Trade openness and manufacturing growth in Malaysia

This study investigates the long-run relationship between trade openness and manufacturing growth and further assesses the causal relationship between these variables. Contrary to some scholars belief that at national level, openness does not contribute to growth in Malaysia, our sector specific analysis suggest otherwise. In this aspect, we believe that in any attempt to establish relationship between openness and growth, the analysis should be sector specific since it is more relevant as well as assures a meaningful insight for policy makers. The results suggest that in the long-run, trade openness is positively related to manufacturing growth in Malaysia. Furthermore, the results also suggest that openness should be viewed as the long term policy initiative for the sector to benefit. Therefore, the policy direction for Malaysian manufacturing sectors should focus on long term trade openness policies. Nevertheless, to ensure sustainability, emphasis should be placed on how (which manufacturing sub-sectors) or when openness is actually important. Importantly, policy makers and scholars should understand that leveraging the benefits of openness also depend on whether the liberalized sector has the comparative advantage.     

基于面板数据的风险投资与区域创新因果关系研究

本文采用面板的Granger因果检验,对1997-2008年间我国24个省市自治区风险投资与创新之间因果关系进行的实证研究结果表明,风险投资和专利授权均是一阶单整变量;且Kao检验、Johansen Fisher检验和Pedroni检验的协整检验结果也十分显著。这不仅说明了风险投资和专利授权变量间存在长期稳定的均衡关系,而且还验证了"风险投资先于创新"假说的成立。但却没有发现"创新先于风险投资"的显著证据。     

Causal inference with generalized structural mean models

Summary.  We estimate cause–effect relationships in empirical research where exposures are not completely controlled, as in observational studies or with patient non-compliance and self-selected treatment switches in randomized clinical trials. Additive and multiplicative structural mean models have proved useful for this but suffer from the classical limitations of linear and log-linear models when accommodating binary data. We propose the generalized structural mean model to overcome these limitations. This is a semiparametric two-stage model which extends the structural mean model to handle non-linear average exposure effects. The first-stage structural model describes the causal effect of received exposure by contrasting the means of observed and potential exposure-free outcomes in exposed subsets of the population. For identification of the structural parameters, a second stage 'nuisance' model is introduced. This takes the form of a classical association model for expected outcomes given observed exposure. Under the model, we derive estimating equations which yield consistent, asymptotically normal and efficient estimators of the structural effects. We examine their robustness to model misspecification and construct robust estimators in the absence of any exposure effect. The double-logistic structural mean model is developed in more detail to estimate the effect of observed exposure on the success of treatment in a randomized controlled blood pressure reduction trial with self-selected non-compliance.     

通货膨胀及紧缩与货币供应关系的实证分析

首先借用剑桥方程式建立了通货膨胀及紧缩与货币供应关系的理论模型,然后运用格兰杰因果检验的方法验证了我国超供货币供应是CPI物价指数的原因,而CPI物价指数作为超供货币供应的原因则被拒绝。说明了我国现阶段以货币供应量为中间目标调控经济的发展仍具较强实际意义。     

股指期货价格发现功能研究——基于印度Nifty50股指期货的实证分析

使用基于VECM（向量误差修正模型）的Granger因果关系检验法验证了印度Nifty50股指期货与现货市场之间的价格发现过程,结果发现现货市场在价格发现过程中占主导地位,在新兴市场国家的印度,股指期货缺乏价格发现功能。     

On Causal Inferences for Personalized Medicine: How Hidden Causal Assumptions Led to Erroneous Causal Claims About the D-Value

Abstract

Personalized medicine asks if a new treatment will help a particular patient, rather than if it improves the average response in a population. Without a causal model to distinguish these questions, interpretational mistakes arise. These mistakes are seen in an article by Demidenko that recommends the “D-value,” which is the probability that a randomly chosen person from the new-treatment group has a higher value for the outcome than a randomly chosen person from the control-treatment group. The abstract states “The D-value has a clear interpretation as the proportion of patients who get worse after the treatment” with similar assertions appearing later. We show these statements are incorrect because they require assumptions about the potential outcomes which are neither testable in randomized experiments nor plausible in general. The D-value will not equal the proportion of patients who get worse after treatment if (as expected) those outcomes are correlated. Independence of potential outcomes is unrealistic and eliminates any personalized treatment effects; with dependence, the D-value can even imply treatment is better than control even though most patients are harmed by the treatment. Thus, D-values are misleading for personalized medicine. To prevent misunderstandings, we advise incorporating causal models into basic statistics education.     

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.     

陕西省居民消费、投资与经济增长关系的协整研究

一、引言消费、投资与我国GDP之间的关系一直以来是宏观经济领域讨论的热点,学者们在这方面已经做出了很多有意义的分析和研究,他们普遍都认为消费和投资对我国的经济增长有促进作用,但是在消费、投资对我国GDP作用的大小以及它们之间的相互因果关系上面却存在着不同的观点。在     

Between dollarization and exchange rate volatility: Nigeria's portfolio diversification option

This paper investigates the relationship between nominal exchange rate volatility and dollarization in Nigeria by applying Granger causality test for the period 1986 (1)–2003 (4). Previous theoretical and empirical studies on this issue provided conflicting results. The empirical results of Granger causality test support a bi-directional relationship. However, causality from dollarization to exchange rate volatility appears stronger and dominates. This suggests that policies that aim to reduce exchange rate volatility in Nigeria must include measures that specifically address the issue of dollarization. An important factor in this case is the supply of sufficient domestic currency assets that would permit portfolio diversification and capable of dousing negative expectations about future inflation in the country.     

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.