Spectral Granger Causality Analysis Research Articles

How volatility in the oil market and uncertainty shocks affect Saudi economy: a frequency approach

In this study, spectral Granger causality analysis is employed to investigate the spectral dynamics of uncertainty transmission and its impact on economic growth and financial development in Saudi Arabia from 1993 to 2020. We examine the relationships between crude oil volatility, geopolitical risk, global economic uncertainty, financial development (measured by market capitalisation, MCGDP, Financial Institutions Access Index, FIAIX) and economic growth. The empirical results show that negative shocks in crude oil volatility have a significant impact on financial development as measured by the MCGDP, with capital flight and reduced domestic investment playing key roles, despite the effective contribution of increased government spending to mitigate these effects. In this study, spectral Granger causality analysis is employed to investigate the spectral dynamics of uncertainty transmission and its impact on economic growth and financial development in Saudi Arabia from 1993 to 2020. We examine the relationships between crude oil volatility, geopolitical risk, global economic uncertainty, financial development (measured by market capitalisation, MCGDP, Financial Institutions Access Index, FIAIX) and economic growth. The empirical results show that negative shocks in crude oil volatility have a significant impact on financial development as measured by MCGDP, with capital flight and lower domestic investment playing a key role, despite the effective contribution of increased government spending in mitigating these effects. However, looking at the FIAIX, crude oil volatility has a different impact, with positive shocks having no significant impact on financial development. In contrast, negative shocks show long-term causal effects, which emphasises the vulnerability of the banking sector to oil price fluctuations. Geopolitical risk has a significant long-term impact on the MCGDP due to uncertainty shocks caused by regional and global geopolitical measures. For geopolitical risk, the results are mixed with a significant causality of negative shocks on the FIAIX over certain frequencies, emphasising the sensitivity of the banking sector to geopolitical tensions. In contrast, the world economic uncertainty has only a limited direct impact on the FIAIX, indicating the resilience of the Saudi financial sector to fluctuations in global uncertainty. In terms of economic growth, positive shocks have a greater impact than negative shocks due to the volatility of crude oil. However, shocks resulting from geopolitical risks, whether positive or negative, have little effect on economic growth. The industrial production index, a measure of the resilience of the Saudi economy, indicates that it is susceptible to positive shocks from fluctuations in oil prices over a range of time periods. Our study’s findings can assist Saudi Arabia’s authorities in fortifying the country’s financial and economic resilience against the spread of uncertainty. For strong financial development and sustainable economic growth, these uncertainty elements must be well monitored.

The relationship between CO2 emissions, renewable energy and economic growth in the US: evidence from symmetric and asymmetric spectral granger causality analysis

The relationship between CO2 emissions, renewable energy and economic growth in the US: evidence from symmetric and asymmetric spectral granger causality analysis

Uncovering spatiotemporal dynamics of the corticothalamic network at ictal onset.

Although the clinical efficacy of deep brain stimulation targeting the anterior nucleus (AN) and centromedian nucleus (CM) of the thalamus has been actively investigated for the treatment of medication-resistant epilepsy, few studies have investigated dynamic ictal changes in corticothalamic connectivity in human electroencephalographic (EEG) recording. This study aims to establish the complex spatiotemporal dynamics of the ictal corticothalamic network associated with various seizure foci. We analyzed 10 patients (aged 2.7-28.1 years) with medication-resistant focal epilepsy who underwent stereotactic EEG evaluation with thalamic sampling. We examined both undirected and directed connectivity, incorporating coherence and spectral Granger causality analysis (GCA) between the diverse seizure foci and thalamic nuclei (AN and CM) at ictal onset. In our analysis of 36 seizures, coherence between seizure onset and thalamic nuclei increased across all frequencies, especially in slower bands (delta, theta, alpha). GCA showed increased information flow from seizure onset to the thalamus across all frequency bands, but outflows from the thalamus were mainly in slower frequencies, particularly delta. In the subgroup analysis based on various seizure foci, the delta coherence showed a more pronounced increase at CM than at AN during frontal lobe seizures. Conversely, in limbic seizures, the delta coherence increase was greater at AN compared to CM. It appears that the delta frequency plays a pivotal role in modulating the corticothalamic network during seizures. Our results underscore the significance of comprehending the spatiotemporal dynamics of the corticothalamic network at ictal onset, and this knowledge could guide personalized responsive neuromodulation treatment strategies.

