Partial unit root and surplus-lag Granger causality testing: A Monte Carlo simulation study

Previous literature has shown that the addition of an untested surplus-lag Granger causality test can provide highly robust to stationary, non stationary, long memory, and structural break processes in the forcing variables. This study extends this approach to the partial unit root framework by simulation. Results show good size and power. Therefore, the surplus-lag approach is also robust to partial unit root processes.     

Estimating school effectiveness with student growth percentile and gain score models

Measuring school effectiveness using student test scores is controversial and some methods used for this can be inaccurate in some situations. The validity of two statistical models – the Student Growth Percentile (SGP) model and a multilevel gain score model – are evaluated. The SGP model conditions on previous test scores thereby unblocking a backdoor path between true school/teacher effectiveness and student test scores. When the product of the coefficients that make up this unblocked backdoor path is positive, the SGP estimates can be inaccurate. The accuracy of the multilevel gain score model was not associated with the product of this backdoor path. The gain score model appears promising in these situations where the SGP and other covariate adjusted models perform poorly.     

The Effects of Detrending in Granger Causality Tests

Nonstationary time series are frequently detrended in empirical investigations by regressing the series on time or a function of time. The effects of the detrending on the tests for causal relationships in the sense of Granger are investigated using quarterly U.S. data. The causal relationships between nominal or real GNP and M1, inferred from the Granger–Sims tests, are shown to depend very much on, among other factors, whether or not series are detrended. Detrending tends to remove or weaken causal relationships, and conversely, failure to detrend tends to introduce or enhance causal relationships. The study suggests that we need a more robust test or a better definition of causality.     

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.     

FDI 对安徽省装备制造业发展的影响分析

外商直接投资（FDI）在拓宽国内资金需求渠道的同时,具有较强的技术溢出效应,迎合了装备制造业资本和技术密集的双重特征。当前,安徽省装备制造业处在资本密集型占主导的发展阶段,对 FDI的偏好性较强。研究表明,安徽省装备制造业与FDI间具有较强的相关性,FDI能够有效促进安徽省装备制造业发展,但安徽省装备制造业对FDI的吸引力较弱,且各具体行业对 FDI依赖程度存在较大差异。据此提出相应的建议,一方面,安徽省应注重装备制造业转型升级,提升行业整体竞争力;另一方面,要优化投资环境,增强安徽省装备制造业对FDI的引致能力。     

A股上市公司变相财务操纵对行业估值的影响

关于上市公司利润操控的相关研究主要是将净利润作为一个事关操控的敏感指标,但在监管与被监管双方努力的博弈下,其可被操纵的潜力已被充分挖掘。从实证角度关注上市公司财务操纵的其他可操作途径,其中就包括一些看似合理的变相财务操纵手段。按照2001年中国证监会公布的《上市公司行业分类指引》,把我国上市企业分为13个行业,对不同行业内企业2003—2013年部分主观可操控的财务指标与其所在行业的平均市盈率进行格兰杰因果检验和回归分析,结果表明,一些行业内企业的部分财务指标与其所在行业的平均市盈率存在领先与滞后关系,并且影响作用显著。     

过错在因果关系判断中的影响

过错与因果关系共同作为侵权行为的构成要件,并非彼此间毫无联系,过错对于因果关系的判断有重要影响,侵权人、受害人、第三人的过错均影响到因果关系判断,但过错并非在因果关系判断中独立发挥作用,过错须和原因力结合在一起确定侵权责任范围,这样才能更接近公平.     

中国农村金融发展与经济增长（1978～2001）实证分析

基于VAR模型,利用Granger因果检验法,对中国农村1978～2001年间金融发展与经济增长的关系作出实证研究。发现中国农村正规金融的发展对农村经济增长并没有起到"供给主导"作用,而是处于一个严重滞后的"需求遵从"地位。实证研究表明,农村正规金融相对于农村经济增长是缺乏效率的,而农村非正规金融值得关注。     

金融资本结构中证券比重与GDP增长之间的相互关系分析

采用Granger非因果检验的方法 ,分析得出金融资产中证券比重与GDP增长之间的相互关系     

农村劳动力转移和经济增长之间的协整分析

运用时间序列经济计量方法对1979--2005年我国农村劳动力转移在实际经济增长中的作用进行实证分析，结果证明农村劳动力转移与实际经济增长之间互为格兰杰因果关系，并在长期内稳定地存在着协同互动的均衡关系．实证结果肯定了农村劳动力转移在我国实际经济增长中的贡献，并检验了国外劳动力转移理论．