Granger Causality Method Research Articles

The Linkage between Imported Energy and Trade in Taiwan

This study examines the Granger causality between Taiwan's aggregate and disaggregate energy consumption and trade variables, including total imports (IM), total exports (EX), total energy consumption (ENERGY), oil and petroleum products consumption (OIL), coal and coal products consumption (COAL), natural gas consumption (GAS), export value of the industrial sector (EX_I), export value of heavy-chemical industrial products (EX_HI), and export value of non-heavy-chemical industrial products (EX_NHI) with monthly data during 1998–2009. Via applying Hsiao's version of the Granger causality method, the results find causality running from ENERGY to IM, EX, EX_I, and EX_HI. The impulse-response simulations show that the above relations have positive responses at the initial period. OIL Granger causes all trade variables. The impulse directions to IM and EX_NHI are negative, whereas others are positive. On the other hand, COAL responds to impulses in all trade variables. The impulse-response simulations show that these relations have positive responses at the initial period except for causality running from EX_HI and EX_NHI to COAL. GAS positively responds to impulses in EX, EX_I, and EX_HI at the initial period. The bidirectional Granger causality between pairs of variables (such as GAS and EX_NHI as well as GAS and EX_HI) is found.

Internationalisation, growth and pay inequality: a cointegration analysis for Turkey, 1970–2007

The nature of the internationalisation-growth-inequality nexus is very complex; and therefore, not surprisingly, there is no consensus on whether increasing openness to trade leads to higher inequality or not – in fact, there is even no full understanding on the impact of the openness on the economic growth. In the case of Turkey it is observed that there is relatively little empirical work that addresses the issue of inequality. Considering this fact, the study aims to provide some more evidence on the complex relationship between trade openness, foreign direct investment, economic growth and pay inequality by utilising a combination of different Theil Indices of pay inequality. The paper utilises the Johansen Cointegration and Granger Causality methods. Our findings yield that higher economic growth resulting from trade openness comes with higher pay inequality.

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.

Economic Growth and Electricity Consumption in Africa: MS-VAR and MS-Granger Causality Analysis

Knowledge of the direction of the causality between electricity consumption and economic growth is of primary importance if appropriate energy policies and energy conservation measures are to be devised. This study estimates the causality relationship between electricity consumption and economic growth by Markov Switching Vector Auto Regression (VAR) and Markov Switching Granger Causality methods for some countries in Africa (7 Countries) and Asia(Brunei); Brunei, Cameron, Cote d'Ivoire, Nigeria, South Africa, Togo and Zimbabwe. The results from MS-VAR models show that in regime one, two and three, Electricity Consumption (EC) is the Granger cause of the Gross Domestic Product (GDP) and GDP is the Granger cause of the EC. In sum, we find some evidence of bidirectional GC between the EC and the GDP.

Evaluation of Causal Influences in Model of Motor Control in Left Hands Movement-Readiness State

The previous research revealed some functional coupling among nodes in model of motor control in human brain, which described nondirectional synchronous actions among these nodes during movement-readiness state. However, causal relationships among these nodes were still lack, which represented some directional interactions among these nodes in movement-readiness state. In the present study, we used functional magnetic resonance imaging (fMRI) and conditional Granger causality (CGC) method to investigate the interactions in model of motor control in movement-readiness state. Our result showed that upper precuneus and cingulate motor area revealed net causal influences with contralateral supplementary motor areas and contralateral caudate nucleus during the left hands movement-readiness state. Moreover, the results of Out-In degrees indicated that bilateral primary sensorimotor areas revealed competitive relationship during left hands movement-readiness.

