Leontief逆矩阵和Ghosh逆矩阵性质应用的再研究北大核心CSSCI

本文首先总结了价值型Leontief逆矩阵、Ghosh逆矩阵和实物型Leontief逆矩阵的性质,回顾了这些性质在产出调整分析和价格调整分析中的一些应用,然后研究了这些性质在产出调整分析中关于投入乘数方面,以及在价格调整分析中关于产出乘数方面进一步的应用,结论是如果只有部门i的实物型最终产出增加(减少)而其余部门的不变,那么部门i的投入乘数一定不增加(不减少),而且至少存在一个部门i_0(i_0≠i)的投入乘数一定不减少(不增加);对偶地,如果只有部门j的增加值上升(下降)而其余部门的不变,那么部门j的产出乘数一定不增加(不减少),而且至少存在一个部门j_0(j_0≠j)的产出乘数一定不减少(不增加)。     

基于动态风险乘数调整的CPPI和TIPP策略研究

本文引入一个动态风险乘数调整因子,对CPPI和TIPP的风险乘数m进行动态调整,提出一种新的基于动态风险乘数调整的CPPI(D-CPPI)和TIPP(D-TIPP)策略,其中m由固定乘数变为随股价变动的动态乘数。在股价上涨时,动态乘数调整因子随之上涨,当股价下跌时,动态乘数调整因子随之下跌,由此起到股价上涨时扩大参与获利,股价下跌时更好的进行向下保护的目的。结合我国股市的实际数据,分析不同行情和不同影响因素下动态风险乘数调整的CPPI(D-CPPI)和TIPP(D-TIPP)策略的执行绩效,并与传统的CPPI和TIPP策略比较,结果显示基于动态风险乘数调整的CPPI(D-CPPI)和TIPP(D-TIPP)策略总体优于传统的CPPI和TIPP策略。     

服务业乘数效应与经济发展

<正>一、乘数理论与乘数效应1.乘数的定义。在宏观经济学中,乘数有广义上和狭义上两种含义:广义含义,是指均衡国民收入的变化量与引起这一变动的变量的变化量之间的比率。狭义含义,特指投资乘数,即在一定的边际消费倾向条件下,投资的增加(或减少)可导致国民收入和就业量若干倍的增加(或减少)。     

企业存货调整与中国财政政策的效力发挥

存货波动是宏观经济波动的重要组成部分,为此,企业存货调整将对宏观政策的效力发挥产生影响。本文在基准的新凯恩斯模型上,引入存货变量,分析中国财政政策的有效性。研究发现:(1)考虑存货变量之后,财政支出产出乘数的短期乘数变大,长期乘数变小;(2)财政支出增加会促进私人消费提高,同时短期挤出、长期挤入私人投资,但二者的总量效应微弱。基于不同存货持有动机和不同货币政策规则的模型检验,证实了上述判断的稳健性。接着,基于1995～2015年中国省际面板数据,采用VAR方法估计,本文发现,产出、居民消费与私人投资对财政支出的脉冲响应函数基本与存货模型的模拟结果匹配。由此,本文认为,当前财政政策的实施需要重视企业存货调整对政策效果的影响,政策的着力点应该在于创造有效消费需求、加快"去库存"。     

关于"教育问责制"的对话

对话者:G(教育学教授) M(中学校长) Q(教育局局长) 何谓"教育问责制" G:教育问责制是一个现代政治概念的演化物,是"岗位责任制"的追究制度. Q:教育问责制实际上是问责制在学校教育管理和教育行政过程中,对教育行政领导和学校校长及教师进行职、权与责的比照,强调教育效益.     

开放经济下的财政支出乘数研究——基于包含投入产出结构DSGE模型的分析

本文建立了一个含有投入产出框架的多部门DSGE模型,研究不同汇率制度下政府消费型与投资型支出对贸易部门和非贸易部门的影响。研究发现:第一,引入投入产出结构后,财政扩张将产生乘数放大效应与部门间联动(co-movement)效应;第二,相比于浮动汇率,固定汇率下的政府支出乘数更大,对消费与投资的挤出效应更小;第三,政府对非贸易部门的投资型与消费型支出将产生更强的乘数效应;第四,无论对于贸易部门与非贸易部门,政府投资型支出的乘数效应均大于消费型支出。     

上海股票市场"规模效应"的实证研究

"规模效应"是股票市场上一种重要的异常收益现象,反映了股票收益与公司规模之间的反向关系.选择沪市所有A股为样本,以流通市值来衡量公司的规模,验证了1997年1月～2002年12月间沪市股票(组合)的平均收益与公司规模之间具有明显的负相关关系.通过逐月横截面回归分析进一步检验了公司规模对股票收益的解释能力,证明了沪市"规模效应"的稳健性.上海股票市场"规模效应"产生的原因主要在于市场操纵和公司购并行为.     

