股改对价计算依据与公允对价计算原则探讨

通过对22家股改试点代表性公司对价计算依据的逐一分析，其对价依据可归纳为保值法、退款法、让利法、保价法、直接法和待定法6种。其中前4种是可以推广的主要方法。那么针对试点过程中对价依据存在的问题如何加以改进则是值得研究的课题。     

连续监测方法在全国碳市场应用的挑战与对策

全国碳市场启动在即,探索适合的碳排放量化方法具有重要现实意义。本文介绍了国内外连续监测方法的应用现状,比较分析了基于核算的方法与基于连续监测的方法的优缺点,剖析了在我国碳市场中应用连续监测方法面临的问题和挑战。本文建议在推广连续监测方法之前,需要选取试点设施获取实际应用经验,建立监测、报告、核查和认证等一系列配套的支撑体系,并解决与传统污染物监测设备的一致性问题以及与核算方法确定的历史排放数据的一致性问题。     

Are the Methods of the Net Present Value Rate and Net Annual Value Rate the Effective Scheme Comparison Methods

As for the dispute about the best-choosing method of mutually-exclusive scheme and index selection, this text proves that there is an error to make a point that using net present value rate or net annual value rate, the most scientific and effective method is chain-system differential analysis and the most short-cutting method is the method of net annual value, to select the NA V maximum scheme.     

Comparing benefit estimates from travel cost and contingent valuation using confidence intervals for Hicksian welfare measures

An approach to determining whether benefit estimates derived from the travel cost method and contingent valuation method are statistically different is presented. Unlike past comparisons compensating variation is estimated for both methods. Benefit comparisons are made more rigorous by use of confidence intervals which are developed using the same Krinsky and Robb simulation technique for both valution mothods. The techniques are applied to deer hunting in California. While point estimates of benefits from both truncated and untruncated adjusted travel cost methods are lower than the contingent valuation method, the confidence intervals on the untruncated travel cost method do overlap the contingent valution method benefit estimates.     

Unveiling the core technology structure for companies through patent information

Patent information provides an objective and public source to understand core technologies of companies. In this paper, a method is proposed for identifying core technology capabilities for a company in the semiconductor industry. The method is built on the patent similarity and K-means clustering algorithm. The indirect relations among the patents in the complex industry are considered in the method. In addition, the age of the patent is taken into account to avoid identifying aged core patents. The method is demonstrated by exploring the core technology capabilities that support the platform technology portfolio of the Taiwan Semiconductor Manufacturing Company (TSMC).     

Consumption norms,trickle-down and the video/microwave syndrome

A new method is presented for investigating empirically the presence or not of consumption norms in the ownership of durables amongst different socioeconomic groups (although the method is more generally applicable to any situation in which a number of characteristics, and not just durables, may be acquired in a specific sequence). In order to illustrate the method, some results are presented for the ownership of durables as sampled by the National Readership Survey for 1985 and 1990. As a further application of the method, particular attention is paid to the changing incidence of ownership of videos and microwaves. Both theoretically and empirically, the trickle-down model of consumer choice is critically assessed and found to be wanting.     

A Poisson ridge regression estimator

The standard statistical method for analyzing count data is the Poisson regression model, which is usually estimated using maximum likelihood (ML) method. The ML method is very sensitive to multicollinearity. Therefore, we present a new Poisson ridge regression estimator (PRR) as a remedy to the problem of instability of the traditional ML method. To investigate the performance of the PRR and the traditional ML approaches for estimating the parameters of the Poisson regression model, we calculate the mean squared error (MSE) using Monte Carlo simulations. The result from the simulation study shows that the PRR method outperforms the traditional ML estimator in all of the different situations evaluated in this paper.     