Identification of feedback loops in neural networks based on multi-step Granger causality

Feedback circuits are crucial network motifs, ubiquitously found in many intra- and inter-cellular regulatory networks, and also act as basic building blocks for inducing synchronized bursting behaviors in neural network dynamics. Therefore, the system-level identification of feedback circuits using time-series measurements is critical to understand the underlying regulatory mechanism of synchronized bursting behaviors. Multi-Step Granger Causality Method (MSGCM) was developed to identify feedback loops embedded in biological networks using time-series experimental measurements. Based on multivariate time-series analysis, MSGCM used a modified Wald test to infer the existence of multi-step Granger causality between a pair of network nodes. A significant bi-directional multi-step Granger causality between two nodes indicated the existence of a feedback loop. This new identification method resolved the drawback of the previous non-causal impulse response component method which was only applicable to networks containing no co-regulatory forward path. MSGCM also significantly improved the ratio of correct identification of feedback loops. In this study, the MSGCM was testified using synthetic pulsed neural network models and also in vitro cultured rat neural networks using multi-electrode array. As a result, we found a large number of feedback loops in the in vitro cultured neural networks with apparent synchronized oscillation, indicating a close relationship between synchronized oscillatory bursting behavior and underlying feedback loops. The MSGCM is an efficient method to investigate feedback loops embedded in in vitro cultured neural networks. The identified feedback loop motifs are considered as an important design principle responsible for the synchronized bursting behavior in neural networks.

The equivalence of linear Gaussian connectivity techniques

The theoretical basis of linear Gaussian connectivity methods for the analysis of fMRI data is examined in this article, resulting in a clarification of methodological dependencies between techniques. In particular, Granger causality connectivity procedures, which describe instantaneous and directed influence between sets of voxel timeseries, are shown to be remappings of correlation-based metrics. Furthermore, the statistical inference tests applied to pairwise Granger causality measures are theoretically shown to be equivalent to inference tests applied to correlation-based metrics. These results are demonstrated empirically using receiver operating characteristic curves derived from vector autoregressive models of various lags, sample size, and noise covariance values. The equivalence of linear Granger causality and correlation-based methods, in both metric and test statistic, renders linear Granger causality a restatement of traditional data-driven methodologies in the context of brain connectivity studies. Furthermore, the equivalence highlights the centrality of partial correlation and partial variance in linear connectivity analyses and bridges the gap between functional and effective connectivity techniques. Consequently, rather than a distinction rooted in methodological difference, the dichotomy between functional and effective connectivity methods is ultimately a function of model configuration realized in choices such as the selection of nodes, the choice to model instantaneous and/or directed influence, and the choice to employ many bivariate models or a single multivariate model. While these theoretical results may be unsurprising to the reader with advanced statistical knowledge, they highlight the importance of a clear understanding of the theoretical basis of connectivity analysis methods for human brain mapping researchers.

Leadership in Orchestra Emerges from the Causal Relationships of Movement Kinematics

Non-verbal communication enables efficient transfer of information among people. In this context, classic orchestras are a remarkable instance of interaction and communication aimed at a common aesthetic goal: musicians train for years in order to acquire and share a non-linguistic framework for sensorimotor communication. To this end, we recorded violinists' and conductors' movement kinematics during execution of Mozart pieces, searching for causal relationships among musicians by using the Granger Causality method (GC). We show that the increase of conductor-to-musicians influence, together with the reduction of musician-to-musician coordination (an index of successful leadership) goes in parallel with quality of execution, as assessed by musical experts' judgments. Rigorous quantification of sensorimotor communication efficacy has always been complicated and affected by rather vague qualitative methodologies. Here we propose that the analysis of motor behavior provides a potentially interesting tool to approach the rather intangible concept of aesthetic quality of music and visual communication efficacy.