基于风险与双渠道的全球供应链"超网络"均衡优化模型研究

在电子商务环境下,提出并分析了全球供应链"超网络"结构的概念、特点与功能.建立了包含传统分销(physical channel)和网络分销(internet channel)双重渠道、考虑供应风险(supply side risk)和需求风险(.demand siderisk)优化的、包含制造商、零售商和顾客在内的三层全球供应链"超网络"结构拓扑模型.运用有限空间变分不等式理论分析了三层决策主体各自的交易行为与多目标(利润最大化与风险最小化)最优化条件.推导出全球供应链"超网络"系统的均衡优化模型,并给出具体的算例进行求解.     

于成龙:"天下廉吏第一"

于成龙在清代顺治、康熙时期,素有"包(拯)孝肃、海(瑞)忠介"之清誉.他生于明万历四十五年(1617年),卒于清康熙二十三年(1684年),山西永宁(今离石)人.明崇祯年间,他曾考取过副榜贡生,倡导经世之学.清取代明而起后,他于顺治十八年(1661年)被提为广西罗城县知县,从此开始了其清正廉明的仕途生涯.此后,由于其政绩昭著,又屡被提升.     

规范书记用人的"桦甸实验"

变隐性权力为显性权力 从2002年开始,"科学规范与有效监督县(市)委书记用人权"试点在吉林桦旬市实施.在赋予书记干部调整动议权、提名推荐权、主持决策权和监督管理权的同时,为了防止干部任用动议行为的随意性,桦甸市进行了一系列的探索.     

Data envelopment analysis: Prior to choosing a model

In this paper, we address several issues related to the use of data envelopment analysis (DEA). These issues include model orientation, input and output selection/definition, the use of mixed and raw data, and the number of inputs and outputs to use versus the number of decision making units (DMUs). We believe that within the DEA community, researchers, practitioners, and reviewers may have concerns and, in many cases, incorrect views about these issues. Some of the concerns stem from what is perceived as being the purpose of the DEA exercise. While the DEA frontier can rightly be viewed as a production frontier, it must be remembered that ultimately DEA is a method for performance evaluation and benchmarking against best-practice. DEA can be viewed as a tool for multiple-criteria evaluation problems where DMUs are alternatives and each DMU is represented by its performance in multiple criteria which are coined/classified as DEA inputs and outputs. The purpose of this paper is to offer some clarification and direction on these matters.     

Non-oriented slack-based decompositions of profit change with an application to Taiwanese banking

A change in profit can originate from the output side and the input side. In the spirit of work by Tone [1] and follows Grifell-Tatjé and Lovell's [2], we propose a non-oriented slacks-based measure (SBM) model to decompose the change in the operating profit into various meaningful components: quantity effect and a price effect. The quantity effect can be decomposed into a productivity effect and an activity effect. The productivity effect is further decomposed into a technical effect and an operating efficiency effect. Both of them include an output side, which will result in a change in revenue and an input side which will result in a change in cost. The activity effect can be decomposed into a product mix effect, a resource mix effect and a scale effect. We illustrate our decompositions to the Taiwanese banking sector during the period 1994-2002 using the average of the base and current prices to evaluate these contributions. We find ignoring input side effects on the decomposition of profit changes would cause misleading results in managerial issues.     

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 systems simulation model of the Kenyan economy

This paper describes a systems simulation model of the national economy of Kenya. The model contains an input/output production component linked to a consumption component, disaggregated into nine income classes. Capital formation and government are integrated into the model as interactive elements. The model is demand driven and thus growth rates in the productive sectors are generated endogenously as a function of demand. The model has been used by the Kenyan Ministry of Finance and Economic Planning for forecasting and policy evaluation problems. A contributory factor in the successful implementation of the model is its ability to supply detailed quantitative forecasts which, in a developing country, are not readily available from routine sources. In addition, the model deals explicitly with income distribution and inflation consequences which are issues of current concern to local development planners.     

