scholarly journals Frequency Domain Repercussions of Instantaneous Granger Causality

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 1037
Author(s):  
Luiz A. Baccalá ◽  
Koichi Sameshima
Keyword(s):  
Time Series ◽  
Transfer Function ◽  
Frequency Domain ◽  
Granger Causality ◽  
Partial Directed Coherence ◽  
Directed Transfer Function ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive ◽  
Standard Vector ◽  
Domain Description

Using directed transfer function (DTF) and partial directed coherence (PDC) in the information version, this paper extends the theoretical framework to incorporate the instantaneous Granger causality (iGC) frequency domain description into a single unified perspective. We show that standard vector autoregressive models allow portraying iGC’s repercussions associated with Granger connectivity, where interactions mediated without delay between time series can be easily detected.

scholarly journals Frequency Domain Repercussions of Instantaneous Granger Causality

2021 ◽  
Author(s):  
Luiz Antonio Baccalá ◽  
Koichi Sameshima
Keyword(s):  
Time Series ◽  
Transfer Function ◽  
Frequency Domain ◽  
Granger Causality ◽  
Partial Directed Coherence ◽  
Directed Transfer Function ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive ◽  
Standard Vector ◽  
Domain Description

Using Directed Transfer Function (DTF) and Partial Directed Coherence (PDC) in their information version, this paper extends their theoretical framework to incorporate instantaneous Granger Causality (iGC)’s frequency domain description into a single unified perspective. We show that standard vector autoregressive models allow portraying iGC’s repercussions associated with Granger Connectivity where interactions mediated without delay between time series can be easily detected.

scholarly journals The impact of latent confounders in directed network analysis in neuroscience

2013 ◽  
Vol 371 (1997) ◽  
pp. 20110612 ◽  
Author(s):  
Rebecca Ramb ◽  
Michael Eichler ◽  
Alex Ing ◽  
Marco Thiel ◽  
Cornelius Weiller ◽  
...  
Keyword(s):  
Network Analysis ◽  
Nonlinear System ◽  
Granger Causality ◽  
Directed Network ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive ◽  
Physiological Pathways ◽  
The Impact ◽  
The Brain ◽  
Past Activity

In the analysis of neuroscience data, the identification of task-related causal relationships between various areas of the brain gives insights about the network of physiological pathways that are active during the task. One increasingly used approach to identify causal connectivity uses the concept of Granger causality that exploits predictability of activity in one region by past activity in other regions of the brain. Owing to the complexity of the data, selecting components for the analysis of causality as a preprocessing step has to be performed. This includes predetermined—and often arbitrary—exclusion of information. Therefore, the system is confounded by latent sources. In this paper, the effect of latent confounders is demonstrated, and paths of influence among three components are studied. While methods for analysing Granger causality are commonly based on linear vector autoregressive models, the effects of latent confounders are expected to be present also in nonlinear systems. Therefore, all analyses are also performed for a simulated nonlinear system and discussed with regard to applications in neuroscience.

scholarly journals Exports as a Determinant of Inflation in Kenya: Disaggregated Econommetric Analysis

2017 ◽  
Vol 13 (10) ◽  
pp. 417
Author(s):  
Evans Ovamba Kiganda ◽  
Scholastica Adhiambo ◽  
Nelson Obange
Keyword(s):  
Time Series ◽  
Central Bank ◽  
Granger Causality ◽  
Impulse Response ◽  
Response Analysis ◽  
Vector Autoregressive ◽  
Impulse Response Analysis ◽  
Long Run ◽  
The Government ◽  
The Relationship

The purpose of this study was to examine exports as a determinant of inflation in Kenya: A disaggregated econometric analysis with specific objectives of establishing the relationship between domestic exports and inflation in Kenya and determining the relationship between re - exports and inflation in Kenya. This was occasioned by inconclusive and incomprehensive analysis on the relationship between exports and inflation given mixed results and failure by scholars to disaggregate total exports into domestic exports and re-exports. Correlation research design was employed using monthly time series obtained from Central Bank of Kenya (CBK) data spanning 132 months from January 2005 to December 2015.Vector Autoregressive (VAR) techniques of cointegration, Granger causality and impulse response analysis were employed. Results indicated a significant positive and negative long run relationship between domestic exports and re- exports with inflation in Kenya respectively that were supported by the impulse response analysis. A unidirectional causality running from domestic exports to inflation and re-exports to inflation was also established. The study concluded that domestic exports and re-exports determine inflation in Kenya with domestic exports having greater influence and therefore recommended that the government of Kenya needs to advocate for a trade policy that aims at reducing exports of domestically produced products and increase re-exports. This will ensure that only surplus is exported to reduce shortage of domestically produced commodities hence a reduction in price for the products.

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