Housing Pricesand General Economic Conditions： An Analysis of Chinese New Dwelling Market

This paper presents an investigation of the interaction between housing prices and general economic conditions in China for the period of 1986-2002, The empirical results indicate that housing prices in China are predictable by market fundamentals, which could explain most of the variations in housing prices. The results of Granger causality tests confirm that unemployment rate, total population, changes in construction costs, changes in the consumer price index (CPI) are all Granger causalities of housing prices, with feedback effects observed to affect the vacancy rate of new dwellings, changes in CPI, and changes in per capita disposable income of urban households, Studies with impulse response functions further illustrate these relationships in terms of the degree of the impact on housing prices from the determinants and the feedbacks, The findings indicate that there is a long-term equilibrium relationship between housing prices and market fundamentals in China and it is the identified fundamentals that drive housing prices up, rather than a bubble,     

Causality and forecasting in incomplete systems

In this paper we examine how causality inference and forecasting within a bivariate VAR, consisting of y(t) and x(t), are affected by the omission of a third variable, w(t), which causes (a) none, (b) one, and (c) both variables in the bivariate system. We also derive conditions under which causality inference and forecasting are invariant to the selection of a bivariate or a trivariate model. The most general condition for the invariance of both causality and forecasting to model selection is shown to require the omitted variable not to cause any of the variables in the bivariate system, although it allows the omitted variable to be caused by the other two. We also show that the conditions for one-way causality inference to be invariant to model selection are not sufficient to ensure that forecasting will also be invariant to the model selected. Finally, we present a numerical illustration of the potential losses, in terms of the variance of the forecast, as a function of the forecast horizon and for alternative parameter values—they can be rather large, as the omission of a variable can make the incomplete model unstable. © 1997 John Wiley & Sons, Ltd.     

外商直接投资对内蒙古经济影响的实证分析

本文运用计量分析的方法对内蒙古1988-2007年间外商直接投资和国内生产总值之间的关系进行研究,通过线性回归模型检验、协整检验和因果关系检验,得出结论：外商直接投资对内蒙古经济的增长具有显著影响、二者呈长期均衡关系并存在因果关系.最后提出了吸引外资的建议.     

多传感器融合的因果映射网故障诊断方法

针对异构、时变、耦合的复杂系统故障诊断问题,提出一种基于多传感器融合的因果映射网故障诊断方法.以时态数据挖掘为手段,实现包含原因层和结果层的快速映射网络.通过因果度定义节点连接强度,通过依赖度和影响度进行故障位置定位和影响预测.应用实例表明方法具有机理简单、算法快捷、结果直观优点.     

上海市房地产业外商直接投资的实证研究——基于外资流量与房地产价格的格兰杰因果检验

近来外商投资对房地产业的影响受到了社会更多的关注,而外商投资的重要形式之一是外商直接投资.运用计量经济学方法探索上海市外商直接投资与房地产价格的相互影响,发现外商直接投资的增长不是房地产价格升高的格兰杰原因,而房地产价格升高是导致外商直接投资增长的格兰杰原因,并在此结论的基础上给出简单的政策性建议.     

中国能源消费与经济增长关系的因果分析

文章从生产函数理论的新视角,利用多变量的协整检验和基于向量误差修正模型(VECM)的因果关系检验,实证分析了中国能源消费与经济增长之间的关系;结果表明,短期内中国能源消费与GDP增长之间不存在因果关系,长期内存在GDP到能源消费的单向因果关系;这一推断有重要的政策涵义,即节能政策在中国是可行的,在长期内不会影响经济的发展。     

Modeling Compositional Time Series with Vector Autoregressive Models

Multivariate time series describing relative contributions to a total (like proportional data) are called compositional time series. They need to be transformed first to the usual Euclidean geometry before a time series model is fitted. It is shown how an appropriate transformation can be chosen, resulting in coordinates with respect to the Aitchison geometry of compositional data. Using vector autoregressive models, the standard approach based on raw data is compared with the compositional approach based on transformed data. The results from the compositional approach are consistent with the relative nature of the observations, while the analysis of the raw data leads to several inconsistencies and artifacts. The compositional approach is extended to the case when also the total of the compositional parts is of interest. Moreover, a concise methodology for an interpretation of the coordinates in the transformed space together with the corresponding statistical inference (like hypotheses testing) is provided. Copyright © 2015 John Wiley & Sons, Ltd.     

面向Agent的时间管理算法研究

随着分布式仿真技术在深度和广度上的发展，如何有效地实现仿真体之间的时间同步成为目前分布式仿真技术中最为引人关注的重点和难点所在。本文运用面向Agent的分析方法研究分布式仿真中的时间管理。在分析了分布式仿真系统中仿真Agent之间关系的基础上，提出一种利用仿真Agent之间的因果关系协调时间推进的仿真时间管理算法。该算法利用各个仿真主体之间的制约关系，进行分组管理，层次化地协调仿真Agent之间时间推进，从而可以较好地提高仿真系统执行效率。     

中国能源消费与经济增长的协整与误差校正模型研究

详细研究中国从1954—2003年间年度GDP和能源总消费以及能源消费各构成部分(包括煤、石油、天然气和水电力等)之间的长期均衡关系。研究结果表明GDP分别与能源总消费、煤炭消费之间存在协整关系，而GDP与石油、天然气和水电之间不存在协整关系，进而分别建立了GDP与能源总消费以及GDP与煤炭消费之间的误差校正模型。     

进出口贸易与中国经济增长关系的统计分析

利用SPSSl9．0软件对中国1990—2011年的进口、出H、净出口额和国内生产总值（GDP）做了一元线性回归,发现国内生产总值与进口、出口额即进出口总额之间的相关性较强;然后用计量经济学的方法,利用eviews6．0软件对GDP与进出口总额两时间序列做单位根检验、协整检验、Granger因果检验及脉冲函数分析、方差分解分析,得到结论：进出口总额是GDP的Granger原因,而GDP不是进出口贸易的Granger原因;接着又利用SPSSl9．0统计软件作图功能对我国2011及2010年的对外商品分类金额做了简单箱图和堆栈面积图,比较直观的分析了我国当前的产业结构．最后对发展我国进出口贸易和经济发展提出建议．