TRANSMISSION CHANNEL AND EFFECTIVENESS OF DUAL MONETARY POLICY IN INDONESIA

This paper investigates the transmission mechanism of dual monetary system from conventional and Islamic policy rates to inflation and output. We apply Granger Causality and VAR methods on monthly data of Indonesian banking, during the period of January 2003 to December 2009. The result shows that conventional policy rate is transmitted to output and inflation, while Islamic policy rate are not. In addition, the shock of conventional interest rate, credit and interbank rate give a negative and permanent impacts on inflation and output, except for SBI (Certificate of Bank Indonesia) with positive impact to inflation though negatively affect the output. On the other hand, the shock of PLS, financing and Islamic interbank PLS, as well as SBIS (Central Bank Shariah Certificate) give positive and permanent impacts on inflation and output. Keywords: Monetary transmission mechanism, Interest rate pass through, Conventional Banking, Islamic BankingJEL Classification: E43, E52, G21, G28

Gross ecosystem photosynthesis causes a diurnal pattern in methane emission from rice

Understanding the relative contribution of environmental and substrate controls on rice paddy methanogenesis is critical for developing mechanistic models of landscape‐scale methane (CH4) flux. A diurnal pattern in observed rice paddy CH4 flux has been attributed to fluctuations in soil temperature physically driving diffusive CH4transport from the soil to atmosphere. Here we make direct landscape‐scale measurements of carbon dioxide and CH4 fluxes and show that gross ecosystem photosynthesis (GEP) is the dominant cause of the diurnal pattern in CH4 flux, even after accounting for the effects of soil temperature. The time series of GEP and CH4 flux show strong spectral coherency throughout the rice growing season at the diurnal timescale, where the peak in GEP leads that of CH4 flux by 1.3 ± 0.08 hours. By applying the method of conditional Granger causality in the spectral domain, we demonstrated that the diurnal pattern in CH4 flux is primarily caused by GEP.

Interaction of catechol O-methyltransferase and serotonin transporter genes modulates effective connectivity in a facial emotion-processing circuitry

Imaging genetic studies showed exaggerated blood oxygenation level-dependent response in limbic structures in carriers of low activity alleles of serotonin transporter-linked promoter region (5-HTTLPR) as well as catechol O-methyltransferase (COMT) genes. This was suggested to underlie the vulnerability to mood disorders. To better understand the mechanisms of vulnerability, it is important to investigate the genetic modulation of frontal-limbic connectivity that underlies emotional regulation and control. In this study, we have examined the interaction of 5-HTTLPR and COMT genetic markers on effective connectivity within neural circuitry for emotional facial expressions. A total of 91 healthy Caucasian adults underwent functional magnetic resonance imaging experiments with a task presenting dynamic emotional facial expressions of fear, sadness, happiness and anger. The effective connectivity within the facial processing circuitry was assessed with Granger causality method. We have demonstrated that in fear processing condition, an interaction between 5-HTTLPR (S) and COMT (met) low activity alleles was associated with reduced reciprocal connectivity within the circuitry including bilateral fusiform/inferior occipital regions, right superior temporal gyrus/superior temporal sulcus, bilateral inferior/middle prefrontal cortex and right amygdala. We suggest that the epistatic effect of reduced effective connectivity may underlie an inefficient emotion regulation that places these individuals at greater risk for depressive disorders.

P-802 - The structure and connectivity of brain regions involved in emotion processing are modulated by 5HTTLPR x COMT epistasis

Imaging genetic studies provide for the possibility to uncover endophenotypes for neuropsychiatric disorders. To establish neuroimaging correlates of the joint effect of serotonergic (5-HTTLPR) and dopaminergic (COMT) genes. To examine an interaction of 5-HTTLPR and COMT markers on effective connectivity and regional brain volume in healthy individuals. Ninety one healthy Caucasian adults underwent functional magnetic resonance imaging (fMRI) and structural MRI. In fMRI study the participants were presented with videoclips of dynamic emotional facial expressions of fear, sadness, happiness and anger. The effective connectivity within the emotion processing circuitry was assessed with Granger causality method. In the structural neuroimaging part of the study we applied diffeomorphic anatomic registration through exponentiated Lie algebra (DARTEL) whole-brain voxel-based morphometry (VBM). In fear processing condition, an interaction between 5-HTTLPR ( S) and COMT (met) low activity alleles was associated with reduced effective connectivity within the facial emotion processing circuitry. The results of the structural data analysis showed an interaction of COMT and 5-HTTLPR genotypes with regional grey matter volume in bilateral parahippocampal gyrus, amygdala, hippocampus, cerebellum and right putamen. In particular, the gray matter volume in these regions was smaller in individuals who were both COMT- met and 5-HTTLPR- S carriers, as compared to those carrying either 5-HTTLPR- L/L, or COMT- val/val . The epistatic effect of COMT- met and 5-HTTLPR- S markers impacts on both the brain function and structure and may underlie an inefficient emotion regulation.

