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.     

DEMAND,CUSTOMER BASE‐LINE AND DEMAND RESPONSE IN THE ELECTRICITY MARKET: A SURVEY

The increasing use of demand‐side management, as a tool to reliably meet electricity demands at peak time, has stimulated interest among researchers, consumers and producer organiza‐tions, managers, regulators and policymakers. This research reviews the growing literature on models which are used to study demand, customer base‐line (CBL) and demand response in the electricity market. After characterizing the general demand models, the CBL, based on which the demand response models are studied, is reviewed. Given the experience gained from the review and existing conditions, the study combines an appropriate model for each case for a possible application to the electricity market; moreover, it discusses the implications of the results. In the literature, these aspects are studied independently. The main contribution of this survey is attributed to the treatment of the three issues as sequentially interdependent. The review is expected to enhance the understanding of the demand, CBL and demand response in the electricity market and their relationships. The objective is conducted through a combination of demand and supply side managements in order to reduce demand through different demand response programs during peak times. This enables electricity suppliers to save costly electricity generation and at the same time reduce energy vulnerability.     

基于组合评价法的混流生产系统运行绩效评价

在目前集装箱制造行业转型升级的背景下，以某集装箱制造公司的特箱生产系统为例，构建混流生产系统运行绩效的评价指标体系，运用组合评价法对运行绩效进行评价。借鉴平衡计分卡的分析思路，对特箱生产系统的生产管理给出了相关的决策建议。此研究成果对其他制造型混流生产系统具有实际的指导意义。     

研学结合教学理念在微观经济学课程中的应用

为了探索适合高职学生学习特点的教学方法，提高教学质量，本文就研学结合教学理念的内涵、实施路径、特征和目的进行了探索和研究，并在微观经济学课程中进行试验。结果显示教学效果良好，教学质量得到提升，学生的学习兴趣得以提高，主动参与的积极性增加，培养了学生分析问题和解决问题的能力，为专业训练和实践打好基础。论文最后就研学结合教学理念在微观经济学课程实施中存在的问题进行了剖析，并提出了进一步探索和努力地方向。     

我国物流人才培养的关键问题分析及解决途径——建立区域联合培养实践基地的战略思考

产学研相结合的人才培育模式是培养高层次、复合型物流人才，解决我国物流人才缺口的关键。但我国目前的物流人才培养模式以及一对一为主的产学研培养模式仍存在着一定的问题需要解决。文章首先分析了我国目前物流人才培养过程中的基本问题，进而针对校企合作的产学研模式及其存在的主要问题进行了探讨。在此基础上，提出了解决这些问题的途径——建立区域联合物流人才培养实践基地的战略思考，并分析了该战略在运作模式、服务范围、资源利用、培养方式、协作关系以及功能拓展等方面的独特优势。     

矿泉水瓶再生设计研究

由于500ml左右矿泉水瓶瓶口具有统一的螺纹规格,其次,瓶体的容量也具有接近统一的标准,这就为矿泉水瓶再生设计的开发提供了必要的前提。市场上关于矿泉水瓶的再生设计多利用矿泉水瓶作为盛水的容器,而没有继续探讨其盛放小型垃圾(瓜子壳,纸屑,铅笔屑等)的功能。本文以绿色设计中延长产品生命周期的理念为原则,以联想法、模仿法及组合法等产品设计方法为指导,推出一款全新的使用矿泉水瓶衍生功能的产品,并着重介绍在本设计进行的过程中得出的新的设计方法:系统化条件下的功能衍生法。通过这款设计来说明现有产品衍生出新的功能的可行性,并总结一定的设计经验与设计方法,为以后进行相关设计奠定理论和方法基础。     

High-frequency credit spread information and macroeconomic forecast revision

We examine whether professional forecasters incorporate high-frequency information about credit conditions when revising their economic forecasts. Using a mixed data sampling regression approach, we find that daily credit spreads have significant predictive ability for monthly forecast revisions of output growth, at both the aggregate and individual forecast levels. The relationships are shown to be notably strong during ‘bad’ economic conditions, which suggests that forecasters anticipate more pronounced effects of credit tightening during economic downturns, indicating an amplification effect of financial developments on macroeconomic aggregates. The forecasts do not incorporate all financial information received in equal measures, implying the presence of information rigidities in the incorporation of credit spread information.     

Forecasting and forecast narratives: The Bank of England Inflation Reports

We analyze the narratives that accompany the numerical forecasts in the Bank of England’s Quarterly Inflation Reports, 1997–2018. We focus on whether the narratives contain useful information about the future course of key macro variables over and above the point predictions, in terms of whether the narratives can be used to enhance the accuracy of the numerical forecasts. We also consider whether the narratives are able to predict future changes in the numerical forecasts. We find that a measure of sentiment derived from the narratives can predict the errors in the numerical forecasts of output growth, but not of inflation. We find no evidence that past changes in sentiment predict subsequent changes in the point forecasts of output growth or of inflation, but do find that the adjustments to the numerical output growth forecasts have a systematic element.     

Correction to: Optimal and robust combination of forecasts via constrained optimization and shrinkage

We provide a correction to Proposition 1 in Optimal and robust combination of forecasts via constrained optimization and shrinkage, published in the International Journal of Forecasting 38(1):97-116 (2021). This correction has no impact on any other result (neither theoretical nor empirical) provided in the above paper.