To investigate the causal relationship between China’s domestic tourism and economic growth, this paper performs co-integration analysis and Granger causality test by making use of annual time series data from 1984 to 2009. Co-integration analysis indicates that there are long-term and stable equilibrium relationships between the development of China’s domestic tourism and economic growth. The ...

The communication among neuronal populations, reflected by transient synchronous activity, is the mechanism underlying the information processing in the brain. Although it is widely assumed that the interactions among those populations (i.e. functional connectivity) are highly nonlinear, the amount of nonlinear information transmission and its functional roles are not clear. The state of the ar...

The present investigation examined the temporal relationships between changes in coronary artery heart disease (CAHD) mortality rates from whites (1938-1980) and changes in national measures of dietary elements, tobacco consumption, alcohol consumption, and unemployment. The magnitude and latency of the causal relationships were estimated with the use of cross-lagged correlation functions (CCFs...

In this paper an effort is made in order to investigate the nexus of dynamic interrelations between the general macroeconomic environment of Greek economy with a special reference to the real wages determination. For the causality analysis among real wages, consumer price index, labour productivity, unemployment rate and gross domestic product a multivariate autoregressive VAR model was used, c...

In this paper we develop a dynamic discrete-time bivariate probit model, in which the conditions for Granger non-causality can be represented and tested. The conditions for simultaneous independence are also worked out. The model is extended in order to allow for covariates, representing individual as well as time heterogeneity. The proposed model can be estimated by Maximum Likelihood. Granger...

In recent years, the study of causality in the brain, or effective connectivity, has become increasingly important in the field of computational neuroscience. Neuroimaging modalities such as EEG, fMRI and MEG provide an immense and rich source of data. Causal analysis has the potential to help make sense of this complex data, and provide important insights about the neural basis of cognition. T...

This paper examines empirically the tourism impact on the long-run economic growth of Greece by using the causality analysis among real gross domestic product, real effective exchange rate and international tourism earnings. A multivariate autoregressive VAR model is applied for the examined period 1960:Ι – 2000:IV. The results of cointegration analysis suggested that there is one cointegrated ...

Atlantic tropical cyclones have been getting stronger recently with a trend that is related to an increase in the late summer/early fall sea-surface temperature over the North Atlantic. Some studies attribute the increasing ocean warmth and hurricane intensity to a natural climate fluctuation, known as the Atlantic Multidecadal Oscillation; others suggest that climate change related to anthropo...

We propose applying the linear Granger Causality concept to very high-dimensional time series. The approach is based on integrating dimensionality reduction into a multivariate time series model. If residuals of dimensionality reduced models can be transformed back into the original space, prediction errors in the high–dimensional space may be computed, and a Granger Causality Index (GCI) is pr...