A novel nonlinear value-at-risk method for modeling risk of option portfolio with multivariate mixture of normal distributions

This paper proposes a novel nonlinear model for calculating Value-at-Risk (VaR) when the market risk factors of an option portfolio are heavy-tailed. A multivariate mixture of normal distributions is used to depict the heavy-tailed market risk factors and accordingly a closed form expression for the moment generating function that can reflect the change in option portfolio value can be derived. Moreover, in order to make use of the correlation between the characteristic function and the moment generating function, Fourier-Inversion method and adaptive Simpson rule with iterative algorithm of numerical integration into the nonlinear VaR model for option portfolio are applied for calculation of VaR values of option portfolio. VaR values of option portfolio obtained from different methods are compared. Numerical results of Fourier-Inversion method and Monte Carlo simulation method show that high accuracy VaR values can be obtained when risk factors have multivariate mixture of normal distributions than when they have normal distributions. Moreover, VaR values obtained by using the Fourier-Inversion method are not obviously different from VaR values obtained by using Monte Carlo simulation when market risk factors have normal distributions or multivariate mixture of normal distributions. However, the speed of computation is obviously faster when using Fourier-Inversion method, than when using Monte Carlo simulation method. Besides, Cornish Fisher method is faster and simpler than Monte Carlo simulation method or Fourier-Inversion method. However, this method does not offer high accuracy and cannot be used to calculate VaR values of option portfolio when market risk factors have heavy-tailed distributions.     

“互联网+”下大规模个性化定制产品的三元证据融合配置方法

为了解决“互联网+”大规模个性化定制下存在的产品配置方案规模大、参与定制主体数量多等问题,首先针对客户异质性特点,结合产品参数约束和实例推理给出了产品配置备选方案的界定方法,然后基于基本信度分配函数构建了能够从企业、消费者、客户3类主体中有效提取经验证据、评价证据、偏好证据的三元证据获取方法,并依据证据推理方法构建了可以对同时存在可靠性和重要性两种性质的三元证据进行融合决策的方法步骤,最后以红领西服定制为样本模拟了提出方法的具体操作过程,验证了方法的应用可行性。     

广义变系数模型的B样条估计及R软件实现

结合基函数逼近技术以及拟似然方法,对广义变系数模型,提出了一个B样条估计方法,并结合R统计软件,对所提出的估计方法给出了一个基于R软件的实现过程。数据模拟表明所提出的B样条估计方法以及R软件的实现过程均是可行的。     

The Effect of Protest Votes on the Estimates of WTP for Use Values of Recreational Sites

Contingent valuation studies are often characterized by a considerable number of protest responses, which may cause selectivity bias on the final estimates for WTP. Sample selection models can detect and – if necessary – correct selectivity bias. In economic applications where the relevant dependent variable is continuous, sample selection models are generally estimated using Heckman's 2-step method rather than the FIML estimator. Either method has its own drawback: computational complexity for the FIML method, susceptibility to collinearity problems for the 2-step method. Using data on valuation of forest resources for recreational use, we analyse the performance of the two estimators. In this application, given the presence of some collinearity, the FIML is preferred to the 2-step method. A procedure is outlined to deal with selectivity problems in similar settings.     

Determining the environmental effects of indirect subsidies: integrated method and application to the Netherlands

The term ‘environmentally damaging subsidies’ covers all sorts of direct and indirect subsidies with negative consequences for the environment. This article presents a method to determine the environmental impact of these subsidies. It combines a microeconomic framework with an environmental impact module. The method is particularly useful for analysing indirect subsidies. These are often hidden, and therefore, not recognized as subsidies. Use of the method will provide a basis for formulating corrective policy. The method is applied to several important subsidies in the Netherlands, in agriculture, energy and transport sectors. The results reveal large environmental effects, which deserve serious attention from policy makers. To illustrate the specific features of the method, its application to a particular subsidy, namely the exemption of excise taxes on aviation fuels, is presented in full detail.     

经济混沌研究的非线性科学方法

本文根据混沌理论和分形理论,对经济混沌特征研究的非线性科学方法进行了必要的总结,具体包括经济序列时间分维的计算方法、关联维的计算方法、Lyapunov指数和Kolmogorov熵的计算方法以及R/S分析方法.在此基础上,对上述方法在经济序列混沌特征的非线性研究中的未来应用进行了必要的展望.     