Modeling Uncertainties in Workforce Disruptions from Influenza Pandemics Using Dynamic Input‐Output Analysis

Influenza pandemic is a serious disaster that can pose significant disruptions to the workforce and associated economic sectors. This article examines the impact of influenza pandemic on workforce availability within an interdependent set of economic sectors. We introduce a simulation model based on the dynamic input‐output model to capture the propagation of pandemic consequences through the National Capital Region (NCR). The analysis conducted in this article is based on the 2009 H1N1 pandemic data. Two metrics were used to assess the impacts of the influenza pandemic on the economic sectors: (i) inoperability, which measures the percentage gap between the as‐planned output and the actual output of a sector, and (ii) economic loss, which quantifies the associated monetary value of the degraded output. The inoperability and economic loss metrics generate two different rankings of the critical economic sectors. Results show that most of the critical sectors in terms of inoperability are sectors that are related to hospitals and health‐care providers. On the other hand, most of the sectors that are critically ranked in terms of economic loss are sectors with significant total production outputs in the NCR such as federal government agencies. Therefore, policy recommendations relating to potential mitigation and recovery strategies should take into account the balance between the inoperability and economic loss metrics.     

确定任意投入-产出组合规模弹性的DEA模型

本文探讨数据包络分析(DEA)对规模收益的定量分析.过去的研究文献只涉及全输入组合对全输出组合的产出弹性.本文通过建立一般模型来计算任意输入组合对任意输出组合的产出弹性,从而可以确定在产出弹性中占主导地位的最佳投入组合.按照最佳投入组合来扩展规模可避免盲目投资和浪费资源,达到以最小投入获取最大产出的效用.     

所有制分割、行业选择与工资差异

为揭示中国劳动力市场所有制分割引起的工资差异,基于二元选择Logit模型和Mincer方程,构建二元选择Logit-非歧视分解模型,将国有部门与非国有部门之间的工资差异分解为行业间可解释、行业间不可解释、行业内可解释、行业内不可解释1(超额回报)和行业内不可解释2(不足回报)5个部分。以2002年中国家庭收入调查微观数据为研究对象,对在国有部门和非国有部门就业的中国城镇居民行业选择行为、工资决定机制、工资差异构成等进行定量研究。实证结果表明,国有部门与非国有部门劳动力特征显著不同,导致其行业选择行为存在较大差异;国有部门与非国有部门工资决定机制显著不同,导致其工资水平存在较大差距,劳动力特征差异可以解释其中的60.10%,仍有39.90%不可解释部分形成国有部门非正常的工资溢价。     

评价相对效率的投入-产出型DEA

传统DEA只能在固定投入或产出的条件下,从产出或投入角度测算决策单元相对效率,因而不能综合地反映决策单元的投入产出效果.基于双目标规划,本文将提出从投入及产出角度评价决策单元相对效率的投入-产出型DEA,并研究其相对有效性.最后以沪市16家高科技上市公司为应用实例,研究其相对经营效率.     

A Risk‐Based Approach for Identifying Key Economic and Infrastructure Systems

This article introduces approaches for identifying key interdependent infrastructure sectors based on the inventory dynamic inoperability input‐output model, which integrates an inventory model and a risk‐based interdependency model. An identification of such key sectors narrows a policymaker's focus on sectors providing most impact and receiving most impact from inventory‐caused delays in inoperability resulting from disruptive events. A case study illustrates the practical insights of the key sector approaches derived from a value of workforce‐centered production inoperability from Bureau of Economic Analysis data.     

Multiobjective Prioritization Methodology and Decision Support System for Evaluating Inventory Enhancement Strategies for Disrupted Interdependent Sectors

Disruptions in the production of commodities and services resulting from disasters influence the vital functions of infrastructure and economic sectors within a region. The interdependencies inherent among these sectors trigger the faster propagation of disaster consequences that are often associated with a wider range of inoperability and amplified losses. This article evaluates the impact of inventory‐enhanced policies for disrupted interdependent sectors to improve the disaster preparedness capability of dynamic inoperability input‐output models (DIIM). In this article, we develop the dynamic cross‐prioritization plot (DCPP)—a prioritization methodology capable of identifying and dynamically updating the critical sectors based on preference assignments to different objectives. The DCPP integrates the risk assessment metrics (e.g., economic loss and inoperability), which are independently analyzed in the DIIM. We develop a computer‐based DCPP tool to determine the priority for inventory enhancement with user preference and resource availability as new dimensions. A baseline inventory case for the state of Virginia revealed a high concentration of (i) manufacturing sectors under the inoperability objective and (ii) service sectors under the economic loss objective. Simulation of enhanced inventory policies for selected critical manufacturing sectors has reduced the recovery period by approximately four days and the expected total economic loss by $33 million. Although the article focuses on enhancing inventory levels in manufacturing sectors, complementary analysis is recommended to manage the resilience of the service sectors. The flexibility of the proposed DCPP as a decision support tool can also be extended to accommodate analysis in other regions and disaster scenarios.