this paper examines the impact of government expenditure on the nigerian economy for the period 1983 - 2012. the government expenditure components used as the explanatory variables in the model are: expenditures on health, education, defense, agriculture and transportation and communication. the gross domestic product (gdp) was used as a parameter for measuring economic growth. in order to esta...

We introduce graphical time series models for the analysis of dynamic relationships among variables in multivariate time series. The modelling approach is based on the notion of strong Granger causality and can be applied to time series with non-linear dependencies. The models are derived from ordinary time series models by imposing constraints that are encoded by mixed graphs. In these graphs ...

BACKGROUND Understanding circuit function would be greatly facilitated by methods that allow the simultaneous estimation of the functional strengths of all of the synapses in the network during ongoing network activity. Towards that end, we used Granger causality analysis on electrical recordings from the pyloric network of the crab Cancer borealis, a small rhythmic circuit with known connectiv...

We introduce graphical time series models for the analysis of dynamic relationships among variables in multivariate time series. The modelling approach is based on the notion of strong Granger causality and can be applied to time series with non-linear dependencies. The models are derived from ordinary time series models by imposing constraints that are encoded by mixed graphs. In these graphs,...

We analyze the relations between Granger (G) non-causality and a notion of structural causality arising naturally from a general nonseparable recursive dynamic structural system. Building on classical notions of G non-causality, we introduce interesting and natural extensions, namely weak G non-causality and retrospective weakG non-causality. We show that structural non-causality and certain (r...

This paper focuses on the causality relation between US and the several Asia-pacific markets (Japan, China, Hong Kong, Taiwan, Singapore, Korea, and Indonesia). We check the causality of the co-movement among the markets across Pacific by using Granger-Causality test, VAR, and event studying on unexpected high volatile period. Our tests show that U.S. and Japan have strong influence to other As...

"The dynamic relationship of net migration and employment change is examined for ten selected states of the U.S. using a multivariate time series approach--a vector autoregression (VAR) model. Granger causality tests and dynamic multipliers provide information on the dynamic process. The results suggest a state-level process in which employment change occurs first, and net migration follows wi...

Granger causality analysis is becoming central for the analysis of interactions between neural populations and oscillatory networks. However, it is currently unclear whether single-trial estimates of Granger causality spectra can be used reliably to assess directional influence. We addressed this issue by combining single-trial Granger causality spectra with statistical inference based on gener...

Causality discovery has been one of the core tasks in scientific research since the beginning of human scientific history. In the age of data tsunami, the task could involve millions of variables, which cannot be achieved feasibly by human. However, the causal discovery using artificial intelligence and statistical techniques in non-experimental settings faces several challenges. In this work, ...

This paper investigates the dynamic relationship between volatility, volume and open interest in CSI 300 futures market using asymmetric GARCH model, Granger causality test, variance decomposition and impulse response function based on 1-min data. ARMA-EGARCH model is employed and find that both contemporaneous and lagged volume is positively related to volatility, and current open interest has...