Solving the budget deficit problem is a concern for many countries; some economists emphasized tax increases or tax cuts, while others favour spending cuts. This paper investigates the interrelationship between total government expenditure and total tax revenue in Barbados using both bivariate and multivariate cointegrating models. The technique of Granger Causality is also applied to determine...

Causal prediction has become a popular tool for neuroscience applications, as it allows the study of relationships between different brain areas during rest, cognitive tasks or brain disorders. We propose a nonparametric approach for the estimation of nonlinear causal prediction for multivariate time series. In the proposed estimator, C NPMR , Autoregressive modeling is replaced by Nonparametri...

This paper examines empirically the causal relationship among the degree of openness of the economy, financial development and economic growth by using a multivariate autoregressive VAR model in Greece for the examined period 1960:Ι – 2000:IV. The results of cointegration analysis suggest that there is one cointegrated vector among GDP, financial development and the degree of openness of the ec...

We relate notions of structural causality and conditional exogeneity as de…ned in White and Chalak (2006) (WC) to the concept of Granger causality. We show that given conditional exogeneity, structural non-causality implies retrospective Granger non-causality, an extension of the classical Granger (1969) non-causality condition. We also provide a form of converse to this result and tests for re...

This paper analyzes empirically the effect of crude oil price change on the economic growth of Indian-Subcontinent (India, Pakistan and Bangladesh). We use a multivariate Vector Autoregressive analysis followed by Wald Granger causality test and Impulse Response Function (IRF). Wald Granger causality test results show that only India’s economic growth is significantly affected when crude oil pr...

parkinson’s disease (pd) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. specific changes associated with various pathological attacks in parkinson’s disease can be indicated in causality interactions of the brain network from resting state fmri data. in this paper, we aimed to reveal the network architecture of the directed influence brain n...

T his study evaluates the causality relationship between human capital and foreign direct investment inflow in twenty-six OIC (the Organization of Islamic Cooperation) countries over the period 1970–2014. We employed the panel Granger non-causality testing approach of Kònya (2006) that is based on seemingly unrelated regression (SUR) systems, and Wald tests with country specific boot...

iran is one of the most concentrated areas of afghan migrants and refugees. most afghans dispersed throughout the country mixed with iranian households. the majority of afghan immigrants are typically unskilled and illegal workers. this study aims at investigating the nature of the causal relationship between afghan immigrants and two main labor market indicators, average wages and unemployment...

Co-circulation of respiratory syncytial virus (RSV) and influenza has made the partitioning of morbidity and mortality from each virus difficult. Given the interaction between chronic obstructive lung disease (COPD) and pneumonia, often one can be mistaken for the other. Multivariate time-series methodology was applied to examine the impact of RSV and influenza on hospital admissions for bronch...

Assessing directed functional connectivity from time series data is a key challenge in neuroscience. One approach to this problem leverages a combination of Granger causality analysis and network theory. This article describes a freely available MATLAB toolbox--'Granger causal connectivity analysis' (GCCA)--which provides a core set of methods for performing this analysis on a variety of neuros...