基于Granger因果图方法的物价水平国际间传递分析

目前,对Granger因果关系的研究大多数采用两变量Granger因果检验法,由于忽视其它重要变量的影响,常会导致虚假因果关系的出现。鉴此,采用Granger因果图模型方法分析中国及其主要贸易伙伴国(地区)间的物价传递,研究结果表明:美国在物价传递中发挥着主导作用,物价国际间传递存在一定的区域效应;除和中国香港地区存在即期因果关系外,中国对主要贸易伙伴国(地区)的物价水平基本无显著影响,中国既无输出通货膨胀也无输出通货紧缩。同时,样本期内中国物价水平呈现明显的外部"输入性"特征。因此,中国政府应采取措施应对国际的物价冲击,同时防范物价输入性引发的风险,以实现中国物价的稳定。     

Testing the Granger Noncausality Hypothesis in Stationary Nonlinear Models of Unknown Functional Form

In this article, we propose a general method for testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. These tests are based on a Taylor expansion of the nonlinear model around a given point in the sample space. We study the performance of our tests by a Monte Carlo experiment and compare these to the most widely used linear test. Our tests appear to be well-sized and have reasonably good power properties.     

外国直接投资对于福建经济增长的影响分析

外国直接投资在福建经济增长过程中起到了非常重要的作用。文章运用因果检验和时间序列的单整、协整检验分析了外国直接投资和福建经济增长两者之间的关系,得出了外国直接投资和福建经济增长之间存在着长期稳定的互动关系的结论。     

中国产业结构变动与就业水平的实证研究

文章运用时间序列和计量模型研究了中国产业结构与就业水平之间的发展关系.首先运用格兰杰因果检验分析了第一、二、三次产业的产值与其就业之间的因果影响关系,继而从产值与就业两个角度定量分析了第一、二、三次产业各自对总就业水平的贡献,得出结论:第一产业和第三产业是劳动力就业的决定因素,而第二产业不是就业的决定因素;从产值角度来看,第三产业对劳动力就业的贡献最大,从就业角度来看,第一产业的就业对总体就业水平的贡献最高,其次是第三产业,而第二产业的就业对总体就业水平的贡献最小.最后根据研究结论提出相应的建议措施.     

能源与经济因果关系检验:回顾与展望

针对国内外能源与经济因果关系众说纷纭的现状,在总结Granger因果关系检验方法发展脉络的基础上,归纳检验变量之间因果关系的统计方法及其在国内外能源消费与经济发展关系实证检验的结果,做出四个代际划分,并按照检验因果关系四个代际的区分与相应的优劣,给出适用于时间序列和面板数据统计因果关系检验的一般步骤。同时指出面板数据、非线性因果关系检验方法将成为研究的发展方向。     

广东对外贸易与经济增长关系的协整分析

利用多种计量分析工具,从总量和增长效应的角度研究了广东进出口与GDP增长间的关系。研究发现:从长期来说,进口、出口与GDP存在唯一稳定关系,出口较进口对经济增长有更大的促进作用;从短期来说,进口增长、出口增长都是GDP增长的Granger原因,出口增长同时也是进口增长的Granger原因,进口增长、出口增长都带动了经济增长,而且进口增长比出口增长与经济增长有更稳定、更紧密的联系     

Separating trend and cyclical dynamics in state space models with exogenous inputs

In the present study we compare three state rotation methods in modelling the impact of the US economy on the Finnish economy, i.e. Schur decomposition, eigenvalue analysis and singular value decomposition. Singular value decomposition is seen to provide a robust approximation of the state rotation in most cases studied, irrespective of whether the characteristic roots of the state transition matrix are complex. Thus, singular value decomposition seems to be a viable computational device not only in estimating the system matrices of the state space model, but also in state rotation, as compared to the more involved techniques based on eigenvalue analysis or Schur decomposition.     

Modelling method effects as individual causal effects

Summary.  Method effects often occur when different methods are used for measuring the same construct. We present a new approach for modelling this kind of phenomenon, consisting of a definition of method effects and a first model, the method effect model , that can be used for data analysis. This model may be applied to multitrait–multimethod data or to longitudinal data where the same construct is measured with at least two methods at all occasions. In this new approach, the definition of the method effects is based on the theory of individual causal effects by Neyman and Rubin. Method effects are accordingly conceptualized as the individual effects of applying measurement method j instead of k . They are modelled as latent difference scores in structural equation models. A reference method needs to be chosen against which all other methods are compared. The model fit is invariant to the choice of the reference method. The model allows the estimation of the average of the individual method effects, their variance, their correlation with the traits (and other latent variables) and the correlation of different method effects among each other. Furthermore, since the definition of the method effects is in line with the theory of causality, the method effects may (under certain conditions) be interpreted as causal effects of the method. The method effect model is compared with traditional multitrait–multimethod models. An example illustrates the application of the model to longitudinal data analysing the effect of negatively (such as 'feel bad') as compared with positively formulated items (such as 'feel good') measuring mood states.     

决定论与机遇论之争：休谟问题的延续（上）——规范数学方法与“具体性的误置”

今天围绕因果关系中决定与非决定的许多争论,都没能突破决定论与机遇论必居其一的简单逻辑.因果律和机遇律都是对自然规律的数学刻划,是规范化的数学工具带来的结果.决定论论题的真正焦点是隐藏在其背后的必然性这一抽象的核心范畴,它引发了因果观中那些最根本的争论.自然具有必然性和完备的秩序信念,是人类对自然进行理性探索的公设,是科学存在的前提,也是因果观念合理性的基础.决定论是逻辑上的必然性在现实世界中的误置,但机遇论则主张把由数学工具而来的统计相关联系,作为否定自然规律背后必然性的理由.这与休谟的自然主义如出一辙.今天的有关决定论与机遇论的争论,其实质仍然是必然性问题.自然规律中必然性如何实现?这是休谟问题的延续.