Quantification of Effective Connectivity in the Brain Using a Measure of Directed Information

Effective connectivity refers to the influence one neural system exerts on another and corresponds to the parameter of a model that tries to explain the observed dependencies. In this sense, effective connectivity corresponds to the intuitive notion of coupling or directed causal influence. Traditional measures to quantify the effective connectivity include model-based methods, such as dynamic causal modeling (DCM), Granger causality (GC), and information-theoretic methods. Directed information (DI) has been a recently proposed information-theoretic measure that captures the causality between two time series. Compared to traditional causality detection methods based on linear models, directed information is a model-free measure and can detect both linear and nonlinear causality relationships. However, the effectiveness of using DI for capturing the causality in different models and neurophysiological data has not been thoroughly illustrated to date. In addition, the advantage of DI compared to model-based measures, especially those used to implement Granger causality, has not been fully investigated. In this paper, we address these issues by evaluating the performance of directed information on both simulated data sets and electroencephalogram (EEG) data to illustrate its effectiveness for quantifying the effective connectivity in the brain.

Oil price, agricultural commodity prices, and the dollar: A panel cointegration and causality analysis

This study examines the dynamic relationship between world oil prices and twenty four world agricultural commodity prices accounting for changes in the relative strength of US dollar in a panel setting. We employ panel cointegration and Granger causality methods for a panel of twenty four agricultural products based on monthly prices ranging from January 1980 to February 2010. The empirical results provide strong evidence on the impact of world oil price changes on agricultural commodity prices. Contrary to the findings of many studies in the literature that report neutrality of agricultural prices to oil price changes, we find strong support for the role of world oil prices on prices of several agricultural commodities. The positive impact of a weak dollar on agricultural prices is also confirmed.

Why do some emerging economies proactively accelerate the adoption of renewable energy?

This article analyses the determinants of renewable energy consumption in a panel of six major emerging economies, namely Brazil, China, India, Indonesia, Philippines and Turkey that are proactively accelerating the adoption of renewable energy. Using Fully modified ordinary least square (FMOLS), Dynamic ordinary least square (DOLS), and Granger causality methods this paper finds that in the long-run, renewable energy consumption is significantly determined by income and pollutant emission in Brazil, China, India and Indonesia while mainly by income in Philippines and Turkey. Causal link between renewable energy and income; and between renewable energy and pollutant emission are found to be bidirectional in the short-run. These results suggest that the appropriateness of the efforts undertaken by emerging countries to reduce the carbon intensity by increasing the energy efficiency and substantially increasing the share of renewable in the overall energy mix.

Analysis of Net Causal Flows in Circuit of Premotor Control during Left Hand's Movement Readiness State

the previous research revealed some functional coupling among nodes in model of motor control in human brain, which described nondirectional synchronous actions among these nodes during movement-readiness state. However, causal relationships among these nodes, which represent some directional interactions in movement- readiness state, are still lack. In the present study, we used functional magnetic resonance imaging (fMRI) and conditional Granger causality (CGC) method to investigate the interactions in model of motor control in left hand's movement readiness state. Our results showed that upper precuneus (UPCU) and cingulated motor area (CMA) revealed net causal influences with contra lateral supplementary motor areas and contra lateral caudate nucleus during the left hand's movement-readiness state. The net causal flows among these nodes can construct a closed circuit, which is similar as the circuit found in monkey's brain and in human's brain in right hand's movement readiness state. This confirmed that there was an intrinsic circuit for motor control in either right hand's or left hand's movement readiness. Moreover, the results of Out-In degrees indicated that bilateral primary sensorimotor areas revealed competitive relationship during left hand's movement-readiness.

