Chance Constrained Programming Formulations for Stochastic Characterizations of Efficiency and Dominance in DEA

Pareto-Koopmans efficiency in Data Envelopment Analysis (DEA) is extended to stochastic inputs and outputs via probabilistic input-output vector comparisons in a given empirical production (possibility) set. In contrast to other approaches which have used Chance Constrained Programming formulations in DEA, the emphasis here is on joint chance constraints. An assumption of arbitrary but known probability distributions leads to the P-Model of chance constrained programming. A necessary condition for a DMU to be stochastically efficient and a sufficient condition for a DMU to be non-stochastically efficient are provided. Deterministic equivalents using the zero order decision rules of chance constrained programming and multivariate normal distributions take the form of an extended version of the additive model of DEA. Contacts are also maintained with all of the other presently available deterministic DEA models in the form of easily identified extensions which can be used to formalize the treatment of efficiency when stochastic elements are present.     

Asymptotic confidence bands for the estimated autocovariance and autocorrelation functions of vector autoregressive models

This paper provides closed-form formulae for computing the asymptotic covariance matrices of the estimated autocovariance and autocorrelation functions of stable VAR models by means of the delta method. These covariance matrices can be used to construct asymptotic confidence bands for the estimated autocovariance and autocorrelation functions to assess the underlying estimation uncertainty. The usefulness of the formulae for empirical work is illustrated by an application to inflation and output gap data for the U.S. economy indicating the existence of a significant short-run Phillips-curve tradeoff.First version received: November 2002/Final version received: September 2003     

总量均衡区间与宏观调控应确立的若干新原则

现代市场经济条件下,供给方调整其生产规模所需的成本可称为调节成本。由于存在调节成本,传统分析中的“总量均衡中心点”两侧便分别存在着“低位临界点”与“高位临界点”,这两点界定了一个特殊的“总量均衡区间”。“总量均衡区间”的出现对宏观调控将产生诸多重要影响,使之面临一系列新问题、新挑战。为有效应对这种新情况,在宏观调控实践中有必要相应地确立“近似均衡原则”、“适度超前原则”、“临界点原则”、“供给方原则”。     

“机械制图用计算机信息交换制图规则”中的若干问题探讨

分析讨论了ＧＢ／Ｔ１４６６５－９３《机械制图用计算机信息交换、制图规则》中存在的问题与错误,并提出了相应的修正建议。     

Impact of Divergent Consumer Confidence on Option Prices

This paper investigates the impact of divergent consumer confidence on option prices. To model this, we assume that consumers disagree on the expected growth rate of aggregate consumption. With other conditions unchanged in the discrete-time Black–Scholes option-pricing model, we show that the representative consumer will have declining relative risk aversion instead of the assumed constant relative risk aversion. In this case all options will be underpriced by the Black–Scholes model under the assumption of bivariate lognormality. This revised version was published online in June 2006 with corrections to the Cover Date.     

Inference with Dependent Data in Accounting and Finance Applications

We review developments in conducting inference for model parameters in the presence of intertemporal and cross‐sectional dependence with an emphasis on panel data applications. We review the use of heteroskedasticity and autocorrelation consistent (HAC) standard error estimators, which include the standard clustered and multiway clustered estimators, and discuss alternative sample‐splitting inference procedures, such as the Fama–Macbeth procedure, within this context. We outline pros and cons of the different procedures. We then illustrate the properties of the discussed procedures within a simulation experiment designed to mimic the type of firm‐level panel data that might be encountered in accounting and finance applications. Our conclusion, based on theoretical properties and simulation performance, is that sample‐splitting procedures with suitably chosen splits are the most likely to deliver robust inferential statements with approximately correct coverage properties in the types of large, heterogeneous panels many researchers are likely to face.     

Forecasting U.S. money growth using economic uncertainty measures and regularisation techniques

This paper examines the out-of-sample forecasting properties of six different economic uncertainty variables for the growth of the real M2 and real M4 Divisia money series for the U.S. using monthly data. The core contention is that information on economic uncertainty improves the forecasting accuracy. We estimate vector autoregressive models using the iterated rolling-window forecasting scheme, in combination with modern regularisation techniques from the field of machine learning. Applying the Hansen-Lunde-Nason model confidence set approach under two different loss functions reveals strong evidence that uncertainty variables that are related to financial markets, the state of the macroeconomy or economic policy provide additional informational content when forecasting monetary dynamics. The use of regularisation techniques improves the forecast accuracy substantially.     

基于失效风险的建筑物预防维修成本模型优化

建筑物预防性维修成本的最优控制问题,是企业现代化经营管理的一个重要组成部分,直接影响到企业的经济效益。针对承受重复荷载作用的建筑构件,失效概率随服役时间增加而增大的实际情况,提出了失效风险的概念。采用役龄回退因子描述了维修后失效概率降低的程度,在此基础上推算出满足可靠度约束条件,适用于特定时间段非等间隔检测期序列,计算出单位维修周期内的检测次数。通过对维修成本函数的分析,建立了基于等失效风险状态的维修成本优化模型。为房屋物业管理部门进行建筑物的维修和更换决策提供参考依据。     

日本公共养老金制度的信任危机

随着老龄化和少子化问题的逐渐显露,日本的公共养老金制度已经暴露出了十分严重的问题,日本国民的不信任情绪逐渐滋生。公共养老金问题不仅是一个社会保障的相关问题,也直接影响到日本各届首相的前后更替和日本政局的稳定。进行日本公共养老金制度改革已经迫在眉睫。本文从日本公共养老金制度的财政危机和信任危机两个角度进行公共危机分析,进一步提出对现收现付制的养老金体系的看法。     

“中国道路”的接续探索与时代价值

“中国道路”的发展“奇迹”引起了国内外专家学者热议,有赞誉,有指责;有肯定,也有否定,呈现出多种思考与议论。针对这些热议,需要坚持“历史与逻辑”相统一的辩证唯物主义立场来认识“中国道路”演化的系统性和必然性,进而领会“中国道路”的时代价值。“中国道路”创新和丰富了世界现代化发展模式。将“中国道路”的“历史起点和逻辑起点”放在宏观时空环境中来观察分析,以期深刻揭示选择走“中国道路”的必然性;同时秉持历史唯物主义基本立场和观点,坚决批判历史虚无主义,树立“道路自信”。