Modeling the demand reduction input-output (I-O) inoperability due to terrorism of interconnected infrastructures.

Interdependency analysis in the context of this article is a process of assessing and managing risks inherent in a system of interconnected entities (e.g., infrastructures or industry sectors). Invoking the principles of input-output (I-O) and decomposition analysis, the article offers a framework for describing how terrorism-induced perturbations can propagate due to interconnectedness. Data published by the Bureau of Economic Analysis Division of the U.S. Department of Commerce is utilized to present applications to serve as test beds for the proposed framework. Specifically, a case study estimating the economic impact of airline demand perturbations to national-level U.S. sectors is made possible using I-O matrices. A ranking of the affected sectors according to their vulnerability to perturbations originating from a primary sector (e.g., air transportation) can serve as important input to risk management. For example, limited resources can be prioritized for the "top-n" sectors that are perceived to suffer the greatest economic losses due to terrorism. In addition, regional decomposition via location quotients enables the analysis of local-level terrorism events. The Regional I-O Multiplier System II (RIMS II) Division of the U.S. Department of Commerce is the agency responsible for releasing the regional multipliers for various geographical resolutions (economic areas, states, and counties). A regional-level case study demonstrates a process of estimating the economic impact of transportation-related scenarios on industry sectors within Economic Area 010 (the New York metropolitan region and vicinities).     

A decomposition technique for quantifying real process performance

A decomposition technique for quantifying the impacts of changes in product mix and process performance on aggregate process-related indicators is presented. Through application of the technique, the real performance of a process can be quantified. Changes in real performance over time can be monitored to provide useful information for process evaluation and production planning. Two case studies, one related to the aggregate defective rate for an assembly line of an integrated circuit fabrication plant and the other to the aggregate inventory turnover for a tyre distribution company, are presented to illustrate the application of the technique.     

受教育程度与城镇居民收入不平等—基于基尼系数的分解研究

基于2008年中国综合社会调查的数据,本文运用基尼系数分解的方法研究城镇居民受教育程度对收入不平等的影响。基于回归的不平等分解研究发现受教育程度是导致城镇居民职业收入不平等的最主要因素。对基尼系数的亚组分解研究发现受教育程度不同的人群之闻的收入不平等对总体收入不平等的贡献率为8.65％,城镇居民职业收入不平等主要表现为各个受教育程度人群内部的收入不平等。分地区来看,中西部地区受教育程度较低的人群其组内差距的贡献率要远高于东部地区。实证研究的结果表明,提供平等的受教育机会、缩小受教育程度的不平等、加大对中西部地区义务教育的投入可以有效缩小收入不平等。     

A Decomposition of Pearson–Fisher and Dzhaparidze–Nikulin Statistics and Some Ideas for a More Powerful Test Construction

An explicit decomposition on asymptotically independent distributed as chi-squared with one degree of freedom components of the Pearson–Fisher and Dzhaparidze–Nikulin tests is presented. The decomposition is formally the same for both tests and is valid for any partitioning of a sample space. Vector-valued tests, components of which can be not only different scalar tests based on the same sample, but also scalar tests based on components or groups of components of the same statistic are considered. Numerical examples illustrating the idea are presented.     

中国城镇家庭收入增长益贫性形成机制研究

 借助社会福利函数对益贫式增长测度的可分解性,结合中国健康与营养调查（CHNS）提供的家庭就业率、劳动参与率、劳动报酬率、劳动时间等微观数据,追溯居民收入形成的劳动力市场特征要素,将居民收入和各劳动力市场特征的效用性、公平性与增长的损益相结合,应用要素分解模型阐释中国新世纪以来城镇家庭收入增长的益贫性及其形成机制,由此得到更具针对性的收入益贫式增长政策启示。     

与收入相关的老人健康不平等及其分解——基于中国城镇和农村的经验研究

本文使用“中国老年人健康长寿影响因素调查”（CLHLS）数据,测度了中国老人健康不平等程度,重点计算了收入、婚姻状况、居住安排等因素对健康不平等的贡献。回归基础上的集中系数及其分解结果显示：我国存在亲富人的健康不平等,高收入人群的健康状况更好;城镇地区,健康不平等主要的贡献因素为收入、婚姻状况、医疗保险、经常锻炼,居住安排对健康不平等的贡献为负。农村地区,收入因素对于健康不平等的贡献最大,这就意味着消除农村健康不平等的关键是要降低收入不平等。在城镇和农村地区医疗保险的不平等程度更甚,进一步强化了健康不平等。因此如果政策想要降低健康不平等,首先要降低穷人获得医疗保险的经济门槛,增加医疗保健服务的可及性。     

宏观经济因素对房地产价格的长短期影响

本文将购房者、房产商与中央银行纳入统一的模型当中,对房价的影响因素进行理论建模,然后拓展了传统的向量自回归模型长短期分解技术,研究了利率、通货膨胀率、汇率、土地价格以及经济增长率对房价的长期和短期影响。研究表明,利率上升对房价具有长期的负向效应,短期内会加剧房价的波动;通胀预期在长期内促使资金流入房地产行业,对房价会产生推动作用,短期内,通胀促使房地产企业加快投资速度,房屋供给增加预期引起房价下降的冲击;人民币升值在长短期内均与房价上涨存在正向作用;在当前的经济和房地产发展阶段,经济增速提高时,对房地产业的投资和投机具有一定的抑制作用;土地价格长期来看推动房价上涨,短期内对房价影响的传导较慢。     

基于CDM模型的信息服务业和制造业创新过程比较

海淀科技园是全国高技术产业和技术创新的中心,是中央政府追求建设的技术创新资源转化成产业创新能力的全国示范区,其中信息服务业是其龙头产业。本文在CDM的分析框架下,基于海淀科技园企业年报的微观数据,对信息服务业创新过程与制造业进行比较研究, 挖掘促进两个产业创新的关键要素,总结制造业和信息服务业内在的创新机理,并为两个产业的创新政策制定提供有效参考。研究发现：在信息服务业中新产品产出倾向与企业规模呈倒U型关系,而制造业中创新规模效益显著;信息服务业的知识密集特征显著,而制造业并不显著;信息服务业中国有企业从创新投入到创新产出的转化效率低下,而制造业中国有企业在创新投入阶段就表现出创新动力不足的问题。     

贫困缺口总指数的构造、分解与应用

本文构造了一个新贫困指数 ,通过对 指数的因素分解及衍生指数的构造,提出了一些重要贫困指标的预测和推算办法。基于CHNS1991-2011年跨度20年的8轮调查数据进行实证分析,结果表明,我国农村近20年来总贫困缺口率呈现年均6.39%的缩减率,其贡献全部来自贫困人口总规模递减这一因素的影响,而另外两个因素,即平均贫困缺口水平和贫困差异度则呈现年均小幅上升趋势,表明减贫质量不容乐观;以现有减贫模式对我国农村2020年的平均贫困缺口水平、贫困不平等程度、贫困规模等指标进行预测显示,减贫目标依然任重道远;提出了采用精准减贫,重心在于提升贫困人口获取收入的能力和缩小贫困不平等程度的相关建议。