Innovation, income, and waste disposal operations in Korea: evidence from a spectral granger causality analysis and artificial neural networks experiments

The aim of this paper is to assess the causal relationship among innovation in environment-related technologies, per capita income, and three major waste disposal operations (landfill, recycling, and incineration) for Korea. A time-series analysis over the frequency domain (Breitung–Candelon Spectral Granger causality) is applied, followed by Artificial Neural Networks experiments over the 1985–2016 period. Empirical results highlight that economic growth is tightly linked both to the growth of recycled waste and to the increase of environment-related innovations. Findings also highlight that waste recycling operations can spur the level of economic activity.

Coal Pricing in China: Is It a Bit Too Crude?

China is a global leader in methanol production volume, while coal is a major feedstock. The country also has the world’s largest commercial coal-to-methanol operations. Coal-based methanol is used widely within China and is a competitive substitute for gasoline. Owing to this, it is plausible that the price of coal may be linked to international crude oil prices, with methanol prices serving as the connecting channel. We add supporting evidence to a recently emerging area of literature and observe statistically significant relationships among the three prices, and, therefore, the influence from international crude oil and methanol prices on the coal price determination in China. This paper investigates the relationships among these prices for the period from January 2010 to December 2019 through spectral Granger causality analysis, alongside more traditional cointegration tests to develop a comprehensive picture of causal association between the price series in both the frequency and time domain. Cointegration is found in our tri-variate system while the frequency domain Granger causality tests reveal the long-run causality in all directions except from crude oil to methanol, thus, emphasizing the structure of coal price dependence. According to the generalized impulse response functions, the coal price reacts positively to shocks in crude oil prices.

Financial and economic development link in transitional economies: a spectral Granger causality analysis 1991?2017

Research background: The relationship between financial development and economic growth has been attracting attention in the field of economics since the times of the ?great moderation?. Previous empirical studies still fail to put forward a general conclusion on whether and how financial development affects economic growth. This is particularly true due to the lack of empirical research on the matter in question for countries in transition.
 Purpose of the article: This study aims to contribute to bridging the gap in the financial development-growth nexus in transitional economies. Understanding the mechanism behind financial development and economic growth should assist policymakers in the design of efficient economic policies or avoiding/alleviating financial cycles.
 Methods: Using Granger causality test in frequency domain, which shows to have more power over standard time domain Granger causality test, as well as gross domestic product (GDP) and the monetary base (M2 ? intermediate money), we investigated the finance-growth relationship in 19 Central, East, and Southeast European countries (CESEE) from 1991 to 2017.
 Findings & Value added: Study results show that financial development is important for growth in CESEE countries, thus supporting the ?supply-leading? theories in general for countries in the sample. Our findings indicate that the relationship between financial development and economic growth exists in CESEE countries (with one exception ? the Czech Republic) ranging from unidirectional (Albania, Bosnia and Hercegovina, Belarus, Estonia, Macedonia, Russia, Turkey), to bi-directional spectral Granger causality (Bulgaria, Croatia, Hungary, Kazakhstan, Latvia, Lithuania, Poland, Romania, Slovenia, Slovakia, Ukraine).

Persistent changes in cortical, subcortical and network-level dynamics induced by 10-Hz tACS applied over bilateral parietal cortex: a MEG study

Previous studies of the effects of tACS on brain dynamics report entrainment at the stimulation frequency, modulation of phase-phase and phase-amplitude relationships, and non-linear effects such as the generation of harmonic and subharmonic oscillatory activity. The majority of these investigations characterized the on-line effects of tACS in regions proximal to the stimulation electrodes. We utilized a 306-channel MEG array to characterize persistent changes in brain dynamics induced by alpha-band tACS. Eight adults with no neurological or mental disorders received 10-Hz stimulation over bilateral parietal cortex (EEG sites P3/P4; 1 mA; 20 min verum, 30 s sham). Participants performed a global/local visual attention task during and after stimulation. Spectro-temporal (TF) and spectral Granger causality measures were utilized to characterize changes in brain dynamics for cortical and subcortical nodes in the Default Mode Network (DMN) and Rich Club. Although there were frequency-, epoch- and task-related effects, verum vs. sham stimulation tended to upregulate gamma-band activity in the DMN nodes of left middle temporal and inferior parietal cortex, bilateral lateral occipital and medial orbitofrontal and bilateral crus I/II of cerebellum. Downregulation occurred primarily in the Rich Club nodes of right precuneus and right superior frontal cortex. There was little evidence for down-regulation within superior parietal cortex and hippocampus. A spectral Granger causality analysis revealed a complex dependence on brain region and task. Interestingly, all significant changes observed at 10, 20, 30, 40 and 70 Hz were consistently either increases or decreases in causality between ordered pairs of nodes. Causality was increased (decreased) following tACS for posterior cortical nodes in the DNM (Rich Club) networks. In contrast, posterior-to-frontal causal relationships increased for nodes in both networks. Changes in cortico-cerebellar relationships occurred only during attention to local features of visual images. The influence of hippocampus onto cortical nodes decreased for both tasks.

