A new look at Markov processes of G/M/1-type

We present a new method for deriving the stationary distribution of an ergodic Markov process of G/M/1-type in continuous-time, by deriving and making use of a new representation for each element of the rate matrices contained in these distributions. This method can also be modified to derive the Laplace transform of each transition function associated with Markov processes of G/M/1-type.     

我国企业FDI逆向知识转移效能评估模型构建

我国企业在发达国家FDI激增成为近年来的趋势,以创新资产寻求为动机的FDI更关注子公司逆向知识转移的效能。对影响逆向知识转移的因素已有很多学者进行了深入研究,在进行梳理的基础上,总结归纳出影响逆向知识转移效能的四大类因素,即母公司因素、子公司因素、双方关系因素、知识因素,运用网络层次分析法赋予各因素权重,构建可定量评估逆向知识转移效能的模型,最后据此提出我国企业提高逆向知识转移效能的建议。     

政府性基金征收的正当程序研究 ——基于民航发展基金的个案分析

政府性基金的设立,为解决改革开放初期基础设施投上发挥了政策性作用。然而,随着时代的变迁与市场经济模式的完善,作为时代产物的政府性基金,其合法性、合理性与透明度均存在着质疑。选择以民航发展基金为个案,对民航发展基金的由来与发展、征收的使用和制度规范以及设立程序进行阐述与分析不难发现,民航发展基金在前置程序、立法程序、征收标准法律依据、实施程序等方面存在着正当法律程序的偏差,致使其合法性受到质疑。因此,政府性基金的设立,应该在前置程序、程序立法、实施程序、纠纷解决正当程序诸方面做出制度性安排。     

桥塞坐封过程仿真模拟研究

桥塞作为井下封层技术的关键设备,由于它施工工序少、周期短、卡封位置准确而得到了广泛应用。针对设计的可钻式非金属桥塞坐封过程开展模拟研究,涉及弹塑性材料接触、超弹性材料接触和非金属材料动态断裂的非线性动力学问题,利用有限元法建立该桥塞全尺寸模型和所有部件之间的广义接触关系,通过有限元模拟动态坐封过程获得桥塞各部件运动变形特性、桥塞与套管之间的密封特性和动态坐封力等数据,该桥塞坐封完成时,坐封机构部件轴向位移110 mm,坐封力约45 kN。模拟坐封也为进一步优化该型桥塞的结构和评估坐封性能提供了理论依据,对该型桥塞的推广应用奠定了基础。     

灌装包装生产线效率评估系统的设计

针对国内一部分食品企业灌装包装生产线难以量化生产线效率的现状,提出了一套切实有效的生产线效率评估系统。通过评估设备速度V-曲线,以现代信息化技术为基础,提取出关键设备的停机记录,其中包含了停机的起始时间、终止时间、时长、分类、机台和原因等几大关键项内容,然后对内外部因素造成的各类时间损失进行准确量化评估,从而构建以总资产利用率、线毛产出率、设备综合利用率和线效率4项指标为衡量标准的一套生产线效率评估系统。本系统实现了灌装包装生产线数字化过程,整体透视出企业的综合管理能力、部门之间的协调配合能力、设备运行能力和故障处理能力。基于此数字化效率评估系统,可以分析停机成因,识别出影响生产线效率的核心要素,通过针对性的优化手段,达到提高效率的目的,实现降低成本和提高利润的业务目标。     

The k-factor GARMA Process with Infinite Variance Innovations

In this article, we develop the theory of k-factor Gegenbauer Autoregressive Moving Average (GARMA) process with infinite variance innovations which is a generalization of the stable seasonal fractional Autoregressive Integrated Moving Average (ARIMA) model introduced by Diongue et al. (2008 Diongue, A.K., Guégan, D. (2008). Estimation of k-Factor GIGARCH Process: A Monte Carlo Study. Communications in Statistics-Simulation and Computation 37:2037–2049.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). Stationarity and invertibility conditions of this new model are derived. Conditional Sum of Squares (CSS) and Markov Chains Monte Carlo (MCMC) Whittle methods are investigated for parameter estimation. Monte Carlo simulations are also used to evaluate the finite sample performance of these estimation techniques. Finally, the usefulness of the model is corroborated with the application to streamflow data for Senegal River at Bakel.     

Conditional VAR and Expected Shortfall: A New Functional Approach

We estimate two well-known risk measures, the value-at-risk (VAR) and the expected shortfall, conditionally to a functional variable (i.e., a random variable valued in some semi(pseudo)-metric space). We use nonparametric kernel estimation for constructing estimators of these quantities, under general dependence conditions. Theoretical properties are stated whereas practical aspects are illustrated on simulated data: nonlinear functional and GARCH(1,1) models. Some ideas on bandwidth selection using bootstrap are introduced. Finally, an empirical example is given through data of the S&P 500 time series.     

Robust Inference for Near-Unit Root Processes with Time-Varying Error Variances

The autoregressive Cauchy estimator uses the sign of the first lag as instrumental variable (IV); under independent and identically distributed (i.i.d.) errors, the resulting IV t-type statistic is known to have a standard normal limiting distribution in the unit root case. With unconditional heteroskedasticity, the ordinary least squares (OLS) t statistic is affected in the unit root case; but the paper shows that, by using some nonlinear transformation behaving asymptotically like the sign as instrument, limiting normality of the IV t-type statistic is maintained when the series to be tested has no deterministic trends. Neither estimation of the so-called variance profile nor bootstrap procedures are required to this end. The Cauchy unit root test has power in the same 1/T neighborhoods as the usual unit root tests, also for a wide range of magnitudes for the initial value. It is furthermore shown to be competitive with other, bootstrap-based, robust tests. When the series exhibit a linear trend, however, the null distribution of the Cauchy test for a unit root becomes nonstandard, reminiscent of the Dickey-Fuller distribution. In this case, inference robust to nonstationary volatility is obtained via the wild bootstrap.