调节作用则较弱;制度环境对风险倾向的调节作用较弱。     

Schumpeter,Schumacher and the Greening of Technology

We propose a semantic patent claim analysis that can examine patents for possible infringements and identify which needs to be manually perused. So far, numerous approaches have been devised to systemise this burden, but have not been useful in practice because of a lack of consideration of semi-structure of patent claim data and claim element-based procedure of adjudicating patent infringement. At the heart of our method is a hierarchical keyword vector for representing the dependency relationships among claim elements (as well as unstructured textual information) and a tree matching algorithm for comparing claim elements of patents. A case study of the patents about DNA chip technology shows our method has considerable advantages in terms of accuracy and significance. We believe the suggested method could be employed in various research areas and serve as a starting point for developing more general models.     

Model uncertainty and asset return predictability: an application of Bayesian model averaging

We investigate model uncertainty associated with predictive regressions employed in asset return forecasting research. We use simple combination and Bayesian model averaging (BMA) techniques to compare the performance of these forecasting approaches in short-vs. long-run horizons of S&P500 monthly excess returns. Simple averaging involves an equally-weighted averaging of the forecasts from alternative combinations of factors used in the predictive regressions, whereas BMA involves computing the predictive probability that each model is the true model and uses these predictive probabilities as weights in combing the forecasts from different models. From a given set of multiple factors, we evaluate all possible pricing models to the extent, which they describe the data as dictated by the posterior model probabilities. We find that, while simple averaging compares quite favorably to forecasts derived from a random walk model with drift (using a 10-year out-of-sample iterative period), BMA outperforms simple averaging in longer compared to shorter forecast horizons. Moreover, we find further evidence of the latter when the predictive Bayesian model includes shorter, rather than longer lags of the predictive factors. An interesting outcome of this study tends to illustrate the power of BMA in suppressing model uncertainty through model as well as parameter shrinkage, especially when applied to longer predictive horizons.