Interactions between the anterior cingulate-insula network and the fronto-parietal network during perceptual decision-making

Information processing in the human brain during cognitively demanding goal-directed tasks is thought to involve several large-scale brain networks, including the anterior cingulate-insula network (aCIN) and the fronto-parietal network (FPN). Recent functional MRI (fMRI) studies have provided clues that the aCIN initiates activity changes in the FPN. However, when and how often these networks interact remains largely unknown to date. Here, we systematically examined the oscillatory interactions between the aCIN and the FPN by using the spectral Granger causality analysis of reconstructed brain source signals from the scalp electroencephalography (EEG) recorded from human participants performing a face-house perceptual categorization task. We investigated how the aCIN and the FPN interact, what the temporal sequence of events in these nodes is, and what frequency bands of information flow bind these nodes in networks. We found that beta band (13–30Hz) and gamma (30–100Hz) bands of interactions are involved between the aCIN and the FPN during decision-making tasks. In gamma band, the aCIN initiated the Granger causal control over the FPN in 25–225 ms timeframe. In beta band, the FPN achieved a control over the aCIN in 225–425 ms timeframe. These band-specific time-dependent Granger causal controls of the aCIN and the FPN were retained for behaviorally harder decision-making tasks. These findings of times and frequencies of oscillatory interactions in the aCIN and FPN provide us new insights into the general neural mechanisms for sensory information-guided, goal-directed behaviors, including perceptual decision-making processes.

Changes in effective connectivity of sensorimotor rhythms in thalamocortical circuits during the induction and recovery of anesthesia in mice

The thalamocortical network serves a role in both consciousness and sensorimotor processing. However, little is known regarding how changes in conscious states, via induction of and recovery from anesthesia, affect the processing of sensorimotor information in the thalamocortical network. To address this, we investigated the dynamics of causal interactions among sensorimotor rhythms (SMR; frequency range of 3–12Hz) across the thalamocortical network during transitions into and out of ketamine-induced unconsciousness. Two local field potentials from the ventral lateral and ventrobasal thalamic nuclei, as well as two intracranial electroencephalography signals from the primary sensory and primary motor regions, were recorded in 10 mice. Spectral Granger causality analysis revealed two distinct frequency-specific patterns in sensorimotor rhythms. For the low-frequency (3–6.5Hz) SMR, loss of consciousness evoked causal influences directed from the cortex to the thalamus. For the high-frequency (6.5–12Hz) SMR, causal influences from the primary sensory cortex to other regions during the conscious period were abruptly altered by loss of consciousness and gradually regenerated following recovery of consciousness. The results of the present study indicate that anesthesia alters the flow of sensorimotor information in the thalamocortical network and may provide evidence of the neural basis of loss and recovery of sensorimotor function associated with anesthesia.

A Comparison of Methods Reveals that Enhanced Diffusion Helps Explain Cold-Season Soil CO2 Efflux in a Lodgepole Pine Ecosystem

Wintertime respiration contributes significantly to the annual loss of carbon from terrestrial ecosystems to the atmosphere, but the magnitude and physical transport mechanisms of this flux through snow remain unclear. Here, we quantify wintertime soil CO2 efflux in a Lodgepole pine (Pinus contorta Dougl.) forest by comparing chamber, flux gradient, and subcanopy eddy covariance measurements. CO2 efflux estimates from the flux gradient system deviated from the eddy covariance measurements during early and late winter but were only ca. 25% lower than eddy covariance measurements during the main snow accumulation period in mid-winter. During the snow-covered period, the flux gradient carbon efflux estimate (15gCm−2) was ca. three-fold less than eddy covariance measurements (49gCm−2). An analysis of the relationship between friction velocity and eddy covariance-measured CO2 efflux lends support to the notion that advection through snow is an important transport mechanism for trace gasses. A spectral Granger causality analysis indicates that the wind speed time series contributes information to the subnivean CO2 concentration time series during the melt period at time scales greater than 10hours. All three methodologies indicate that wintertime respiration is a major contributor to the annual carbon budget: the sum of eddy covariance-measured CO2 efflux during the snow-covered period was 1/3 of that during the snow-free period of 2011 (ca. 140gCm−2). Future studies should incorporate adjustments for advection when using snow flux gradient systems to avoid underestimating the often-underappreciated contribution of the cold season to ecosystem CO2 efflux.