Evidence For Non-Linear Causality Between Public Spending And Income In The European Union Countries

<p class="MsoSubtitle" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-family: Times New Roman;"><span style="color: black; font-size: 10pt; font-weight: normal; text-decoration: none; text-underline: none;">This paper deploys the non-linear Granger causality methods in order to determine the causal relationship between national income and government expenditure in the European Union countries over the post-war time period. For this purpose, six alternative functional forms of Wagner’s law have been adopted. The empirical results </span><span style="font-size: 10pt; font-weight: normal; text-decoration: none; text-underline: none;">indicate support for non-linear causality between income and government expenditure and they may prove useful theoretical and empirical research for the regulators and the policy makers. </span></span></p>

Evaluation of effective connectivity of motor areas during motor imagery and execution using conditional Granger causality

The effective connectivity networks among overlapped core regions recruited by motor execution (ME) and motor imagery (MI) were explored by means of conditional Granger causality and graph-theoretic method, based on functional magnetic resonance imaging (fMRI) data. Our results demonstrated more circuits of effective connectivity among the selected seed regions during right-hand performance than during left-hand performance, implying the influences of brain asymmetry of right-handedness on effective connectivity networks. The increased causal connections were found during ME than during MI, suggesting that the ME network may have some additional connections compared to MI networks to execute the overt physical movement. Furthermore, the In–Out degrees of information flow suggested left dorsal premotor cortex (PMd), inferior parietal lobule (IPL) and superior parietal lobule (SPL) as causal sources in ME/MI tasks, highlighting the dominant function of left PMd, IPL and SPL. These findings depicted the causal connectivity of motor related core regions in fronto-parietal circuit and might indicate the conversion of causal networks between ME and MI.

A new approach to discovering the causal relationship between meteorological patterns and PM10 exceedances

Air Pollution control is of major concern for the Greater Athens Area (GAA) of Greece. High concentrations of Particulate Matter with diameter less than 10μm (PM10) have been observed and often reported to exceed the currently EU legislated 24-hour limit of 50μg/m3. Efforts therefore have been placed on understanding the PM10 concentration pattern in the area so that mitigation measures can be taken accordingly. The present paper presents a statistical methodology to discover causal relationships between daily PM10 exceedances at a monitoring site, with PM10 concentrations from existing stations from the monitoring network and associated weather patterns. The proposed approach utilised a dimension reduction algorithm, Positive Matrix Factorisation (PMF) algorithm, coupled with the k-means clustering algorithm to identify distinct groups of data. Then for each resulted cluster, the Granger Causality method aided by the Pearson correlation is applied to establish the causal relationships between the meteorological patterns and the observed PM10 exceedances. The study was conducted using 6-years of daily PM10 concentration data from the monitoring network in the GAA, complemented with meteorological data available from the National Centres for Environmental Prediction (NCEP) Global Forecasting System (GFS). The analysis yielded that the PM10 exceedances in the Athens area can be classified into 6 distinct types identified with varying spatial distribution characteristics and air pollution contributors.

Foreign Direct Investment in the Agriculture Sector of South Africa: Do GDP and Exports Determine Locational Inflows?

This study investigates the causal link between agricultural foreign direct investment (FDI), agricultural exports, and agricultural gross domestic product (GDP) in South Africa for the period 1994 – 2006. The central goal of this paper is to answer the question of whether there exists any complementary relationships or not between the two sets of variables. The paper utilizes the Granger causality method and the error correction method (ECM), in a bivariate setting. The results show that while there is a bi-directional causality from FDI to exports, there is only one-way causality from GDP to FDI. Rather than FDI stimulating agricultural productivity, agricultural productivity stimulates FDI. Thus, an increase in agricultural productivity is envisaged to yield increased FDI in the agricultural sector of South Africa.