Measures of Conditional Linear Dependence and Feedback Between Time Series

Geweke, John

doi:10.2307/2288723

Cited by 295 publications

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“…Strictly speaking, this is true only under certain conditions, which always hold in the empirical work reported below. See Geweke (1982Geweke ( , 1984 for a statement of these conditions. 7.…”

Section: Discussionmentioning

confidence: 99%

“…12 Tests of the null hypothesis that these measures are zero are not reported since the asymptotic distribution theory involved is extremely difficult. Instead, estimates corrected for small sample bias and confidence intervals are computed using a bootstrap procedure (Efron, 1982;and Geweke, 1984). 13…”

Section: Estimation Of Conditional Feedback Between Popularity and Momentioning

confidence: 99%

“…Section two briefly and informally introduces the concept of conditional linear feedback due to Geweke (1982Geweke ( , 1984, which is well suited to the investigation of political business cycles, develops its application in the present context, and compares this methodology with the more familiar monetary reaction-function approach. A complete description of the methodology used here may be found in the work of Geweke cited above.…”

Section: Introductionmentioning

confidence: 99%

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Money and politics in a small open economy

Winer

1986

Public Choice

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A time series analysis indicates monetary growth and the Gallup Poll in Canada are systematically related at 'electoral cycle' periodicities (5 to 20 quarters) under flexible exchange rates, and demonstrates the absence of an electoral component in Canadian monetary growth under fixed rates. These results confirm empirically a widely accepted extension of the Mundell-Fleming argument that monetary policy is effective only under flexible rates, which to my knowledge has not before been directly investigated: international constraints on the small open economy under fixed rates lead to the abandonment of monetary policy as an active instrument in electoral politics.

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Section: Discussionmentioning

confidence: 99%

Section: Estimation Of Conditional Feedback Between Popularity and Momentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Money and politics in a small open economy

Winer

1986

Public Choice

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“…However, if both brain regions A and B are driven by region C, but with a different lag, then there will be Granger causality between A and B (Gao et al 2008). In order to handle this issue, an important extension of Granger's original definition of causality to the multivariate case, called CGCA, was proposed by Geweke (1984). For three or more simultaneous time-courses, the causal relation between any two of the courses may be direct, mediated by a third one, or a combination of both.…”

Section: Methodologic Considerationsmentioning

confidence: 99%

“…Another important extension of Granger's original definition of causality is the consideration of the multivariate case: For three or more simultaneous time series, the causal relation between any two of the series may be direct, mediated by a third one, or a combination of both. Recently, the conditional Granger causality analysis (CGCA) (Geweke 1984) has been proposed to estimate functional coupling effectively in multivariate data sets (Chen et al 2006;Zhou et al 2009). …”

Section: Introductionmentioning

confidence: 99%

Evaluating the effective connectivity of resting state networks using conditional Granger causality

et al. 2009

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The human brain has been documented to be spatially organized in a finite set of specific coherent patterns, namely resting state networks (RSNs). The interactions among RSNs, being potentially dynamic and directional, may not be adequately captured by simple correlation or anticorrelation. In order to evaluate the possible effective connectivity within those RSNs, we applied a conditional Granger causality analysis (CGCA) to the RSNs retrieved by independent component analysis (ICA) from resting state functional magnetic resonance imaging (fMRI) data. Our analysis provided evidence for specific causal influences among the detected RSNs: default-mode, dorsal attention, core, central-executive, self-referential, somatosensory, visual, and auditory networks. In particular, we identified that self-referential and default-mode networks (DMNs) play distinct and crucial roles in the human brain functional architecture. Specifically, the former RSN exerted the strongest causal influence over the other RSNs, revealing a top-down modulation of self-referential mental activity (SRN) over sensory and cognitive processing. In quite contrast, the latter RSN was profoundly affected by the other RSNs, which may underlie an integration of information from primary function and higher level cognition networks, consistent with previous task-related studies. Overall, our results revealed the causal influences among these RSNs at different processing levels, and supplied information for a deeper understanding of the brain network dynamics.

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Granger Causality: Basic Theory and Application to Neuroscience

Ding

Chen

Bressler

2006

Handbook of Time Series Analysis

535

521

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Multi-electrode neurophysiological recordings produce massive quantities of data. Multivariate time series analysis provides the basic framework for analyzing the patterns of neural interactions in these data. It has long been recognized that neural interactions are directional. Being able to assess the directionality of neuronal interactions is thus a highly desired capability for understanding the cooperative nature of neural computation. Research over the last few years has shown that Granger causality is a key technique to furnish this capability. The main goal of this article is to provide an expository introduction to the concept of Granger causality. Mathematical frameworks for both bivariate Granger causality and conditional Granger causality are developed in detail with particular emphasis on their spectral representations. The technique is demonstrated in numerical examples where the exact answers of causal influences are known.It is then applied to analyze multichannel local field potentials recorded from monkeys performing a visuomotor task. Our results are shown to be physiologically interpretable and yield new insights into the dynamical organization of large-scale oscillatory cortical networks.

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Measures of Conditional Linear Dependence and Feedback Between Time Series

Cited by 295 publications

References 0 publications

Money and politics in a small open economy

Money and politics in a small open economy

Evaluating the effective connectivity of resting state networks using conditional Granger causality

Granger Causality: Basic Theory and Application to Neuroscience

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