Granger causality analysis reveals distinct spatio-temporal connectivity patterns in motor and perceptual visuo-spatial working memory.

We employed spectral Granger causality analysis on a full set of 56 electroencephalographic recordings acquired during the execution of either a 2D movement pointing or a perceptual (yes/no) change detection task with memory and non-memory conditions. On the basis of network characteristics across frequency bands, we provide evidence for the full dissociation of the corresponding cognitive processes. Movement-memory trial types exhibited higher degree nodes during the first 2 s of the delay period, mainly at central, left frontal and right-parietal areas. Change detection-memory trial types resulted in a three-peak temporal pattern of the total degree with higher degree nodes emerging mainly at central, right frontal, and occipital areas. Functional connectivity networks resulting from non-memory trial types were characterized by more sparse structures for both tasks. The movement-memory trial types encompassed an apparent coarse flow from frontal to parietal areas while the opposite flow from occipital, parietal to central and frontal areas was evident for the change detection-memory trial types. The differences among tasks and conditions were more profound in α (8–12 Hz) and β (12–30 Hz) and less in γ (30–45 Hz) band. Our results favor the hypothesis which considers spatial working memory as a by-product of specific mental processes that engages common brain areas under different network organizations.

Soil CO2 Dynamics in a Tree Island Soil of the Pantanal: The Role of Soil Water Potential

The Pantanal is a biodiversity hotspot comprised of a mosaic of landforms that differ in vegetative assemblages and flooding dynamics. Tree islands provide refuge for terrestrial fauna during the flooding period and are particularly important to the regional ecosystem structure. Little soil CO2 research has been conducted in this region. We evaluated soil CO2 dynamics in relation to primary controlling environmental parameters (soil temperature and soil water). Soil respiration was computed using the gradient method using in situ infrared gas analyzers to directly measure CO2 concentration within the soil profile. Due to the cost of the sensors and associated equipment, this study was unreplicated. Rather, we focus on the temporal relationships between soil CO2 efflux and related environmental parameters. Soil CO2 efflux during the study averaged 3.53 µmol CO2 m−2 s−1, and was equivalent to an annual soil respiration of 1220 g C m−2 y−1. This efflux value, integrated over a year, is comparable to soil C stocks for 0–20 cm. Soil water potential was the measured parameter most strongly associated with soil CO2 concentrations, with high CO2 values observed only once soil water potential at the 10 cm depth approached zero. This relationship was exhibited across a spectrum of timescales and was found to be significant at a daily timescale across all seasons using conditional nonparametric spectral Granger causality analysis. Hydrology plays a significant role in controlling CO2 efflux from the tree island soil, with soil CO2 dynamics differing by wetting mechanism. During the wet-up period, direct precipitation infiltrates soil from above and results in pulses of CO2 efflux from soil. The annual flood arrives later, and saturates soil from below. While CO2 concentrations in soil grew very high under both wetting mechanisms, the change in soil CO2 efflux was only significant when soils were wet from above.

GMAC: A Matlab toolbox for spectral Granger causality analysis of fMRI data

Investigation of causal interactions within brain networks using Granger causality analysis (GCA) is a key challenge in studying neural activity on the basis of functional magnetic resonance imaging (fMRI). The article describes an open-source software toolbox GMAC (Granger multivariate autoregressive connectivity) implementing multivariate spectral GCA. Available features are: fMRI data importing/exporting, network nodes definition, time series preprocessing, multivariate autoregressive modeling, spectral Granger causality indexes estimation, statistical significance assessment using surrogate data, network analysis and visualization of connectivity results. All functions have been integrated into a user-friendly graphical interface developed in the Matlab environment, easily accessible to both technical and clinical users.