Mixed-frequency approaches to nowcasting GDP: An application to Japan

In this paper, we discuss the approaches to nowcasting Japan’s GDP quarterly growth rates, comparing a variety of mixed frequency approaches including a bridge equation approach, Mixed-Data Sampling (MIDAS) and factor-augmented version of these approaches. In doing so, we examine the usefulness of a novel sparse principal component analysis (SPCA) approach in extracting factors from the dataset. We also discuss the usefulness of forecast combination, considering various ways to combine forecasts from models and surveys. Our findings are summarized as follows. First, some of the mixed frequency models discussed in this paper record out-of-sample performance superior to a naïve constant growth model. Second, albeit small, the SPCA approach of extracting factors improves predictive power compared with traditional principal component approach. Furthermore, we find that there is a gain from combining model forecasts and professional survey forecasts.     

浅析桥梁施工质量控制要点

随着我国城市化进程的快速推进,桥梁的建设步伐正在以前所未有的规模在全国各地展开,但频繁出现的质量与安全事故使桥梁的施工管理问题也越来越成为人们关注的焦点.本文就桥梁施工质量控制要点进行初步探讨.     

谈金安桥水电站左岸护岸边坡开挖的控制爆破

金安桥水电站左岸护岸边坡开挖爆破区环境复杂,紧挨将要拆除的下游围堰,在爆破时不能丝毫破坏其下游围堰。为了确保下游围堰、基坑抽水设备的安全,采用预裂爆破、孔间微差爆破、孔内微差爆破,选用较为合理的爆破参数控制爆破,顺利完成了左岸护岸边坡开挖爆破工作,为下游围堰的如期拆除创造了条件。     

港珠澳大桥建设、运输成本降低与大珠三角产业转移研究——一个新经济地理学分析框架

从古典到新古典区位理论再到"新经济地理理论",运输成本成为产业转移区位选择研究的决定性变量。现代交通运输的发展有效降低了运输成本,运输成本又通过改变产业集聚的向心力和离心力进一步影响产业转移的区位选择。通过构建新经济地理学分析框架,深入分析基于运输成本变量的大珠三角产业转移机理,指出港珠澳大桥必将成为发达地区和国家产业转移的重要通道。     

港珠澳大桥通车后珠海市物流需求预测研究

分析了港珠澳大桥通车后给珠海市物流业带来的影响,选取货运量作为物流需求指标,先用灰色预测和神经网络组合的方法对珠海市2012-2014年的货运量进行了预测,再针对港珠澳大桥通车后给珠海市带来的物流需求的突增,选取珠海GDP指标用弹性系数法对2015-2020年的货运量进行了预测,得出结论:大桥通车后,珠海市货运量较2008年将增长近一倍。     

桥梁伸缩缝处跳车原因和防治措施分析

根据桥梁伸缩缝处跳车的表现形式,文章分析了跳车的原因,并提出了防治桥梁伸缩缝处跳车的基本措施,供大家参考。     

柳州螺丝岭柳江特大桥悬臂施工工艺研究

文章结合柳州螺丝岭柳江特大桥介绍了大跨度预应力刚构－连续梁的悬臂施工工艺，可为其他类似桥梁的施工提供参考。     

Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009

In this work we consider the forecasting of macroeconomic variables during an economic crisis. The focus is on a specific class of models, the so-called single hidden-layer feed-forward autoregressive neural network models. What makes these models interesting in the present context is the fact that they form a class of universal approximators and may be expected to work well during exceptional periods such as major economic crises. Neural network models are often difficult to estimate, and we follow the idea of White (2006) of transforming the specification and nonlinear estimation problem into a linear model selection and estimation problem. To this end, we employ three automatic modelling devices. One of them is White’s QuickNet, but we also consider Autometrics, which is well known to time series econometricians, and the Marginal Bridge Estimator, which is better known to statisticians. The performances of these three model selectors are compared by looking at the accuracy of the forecasts of the estimated neural network models. We apply the neural network model and the three modelling techniques to monthly industrial production and unemployment series from the G7 countries and the four Scandinavian ones, and focus on forecasting during the economic crisis 2007–2009. The forecast accuracy is measured using the root mean square forecast error. Hypothesis testing is also used to compare the performances of the different techniques.     

A Rich Vein for Reality Mining

Arik Hesseldahl In the aftermath of the September 11 attacks, U.S. officials quickly turned their attention to other potential targets, including California's Golden Gate Bridge. What would happen if terrorists took down the bridge between San Francisco and Marin County? How much of the region would be affected and for how long?     

合同环境下优化路桥项目施工总工期之方法探讨

在合同环境下,针对某一路桥工程,在一定资源的约束下,可以通过施工作业方式的选择、施工段的排序、施工段数的合理确定、项目总成本和质量控制及经理人素质的提高等方法来进一步缩短和优化路桥项目施工总工期。