Dynamic Model Averaging and CPI Inflation Forecasts: A Comparison between the Euro Area and the United States

The paper forecasts consumer price inflation in the euro area (EA) and in the USA between 1980:Q1 and 2012:Q4 based on a large set of predictors, with dynamic model averaging (DMA) and dynamic model selection (DMS). DMA/DMS allows not solely for coefficients to change over time, but also for changes in the entire forecasting model over time. DMA/DMS provides on average the best inflation forecasts with regard to alternative approaches (such as the random walk). DMS outperforms DMA. These results are robust for different sample periods and for various forecast horizons. The paper highlights common features between the USA and the EA. First, two groups of predictors forecast inflation: temporary fundamentals that have a frequent impact on inflation but only for short time periods; and persistent fundamentals whose switches are less frequent over time. Second, the importance of some variables (particularly international food commodity prices, house prices and oil prices) as predictors for consumer price index inflation increases when such variables experience large shocks. The paper also shows that significant differences prevail in the forecasting models between the USA and the EA. Such differences can be explained by the structure of these respective economies. Copyright © 2015 John Wiley & Sons, Ltd.     

供应链网络风险扩散动力学模型及其应用

在考察分析供应链网络结构域组分特征的基础上,建立了供应链网络风险扩散动力学模型,给出其定态解.该模型由一组方程构成,设置了风险产生项与风险湮没项,合理考虑了风险在供应链网络主体间的传导概率,并设置了主体感染风险阈值.该模型能够反映供应链网络中风险扩散机理,也可以揭示供应链网络结构演进下的风险扩散特征变化.将模型运用到实际的农产品供应链网络中,获得了当前农产品供应链网络及其演进结构下的风险扩散特性.     

基于聚类动态面板引力模型的国际贸易网络研究

本文提出一种针对网络型数据的聚类动态面板引力模型,用于国际贸易流量网络的研究.该模型假设各贸易国分属于不同的潜在类别,各国间贸易流量对应的模型系数由出口国和进口国所属的类别决定.提出使用马尔可夫链蒙特卡罗方法对模型参数以及各贸易国所属的潜在类别进行贝叶斯估计.对2001-2015年60个国家间的贸易流量数据进行了实证分析.结果表明,所提出的模型能够对贸易国进行聚类,有效地提高贸易流量预测的精度.所提出的聚类动态面板引力模型可以被广泛的应用于其他动态网络型数据的研究.     

麻黄细辛附子汤6种活性成分提取动态变化研究

研究麻黄细辛附子汤中盐酸麻黄碱、盐酸伪麻黄碱、细辛脂素、苯甲酰新乌头原碱、苯甲酰乌头原碱、苯甲酰次乌头原碱在提取过程中的含量动态变化。采用HPLC，测定水提取过程中不同时间提取液中6种活性成分的含量。结果表明，6种活性成分溶出量均在前90 min呈上升趋势，且组分稳定存在。90 min后，溶出量增长趋势变缓并有不同程度的消减，存在状态不稳定。研究认为麻黄细辛附子汤的提取工艺为水煎提取90 min，既可保证6种活性成分的稳定存在，又使其溶出量达峰值。     

对称非经典阻尼系统动力响应精确解算法比较

分别采用频响函数法和复频率响应法对同一个数值算例进行了稳态响应、使用条件和范围以及误差来源分析,阐述了两种算法在工程执行过程中的特点及效率。     

基于动态优化双钻头打孔机生产效能的研究

首先,对孔型加工及走刀方式进行分析,为提高打孔机效能,采用两钻头同时作业的方式。然后,根据相关的数据,应用动态优化的相关理论建立数学模型,并运用遗传算法进行求解,从而确立了双钻头作业时的最优作业线路、最佳行进时间和作业成本,并用MATLAB编写程序画出了相应图形,更加形象地显现出了各个路段的最优作业方案。     

河南省新型农村社区建设的动力机制研究

为缓解城乡发展差距,推进农村的发展,中央先后提出"推进社会主义新农村建设"和"积极推进农村社区建设",通过完善农村的政治、经济、文化、社会保障等方面,达到城乡发展一体化。河南省作为农业大省,农村的发展显得尤为重要,但在农村发展过程中依然存在动力不足的问题,在中原经济区建设的背景下探讨河南省农村发展的动力问题则显得更有意义。     

Identifying US business cycle regimes using dynamic factors and neural network models

We use dynamic factors and neural network models to identify current and past states (instead of future) of the US business cycle. In the first step, we reduce noise in data by using a moving average filter. Dynamic factors are then extracted from a large-scale data set consisted of more than 100 variables. In the last step, these dynamic factors are fed into the neural network model for predicting business cycle regimes. We show that our proposed method follows US business cycle regimes quite accurately in-sample and out-of-sample without taking account of the historical data availability. Our results also indicate that noise reduction is an important step for business cycle prediction. Furthermore, using pseudo real time and vintage data, we show that our neural network model identifies turning points quite accurately and very quickly in real time.     

非自治随机Kuramoto-Sivashinsky方程的Wong-Zakai逼近

在Wong-Zakai逼近下证明了非自治Kuramoto-Sivashinsky方程吸引子的存在性.     

中国与“一带一路”沿线部分国家的经济关系动态分析

GTAP(Global Trade Analysis Project)模型综合考虑了资本总量、资本流动、人口因素、国民生产总值等多项指标,可以用于各相关国的经济发展和经济合作互动关系分析.选用GTAP模型,分析了中国与一带一路沿线部分国家的经济互动关系.在西亚地区选择了沙特阿拉伯、以色列、伊朗、阿曼、阿联酋、科威特、伊拉克共7国,分别在降低关税20%和降低关税50%两种假设条件下展开实证分析.实证结果显示:在关税分别降低20%和50%两种假设条件下,中国和西亚诸国的GDP都有一定程度增加,各国之间进出口规模都有一定程度的扩大,这表明"一带一路"倡议对于沿线各国的经济发展和合作互动具有明显的促进作用.