南汇边滩细颗粒泥沙动水沉降的实验研究

细颗粒泥沙在盐水中的絮凝沉降是河流泥沙向海输送过程中在河口区发生的重要现象之一。文章根据室内环形水槽实验对南汇边滩泥沙由盐度和含沙量这两种因素在不同的流速条件下的沉降特性进行了研究。该实验结果对该区域实施围垦工程有实际意义。     

破解伯川德悖论的新视角--修改前提下的古诺模型分析

通过对一般动态古诺模型的分析，指出其未解开反而加强了伯川德悖论的原因，在于其假定前提离现实经济实际太远，为此，对假定前提进行了修正：寡占厂商进入行业市场的成本递增，产品的边际成本不为零，经过数学推导，获得了以下结论：递增的进入成本限定了寡头数目；边际成本的存在使市场容量减小；寡头竞争不会轻易恢复完全竞争。     

不压井起下作业装置在海上边际油田开发中的应用介绍

为了适应边际油田的开发,改善修井机重量大、作业区域宽、整体重心高的弊端,主要介绍了不压井起下作业装置(以下简称Snubbing装置),并对不同形式的应用进行优缺点分析,进一步提出Snubbing装置在渤海边际油田开发的应用方案。     

Social marginal cost pricing and second best alternatives in partnerships for transport infrastructures

According to the economic theory, if all the first-best conditions are met, social optimality involves the prices to be set equal to social marginal costs. When it is not possible to set prices equal to social marginal costs, due to the presence of constraints within the transport sector or distortions elsewhere in the economy, the theory suggests corrections to the SMC principle (second-best alternatives). But the implementation of second best alternatives can give rise to serious problems when transferred from theory to practice. This chapter will discuss in particular the problems that might rise when investment cost are included (totally or partially) in the social marginal costs rules, and in particular when private operators are involved.     

“南海自安装试采平台”主电站方案比选研究

"南海自安装试采平台"是一种多功能的油田开发设施,主要用于滚动开放南海北部湾海域多个年产量小于25万m3、开发年限少于5年、周围无依托设施的边际小油气田,主电站是影响该平台技术方案和运营成本的关键设备。文中根据该平台的功能和用电负荷,结合拟开发边际油田的燃料来源情况,从技术性与经济性两方面比较论证适用于"南海自安装试采平台"的主电站方案。     

城市客运交通工具碳排放效率差异——以襄阳市为例

为准确测度城市客运工具碳排放效率的差异,探寻多元出行和碳减排双赢的改进路径,本文构建涵盖车辆存量、道路、土地、能源及环境 5 大要素体系,利用三阶段超效率 SBM-DEA(Slacks-Based Measure)模型和SFA(Stochastic Frontier Approach)方法,测度城市客运工具碳排放效率,并厘清政策和外生环境因素对投入要素冗余的影响;构建效率贡献度和边际效应模型分析投入产出要素的效率贡献度及其边际效应。基于襄阳市的案例表明：7种客运工具的碳排放效率呈传统公共交通(含巡游车)大于共享交通大于私人交通的差异化态势;外生环境因素中,优化能源结构能显著减少能源资源的多余消耗,交通工具的便捷性对消除多余投入具有显著积极作用。效率贡献度结果反映碳排放效率提升路径的异质性：车辆规模过剩是制约共享交通碳排放效率的主要原因,规模每减少10%,效率分别提高12.0%(网约车)和19.8%(共享电踏车)。清洁能源发展对私家车碳排放效率的提升作用较大,清洁比例每增加10%,碳排放效率平均提高8.9%。在现阶段公交优先发展水平下,公交车平均运行速度每增加1 km∙h-1 ,碳排放效率提高0.201。并从技术和管理两方面提出改善碳排放效率的建议和措施。     

基于均值异质性随机参数Logit模型的城市道路事故驾驶员受伤严重程度研究

驾驶员事故严重程度诱因分析对减少伤亡事故具有重要意义,以往研究假定影响变量为固定参数容易导致参数估计及研究推论出现偏差,据此本文基于均值异质性的随机参数Logit模型深入研究城市道路事故驾驶员受伤严重程度.使用2015—2019年发生在贵阳市的道路交通事故数据,综合考虑驾驶员、车辆、道路、环境特征等潜在影响因素,同时利...     

The cost of second best pricing and the value of risk premium

Private provision of public infrastructure (PPP) is meant to give incentives to increased efficiency in construction as well in operation and maintenance of the infrastructure e.g. within the transport sector. Efficiency is not only (private) economic efficiency, but also social efficiency e.g. social marginal cost pricing of use of the infrastructure.Is it possible to design contracts concerning payment mechanisms and financial instruments for transport infrastructure that will stimulate social efficiency and optimal allocation of risks between parties? The paper discusses whether different targets can be met and whether compromises may lead to acceptable second best solutions.PPP implies an opportunity to let the user-payment give desired incentives in the form of Social Marginal Cost Pricing (SMCP). A PPP project is a set of contracts and agreements between several parties, including the Government, the private contractor, subcontractors, banks and infrastructure users. These contracts should be designed to give the right incentives to the parties to achieve optimal risk allocation and utilising of resources.Long contract-periods are a common feature of PPPs. The paper examines the way that financial solutions should be designed to achieve the goals for the PPP-projects concerning economic and social efficiency. The expected size and variation of the income stream from the project will influence the loan conditions offered by banks concerning interest rates, guarantees and repayment and also the ability to attract investors. The balance between equity and loans again influences the conditions of the loans. An additional problem is asymmetric information between parties. The private contractor usually knows more about the task than the Government (hidden knowledge), and the Government cannot have full knowledge of the efforts of the contractor (hidden actions).     

A latent variable representation of count data models to accommodate spatial and temporal dependence: Application to predicting crash frequency at intersections

This paper proposes a reformulation of count models as a special case of generalized ordered-response models in which a single latent continuous variable is partitioned into mutually exclusive intervals. Using this equivalent latent variable-based generalized ordered response framework for count data models, we are then able to gainfully and efficiently introduce temporal and spatial dependencies through the latent continuous variables. Our formulation also allows handling excess zeros in correlated count data, a phenomenon that is commonly found in practice. A composite marginal likelihood inference approach is used to estimate model parameters. The modeling framework is applied to predict crash frequency at urban intersections in Arlington, Texas. The sample is drawn from the Texas Department of Transportation (TxDOT) crash incident files between 2003 and 2009, resulting in 1190 intersection-year observations. The results reveal the presence of intersection-specific time-invariant unobserved components influencing crash propensity and a spatial lag structure to characterize spatial dependence. Roadway configuration, approach roadway functional types, traffic control type, total daily entering traffic volumes and the split of volumes between approaches are all important variables in determining crash frequency at intersections.     

On accommodating spatial dependence in bicycle and pedestrian injury counts by severity level

This paper proposes a new spatial multivariate count model to jointly analyze the traffic crash-related counts of pedestrians and bicyclists by injury severity. The modeling framework is applied to predict injury counts at a Census tract level, based on crash data from Manhattan, New York. The results highlight the need to use a multivariate modeling system for the analysis of injury counts by road-user type and injury severity level, while also accommodating spatial dependence effects in injury counts.