国际油价波动对国内消费物价水平传导非对称研究

中国原油定价机制逐步市场化,国内与国际油价的关联性大大提高。以研究国际油价波动对中国消费物价水平的传导为研究目的,以2007年1月-2015年12月为样本区间,从国际油价对CPI的传导机理入手,依据传导性质划分为直接传导和间接传导两条传导路径,并以此作为研究框架。以协整和非对称误差修正模型（APT-ECM）为主要研究方法,结合Wald检验和脉冲响应函数分析方法,深入剖析实际传导过程及其特征。实证结果表明,国际油价对国内消费物价水平的传导包括垂直传导和空间传导。受多种因素影响,实际传导效应在油价波动方向、波动幅度和传导速率方面表现出不同程度的非对称性特征。     

基于人工神经网络的在线设备状态监测系统的研究(英文)

研究了基于人工神经网络在线设备状态监测系统,简要介绍了人工神经网络的基础理论,描述了基于人工神经网络在线设备状态监测系的结构和工作过程,给出该系统对卷烟机MK9-5的状态监测和故障诊断的结果。实验结果表明,将多层前馈人工种经网络用于设备在线状态监测具有较好的效果,并可对设备故障进行可靠诊断。     

Identification of Standard Auction Models

This paper presents new identification results for models of first–price, second–price, ascending (English), and descending (Dutch) auctions. We consider a general specification of the latent demand and information structure, nesting both private values and common values models, and allowing correlated types as well as ex ante asymmetry. We address identification of a series of nested models and derive testable restrictions enabling discrimination between models on the basis of observed data. The simplest model—symmetric independent private values—is nonparametrically identified even if only the transaction price from each auction is observed. For richer models, identification and testable restrictions may be obtained when additional information of one or more of the following types is available: (i) the identity of the winning bidder or other bidders; (ii) one or more bids in addition to the transaction price; (iii) exogenous variation in the number of bidders; (iv) bidder–specific covariates. While many private values (PV) models are nonparametrically identified and testable with commonly available data, identification of common values (CV) models requires stringent assumptions. Nonetheless, the PV model can be tested against the CV alternative, even when neither model is identified.     

Designing optimal food safety monitoring schemes using Bayesian network and integer programming: The case of monitoring dioxins and DL-PCBs

Efficient food safety monitoring should achieve optimal resource allocation. In this article, a methodology is presented to optimize the use of resources for food safety monitoring aimed at identifying noncompliant samples and estimating background level of hazards in food products. A Bayesian network (BN) model and an optimization model were combined in a single framework. The framework was applied to monitoring dioxins and dioxin-like polychlorinated biphenyls (DL-PCBs) in primary animal-derived food products in the Netherlands. The BN model was built using a national dataset with monitoring results of dioxins and DL-PCBs in animal-derived food products over a 10-year period (2008–2017). These data were used to estimate the probability of detecting suspect samples with dioxins and DL-PCBs levels above preset thresholds, given certain sample conditions. The results of the BN model were then inserted into the optimization model to compute an optimal monitoring scheme. Model estimates showed that the probability of dioxins and DL-PCBs exceeding threshold limits was higher in laying hen eggs and sheep meat than in other animal-derived food (except deer meat). Compared with the monitoring scheme used in the Netherlands in 2018, the optimal monitoring scheme would save around 10,000 EUR per year. This could be obtained by reallocating monitoring resources from products with lower probability of dioxin and DL-PCBs exceeding threshold limits (e.g., pig meat) to products with higher probability (e.g., bovine animal meat), and by shifting sample collection from the last quarter of the year toward the first three quarters of the year.     

Optimal Contracts when Enforcement is a Decision Variable

This paper analyzes choice‐theoretic costly enforcement in an intertemporal contracting model with a differentially informed investor and entrepreneur. An intertemporal contract is modeled as a mechanism in which there is limited commitment to payment and enforcement decisions. The goal of the analysis is to characterize the effect of choice‐theoretic costly enforcement on the structure of optimal contracts. The paper shows that simple debt is the optimal contract when commitment is limited and costly enforcement is a decision variable (Theorem 1). In contrast, stochastic contracts are optimal when agents can commit to the ex‐ante optimal decisions (Theorem 2). The paper also shows that the costly state verification model can be viewed as a reduced form of an enforcement model in which agents choose payments and strategies as part of a perfect Bayesian Nash equilibrium.     

