Modeling asymmetric price transmission in the European food market

In this study, we employ a multivariate panel error correction model (PVECM) to investigate asymmetric price transmission among the farm, processor, and retail segments of the European food supply chain for the 2005–2016 period. The results indicate that, in both the long- and short-run, retail prices respond more strongly to processor price increases than decreases and the same occurs for processor prices due to farm price changes. Thus, the findings demonstrate the presence of positive asymmetric price transmission in the European food supply chain. Finally, the results of the present study indicate that the food price pass-through varies greatly across product category and across countries, and that the pass-through to producer prices is greater than that to consumer prices.     

A new multiscale decomposition ensemble approach for forecasting exchange rates

Due to the high complexity and strong nonlinearity nature of foreign exchange rates, how to forecast foreign exchange rate accurately is regarded as a challenging research topic. Therefore, developing highly accurate forecasting method is of great significance to investors and policy makers. A new multiscale decomposition ensemble approach to forecast foreign exchange rates is proposed in this paper. In the approach, the variational mode decomposition (VMD) method is utilized to divide foreign exchange rates into a finite number of subcomponents; the support vector neural network (SVNN) technique is used to model and forecast each subcomponent respectively; another SVNN technique is utilized to integrate the forecasting results of each subcomponent to generate the final forecast results. To verify the superiority of the proposed approach, four major exchange rates were chosen for model comparison and evaluation. The experimental results indicate that our proposed VMD-SVNN-SVNN multiscale decomposition ensemble approach outperforms some other benchmarks in terms of forecasting accuracy and statistical tests. This demonstrates that our proposed VMD-SVNN-SVNN multiscale decomposition ensemble approach is promising for forecasting foreign exchange rates.     

Unconventional monetary policies and the corporate bond market

The paper uses a reduced-form vector autoregressive framework to study the effects of quantitative easing and operation “twist”, as well as a conventional monetary expansion, on corporate bond yields and spreads. We construct rating- and maturity-based weekly bond portfolios using TRACE and simulate monetary policies as shocks to the Treasury yield curve. We find that none of the policies can persistently lower corporate spreads, and that operation twist is the only policy capable of lowering corporate yields. This latter finding can be accounted for by the operation twist’s ability to keep the monetary base constant and, therefore, to flatten the riskless yield curve without generating inflationary expectations.     

Measuring Production and Irrigation Efficiencies of Rice Farms: Evidence from the Punjab Province,Pakistan

We employ a non‐parametric approach, data envelopment analysis, to estimate the technical and irrigation efficiency of rice farms in the Punjab Province of Pakistan. We use a cross‐sectional dataset of 80 rice growers, including 45 tube‐well owners and 35 water buyers. Mean technical efficiency scores show that tube‐well owners and water buyers are operating at fairly high efficiency levels, indicating that access to technology is not a major constraint. However, irrigation inefficiency is pronounced, with water buyers being more inefficient than tube‐well owners. A bootstrap truncated regression is used to investigate the determinants of technical and irrigation efficiency. We suggest that groundwater management policies should be designed to address efficiency enhancing factors such as knowledge of crop water consumption requirement, better credit opportunities, outreach extension services and training programs.     

外部经济冲击对我国进出口贸易的影响——基于新兴市场经济体的研究

本文从贸易和金融渠道对我国受到其他新兴经济体的外部冲击的可能性进行了评估,并借助GVAR(Global Vector Auto-Regressive)模型方法,考虑了世界各国的交互影响来分析新兴市场国家的宏观经济波动对中国进出口产生的影响。研究发现,区域内的新兴经济市场对我国影响更为显著,韩国、印度、中国香港发生宏观经济波动时对我国进出口贸易可能造成较大的影响。基本上,中国对外贸易对韩国遭受冲击后的反应快且大,但受影响时间较短,人民币汇率波动在应对外部冲击时发挥了一定作用。中国和印度贸易合作关系大于竞争关系。     

无拍频控制技术在新一代CRH380CL型高速动车组上的应用

高速动车组技术的迅猛发展对牵引变流器的性能提出了更高的要求。在动车组传动系统中,单相脉冲整流器工作时,会在中间直流环节产生2倍于电网频率的脉动分量,该脉动分量传递到逆变器输出侧会在电机上产生拍频现象,引起转矩脉动和电机过热。     

基于支持向量机的品牌特色专业评价

简述了江苏省教育厅在本科品牌专业、特色专业验收时的验收标准。利用支持向量机建立了品牌专业、特色专业验收时的验收模型。通过实例,结果表明支持向量机比较精确和有效。     

基于矢量控制的抽油机电力拖动系统仿真研究

游梁式抽油机是我国石油开采中最普遍使用的有杆泵采油地面设备之一,采取相应措施降低其能耗为多年来国内外研究的热点,近年来,矢量控制在变频调速中的应用日趋成熟,本文利用MATLAB软件成功实现了对游梁式抽油机电机拖动系统的仿真分析,对油田上最常见的三相异步电机进行了分析,搭建了矢量控制下的异步电机的数学模型,同时对抽油机的四连杆结构、三相异步电机建模,最后通过采取现场数据验证的方式证明了仿真的正确性,对今后矢量控制应用于抽油机电力拖动系统的节能改造提供了理论支持。     

一种基于支持向量机的带钢表面缺陷识别方法

鉴于支持向量机（SVM）在小样本、高维模式分类中具有的优良分类性能,可以基于多分类支持向量机来检测带铜表面的缺陷。本文构造了一类有向无环图支持向量机（DAGSVM）,利用交叉验证进行了参数和模型的选取,对冷轧带钢中几种现场易出现的缺陷进行分类,并与BP神经网络进行比较分析。实验结果表明,这类基于SVM的算法识别效率较高,较好地解决了小样本学习问题,避免了BP神经网络出现的过学习、收敛速度慢、泛化能力弱等缺点,可有效地应用于带铜表面缺陷检测。     

农村金融发展对农村经济和农民收入的影响研究——基于VEC模型的实证分析

本文基于2001—2009年的季度数据,通过构建一个向量误差修正模型,实证分析了中国农村金融发展对农村经济增长以及农民收入增加的影响。结论表明,中国农村金融发展对农民收入增加产生了显著的影响,同时中国农村金融发展、农村经济增长以及农民收入增加之间存在长期的均衡关系。