百分位数回归及应用研究

在进行定量分析时,最小二乘法已经成为一种可信赖的工具。但是运用最小二乘法的条件比较高,在实际问题中,完全满足条件的情况并不多见,那么在应用时就难以得到无偏的、有效的参数估计量。针对上述问题,以OILPLUS公司取暖用燃油消耗的分布为主要研究对象,在进行参数估计时,应用百分位数回归方法,既可以看到采用百分位数回归方法与采用最小二乘法得到的模型显著不同,又可以得到比最小二乘法更为丰富的信息。     

油田开发调整方案的多指标群体综合评价方法及应用

本文结合油田开发调整方案优选的多指标特征及群体评价特征,提出了一个多指标群体综合评价方法。该方法在序关系分析法的基础上,通过定义基于向量的诱导有序加权平均(V-IOWA)算子来确定专家群体的指标权重,进而得到专家群体的方案综合评价结果。最后,给出一个应用实例以说明该方法的有效性。     

The measurement of interindustry linkages : Key sectors in the Netherlands

The present paper proposes a new method for the measurement of sectoral interdependencies. It is shown that the elements of the eigenvector corresponding to the dominant eigenvalue of a matrix may be used for measuring interindustry linkages. In an empirical study, the eigenvector method is compared with the two methods that are usually applied. Linkage indicators and key sectors are determined for the Netherlands for the entire post-war period 1948–1984. The results show that the eigenvector method provides a better measurement of the interindustry linkages, that it is useful in detecting clusters of sectors, and that it is sensitive to changes in the structure of the economy.     

RIDGE ESTIMATORS FOR PROBIT REGRESSION: WITH AN APPLICATION TO LABOUR MARKET DATA

In this paper we propose ridge regression estimators for probit models since the commonly applied maximum likelihood (ML) method is sensitive to multicollinearity. An extensive Monte Carlo study is conducted where the performance of the ML method and the probit ridge regression (PRR) is investigated when the data are collinear. In the simulation study we evaluate a number of methods of estimating the ridge parameter k that have recently been developed for use in linear regression analysis. The results from the simulation study show that there is at least one group of the estimators of k that regularly has a lower mean squared error than the ML method for all different situations that have been evaluated. Finally, we show the benefit of the new method using the classical Dehejia and Wahba dataset which is based on a labour market experiment.     

基于LiDAR点云的景观空间“绿视率” 量化分析方法研究

LiDAR点云在景观空间定量研究中具有重要作用, 而目前对其运用多局限于景观空间的信息采集,为探讨如何基 于LiDAR点云数据展开景观空间的相关形态量化分析,选取 了过往研究中多局限于二维图像分析的“绿视率”指标进行具 体分析讨论,将其量化分析方法归为空间数据采集、处理、建 模、分析4个主要环节。以南京河西某住区绿地为研究案例, 选取其中4处具有典型差异的空间节点对基于LiDAR点云数据 的“绿视率”分析方法加以运用,发现该方法具有“分析高效 性”“数据全面性”“结果准确性”3个方面的突出优势及运 用价值,对后续风景园林领域研究与实践的高质量、精细化发 展具有积极作用。     

盐酸左氧氟沙星片微生物限度检测的方法学建立和验证

目的建立了盐酸左氧氟沙星片微生物限度的检测方法,并对方法学进行验证。方法采用低速离心结合薄膜过滤手段建立盐酸左氧氟沙星片的微生物限度检测方法。结果细菌计数及控制菌用薄膜过滤法检查,霉菌及酵母菌计数用常规法检查。结论该方法准确、可靠,适用于左氧氟沙星片的微生物检查。     

Valuing environmental factors in cost-benefit analysis using data envelopment analysis

Environmental cost-benefit analysis (ECBA) is used for the social evaluation of investment projects and policies that involve significant environmental impacts. Economic valuation of environmental impacts forms one of the critical steps of ECBA. We develop a new method for this purpose, which does not require price estimation for environmental impacts using stated or revealed preference methods. Our approach is based on data envelopment analysis (DEA), which is modified to ECBA by using absolute shadow prices instead of relative prices. We also discuss how the method can be used for sensitive analysis in ECBA. We illustrate the method by means of a hypothetical numerical example.