On the probability distribution of economic growth

Three important and significantly heteroscedastic gross domestic product series are studied. Omnipresent heteroscedasticity is removed and the distributions of the series are then compared to normal, normal mixture and normal–asymmetric Laplace (NAL) distributions. NAL represents a skewed and leptokurtic distribution, which is in line with the Aghion and Howitt [1 Aghion, P. and Howitt, P. 1992. A model of growth through creative destruction. Econometrica, 60: 323–351. [Crossref], [Web of Science ®] [Google Scholar]] model for economic growth, based on Schumpeter's idea of creative destruction. Statistical properties of the NAL distributions are provided and it is shown that NAL fits the data better than the alternatives.     

Empirical nonparametric control charts for high-quality processes

For attribute data with (very) small failure rates often control charts are used which decide whether to stop or to continue each time r failures have occurred, for some r?1. Because of the small probabilities involved, such charts are very sensitive to estimation effects. This is true in particular if the underlying failure rate varies and hence the distributions involved are not geometric. Such a situation calls for a nonparametric approach, but this may require far more Phase I observations than are typically available in practice. In the present paper it is shown how this obstacle can be effectively overcome by looking not at the sum but rather at the maximum of each group of size r.     

Constants and variables: Pareto's asymmetric distribution curve

The article sets out the classic Paretian theory of income distribution. As it does so, it seeks to highlight the constant elements in the human faculties represented, at aggregate level, by the invariability and persistence of the asymmetric income curve, and the variable elements connected with the same curve and manifest in upward and downward mobility – what Pareto calls ‘circulation’. The two theorems arising from Pareto's discovery constitute a specific theory of development which has been confirmed from two points of view: in the positive sense of development when – as in the West – the second theorem has been applied (also independently of Pareto) with the connected theory of the entrepreneur and innovation in democratic regimes; but also in the negative sense of underdevelopment, with the destruction of wealth and the consequent general impoverishment, when expropriation policies have been implemented in despotic regimes, or excessive taxation in others.     

基于ARCH-Expectile方法的VaR和ES尾部风险测量

甄别和确定风险因素的贡献是资产或资产组合风险管理的重要研究内容。近十年,下端风险越来越受到关注,在险价值（Value at Risk,VaR）和预期不足（Expected Shortfall,ES）是资产组合风险管理中两个常用的风险度量工具。Kuan等^[1]在一类条件自回归模型（CARE）下提出了基于expectile的VaR度量-EVaR。本文扩展了Kuan等^[2]的CARE模型到带有异方差的数据,引入ARCH效应提出了一个线性ARCH-Expectile模型,旨在确定资产或资产组合的风险来源以及评估各风险因素的贡献大小,并应用expectile间接评估VaR和ES风险大小。同时给出了参数的两步估计算法,并建立了参数估计的大样本理论。最后,将本文所提出的方法应用于民生银行股票损益的风险分析,从公司基本面、市场流动性和宏观层面三个方面选取影响股票损益的风险因素,分析结果表明,各风险因素随股票极端损失大小的水平不同,其风险因素的来源及其大小和方向也是随之变化的。     

基于活动敏感性的动态缓冲监控方法研究

缓冲监控问题对于企业成功应用关键性项目管理,提高项目进度管理绩效和确保项目按时完工,都至关重要。本文针对现有缓冲监控方法在项目进度监控中所存在的忽视内部情况的问题,引入项目进度风险分析方法中的活动敏感性信息。研究了动态环境下活动敏感性指标的计算和监控阀值的设定,在缓冲的黄区监控中集成了考虑活动敏感信息的动态监控过程。在综合考虑缓冲指标和活动关联度指标的监控指标体系,综合设置各指标的监控阀值的基础上,提出了基于活动敏感性信息的关键链动态缓冲监控方法。最后通过一个算例将所提方法与现有方法进行比较,实验结果表明,合理设置活动关联度的监控阀值后,所提方法在总赶工时间、总赶工活动数、超计划完工次数以及监控负荷这四个绩效方面的结果更优。