On hysteretic vector autoregressive model with applications

This paper proposes a new hysteretic vector autoregressive (HVAR) model in which the regime switching may be delayed when the hysteresis variable lies in a hysteresis zone. We integrate an adapted multivariate Student-t distribution from amending the scale mixtures of normal distributions. This HVAR model allows for a higher degree of flexibility in the degrees of freedom for each time series. We use the proposed model to test for a causal relationship between any two target time series. Using posterior odds ratios, we overcome the limitations of the classical approach to multiple testing. Both simulated and real examples herein help illustrate the suggested methods. We apply the proposed HVAR model to investigate the causal relationship between the quarterly growth rates of gross domestic product of United Kingdom and United States. Moreover, we check the pairwise lagged dependence of daily PM2.5 levels in three districts of Taipei.     

论刑法因果关系

无论在刑法理论上,还是在刑法实践上,刑法因果关系都是一个极其重要而又极其复杂的问题。而刑法偶然因果关系能否成立的答案则存在于内外因对立统一原理、必然性与偶然性对立统一原理、因果性与必然性、偶然性辩证统一原理、原因与条件的区别之中,并在刑法实践中得到最终验证。如果刑法偶然因果关系难以成立,则刑法必然因果关系本身也是有问题的。     

Variance (Non) Causality in Multivariate GARCH

This paper extends the current literature on the variance-causality topic providing the coefficient restrictions ensuring variance noncausality within multivariate GARCH models with in-mean effects. Furthermore, this paper presents a new multivariate model, the exponential causality GARCH. By the introduction of a multiplicative causality impact function, the variance causality effects becomes directly interpretable and can therefore be used to detect both the existence of causality and its direction; notably, the proposed model allows for increasing and decreasing variance effects. An empirical application evidences negative causality effects between returns and volume of an Italian stock market index future contract.     

中国A、B股市场相关性与协整性的实证研究

运用相关、协整和因果关系检验等计量经济学方法对中国AB股市场之间的相关性与协整性进行了实证研究,以期找出股市间价格波动的运行规律。结果表明,B股市场对境内投资者开放后,沪深两市A股与B股之间开始存在协整关系,并且沪市的A股市场是先于B股市场的,而深市AB股市场之间不存在先导性。研究结果为判断和分析中国股票市场的基本特征和投资者行为,提供了一定的参考依据。     

我国房地产市场财富效应的实证分析

本文应用格兰杰因果关系检验和协整分析方法,对我国房地产市场的财富效应作了实证分析。实证结果表明,我国房地产市场不具有财富效应而仅具有替代效应。     

政府公共支出与中国经济增长——基于VAR方法的研究

基于协整理论和向量误差修正模型,考察了政府公共支出对中国经济增长的长期影响及二者之间的互动关系.研究发现:(1)多项公共支出变量为非平稳的二阶单整并与总产出及全社会固定资本形成额等经济变量存在长期均衡关系;(2)非生产性支出与经济增长正相关,生产性支出、政府机构支出与经济增长负相关;(3)非生产性支出是经济增长的长期原因,而经济增长只是政府机构支出增加的长期原因.经济增长反方向促进非生产性支出和生产性支出增加在统计学上并不显著.     

An analytic method for randomized trials with informative censoring: Part 1

Consider a randomized trial in which time to the occurrence of a particular disease, say pneumocystis pneumonia in an AIDS trial or breast cancer in a mammographic screening trial, is the failure time of primary interest. Suppose that time to disease is subject to informative censoring by the minimum of time to death, loss to and end of follow-up. In such a trial, the censoring time is observed for all study subjects, including failures. In the presence of informative censoring, it is not possible to consistently estimate the effect of treatment on time to disease without imposing additional non-identifiable assumptions. The goals of this paper are to specify two non-identifiable assumptions that allow one to test for and estimate an effect of treatment on time to disease in the presence of informative censoring. In a companion paper (Robins, 1995), we provide consistent and reasonably efficient semiparametric estimators for the treatment effect under these assumptions. In this paper we largely restrict attention to testing. We propose tests that, like standard weighted-log-rank tests, are asymptotically distribution-free -level tests under the null hypothesis of no causal effect of treatment on time to disease whenever the censoring and failure distributions are conditionally independent given treatment arm. However, our tests remain asymptotically distribution-free -level tests in the presence of informative censoring provided either of our assumptions are true. In contrast, a weighted log-rank test will be an -level test in the presence of informative censoring only if (1) one of our two non-identifiable assumptions hold, and (2) the distribution of time to censoring is the same in the two treatment arms. We also extend our methods to studies of the effect of a treatment on the evolution over time of the mean of a repeated measures outcome, such as CD-4 count.     

Testing Wagner's Law in India: A cointegration and causality analysis

The present study empirically analyzes the validity of Wagner's Law for Indian economy. With the use of annual time series data from 1970–71 to 2013–14, all the six versions of Wagner's Law have been analyzed to test the relationship between government expenditure and gross domestic product. Wagner's Law states that the economic growth is the causative factor of the growth of the public expenditure. The study applied the unit root test and cointegration test to find the long-run relationship between government expenditure and gross domestic product. The present study employed the various econometric techniques such as unit root test, cointegration, and causality analysis for empirical analysis. The empirical analysis under study inferred mixed results of Wagner's Law for Indian economy, where four versions, namely Peacock, Gupta, Guffman, and Musgrave, found valid for Indian economy. The study concluded that the Wagner's Law is valid for the Indian economy except the Pryor and Mann Versions of the Wagner's Law.     

Causal structure among US corn futures and regional cash prices in the time and frequency domain

This study investigates causal structure among daily Chicago Board of Trade corn futures prices and seven regional cash series from Iowa, Illinois, Indiana, Ohio, Minnesota, Nebraska, and Kansas for January 2006–March 2011. Their wavelet transformed series are further analyzed for causal relationships at different time scales. Empirical results indicate no causality among states or between the futures and a cash series for time scales shorter than one month. As scales increase but do not exceed a year, bidirectional causal flows are determined among all prices. The information leadership role of the futures against a cash price is identified for the scale longer than one year and raw series, at which no interstate causality is found.     

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.