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Journal articles on the topic 'Conditional Granger causality (CGC)'

Author: Grafiati

Published: 6 September 2023

Last updated: 7 September 2023

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1

Vidhusha S and Kavitha Anandan. "Inter-hemispherical Investigations on the Functional Connectivity of Autistic Resting State fMRI." International Journal of Cognitive Informatics and Natural Intelligence 10, no. 2 (2016): 95–108. http://dx.doi.org/10.4018/ijcini.2016040105.

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Autism spectrum disorders are connected with disturbances of neural connectivity. Functional connectivity is typically examined during a cognitive task, but also exists in the absence of a task i.e., “rest.” Adults with ASD have been found to show weaker connectivity relative to controls. This work focuses on analyzing the brain activation for autistic subjects, measured by fMRI during rest, relative to the control group using interhemispherical analysis. Though both groups activated similarly in cortical areas, indications of under connectivity were exhibited by the autistic group measured by

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Wang, Yu Qing, Hua Fu Chen, and Ling Zeng. "Evaluation of Causal Influences in Model of Motor Control in Left Hands Movement-Readiness State." Applied Mechanics and Materials 195-196 (August 2012): 418–23. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.418.

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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 t

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WONG, HOCK TSEN. "REAL EXCHANGE RATE RETURNS AND REAL STOCK PRICE RETURNS IN THE STOCK MARKET OF MALAYSIA." Singapore Economic Review 64, no. 05 (2016): 1319–49. http://dx.doi.org/10.1142/s0217590816500387.

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This study examines the relationships between real exchange rate returns and real stock price returns in the stock market of Malaysia. The Kwiatkowski, Phillips, Schmidt and Shin (KPSS) and Dickey and Fuller (DF) unit root test statistics show that all the variables examined are found to be stationary in the first differences. The constant conditional correlation (CCC)-multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) model shows that real exchange rate return of Malaysian ringgit against the United States dollar (RM/USD) and real stock price return of Kuala Lumpu

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Wang, Li, Jingna Zhang, Ye Zhang, Rubing Yan, Hongliang Liu, and Mingguo Qiu. "Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients." BioMed Research International 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/3870863.

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Aims.Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effective connectivity in stroke patients.Methods.Ten stroke patients with right hand hemiplegia and ten normal control subjects were recruited. We applied conditional Granger causality analysis (CGCA) to explore and compare the functional connectivity between motor execution and motor imagery.Results.Compa

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Ferro, Demetrio, Jochem van Kempen, Michael Boyd, Stefano Panzeri, and Alexander Thiele. "Directed information exchange between cortical layers in macaque V1 and V4 and its modulation by selective attention." Proceedings of the National Academy of Sciences 118, no. 12 (2021): e2022097118. http://dx.doi.org/10.1073/pnas.2022097118.

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Achieving behavioral goals requires integration of sensory and cognitive information across cortical laminae and cortical regions. How this computation is performed remains unknown. Using local field potential recordings and spectrally resolved conditional Granger causality (cGC) analysis, we mapped visual information flow, and its attentional modulation, between cortical layers within and between macaque brain areas V1 and V4. Stimulus-induced interlaminar information flow within V1 dominated upwardly, channeling information toward supragranular corticocortical output layers. Within V4, infor

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Zhu, Hongmin. "Real-Time Prognostics of Engineered Systems under Time Varying External Conditions Based on the COX PHM and VARX Hybrid Approach." Sensors 21, no. 5 (2021): 1712. http://dx.doi.org/10.3390/s21051712.

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In spite of the development of the Prognostics and Health Management (PHM) during past decades, the reliability prognostics of engineered systems under time-varying external conditions still remains a challenge in such a field. When considering the challenge mentioned above, a hybrid method for predicting the reliability index and the Remaining Useful Life (RUL) of engineered systems under time-varying external conditions is proposed in this paper. The proposed method is competent in reflecting the influence of time-varying external conditions on the degradation behaviour of engineered systems

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Singh, Amanjot, and Manjit Singh. "How linkages fuel dependent economic policy initiatives." International Journal of Law and Management 59, no. 2 (2017): 303–18. http://dx.doi.org/10.1108/ijlma-01-2016-0007.

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Purpose With the globalization and liberalization in terms of increasing financial flows across the countries, the policy makers around the world are not independent in the context of monetary and fiscal policy initiatives. In this regard, this paper aims to attempt to quantify and capture long run, short run as well as time-varying linkages among the two financial stress indices, namely, Kansas City Financial Stress Index (KCFSI) and Indian Financial Stress Index (IFSI) across the monthly period (2004 to 2014). Design/methodology/approach Owing to the non-existence of a standardized financial

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8

Malekpour, Sheida, and William A. Sethares. "Conditional Granger causality and partitioned Granger causality: differences and similarities." Biological Cybernetics 109, no. 6 (2015): 627–37. http://dx.doi.org/10.1007/s00422-015-0665-3.

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Lu, Xun, Liangjun Su, and Halbert White. "GRANGER CAUSALITY AND STRUCTURAL CAUSALITY IN CROSS-SECTION AND PANEL DATA." Econometric Theory 33, no. 2 (2016): 263–91. http://dx.doi.org/10.1017/s0266466616000086.

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Granger noncausality in distribution is fundamentally a probabilistic conditional independence notion that can be applied not only to time series data but also to cross-section and panel data. In this paper, we provide a natural definition of structural causality in cross-section and panel data and forge a direct link between Granger (G–) causality and structural causality under a key conditional exogeneity assumption. To put it simply, when structural effects are well defined and identifiable,G–non-causality follows from structural noncausality, and with suitable conditions (e.g., separabilit

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Wang, Xia, and Yongmiao Hong. "CHARACTERISTIC FUNCTION BASED TESTING FOR CONDITIONAL INDEPENDENCE: A NONPARAMETRIC REGRESSION APPROACH." Econometric Theory 34, no. 4 (2017): 815–49. http://dx.doi.org/10.1017/s026646661700010x.

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We propose a characteristic function based test for conditional independence, applicable to both cross-sectional and time series data. We also derive a class of derivative tests, which deliver model-free tests for such important hypotheses as omitted variables, Granger causality in various moments and conditional uncorrelatedness. The proposed tests have a convenient asymptotic null N (0, 1) distribution, and are asymptotically locally more powerful than a variety of related smoothed nonparametric tests in the literature. Unlike other smoothed nonparametric tests for conditional independence,

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Stokes, P. A., M. Vangel, F. H. Lin, et al. "Dynamic Frequency-Domain Conditional Granger Causality Applied to Magnetoencephalography." NeuroImage 47 (July 2009): S148. http://dx.doi.org/10.1016/s1053-8119(09)71509-5.

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Xiao, Yanyang, Songting Li, and Douglas Zhou. "Representing conditional Granger causality by vector auto-regressive parameters." Communications in Mathematical Sciences 17, no. 5 (2019): 1353–86. http://dx.doi.org/10.4310/cms.2019.v17.n5.a9.

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Zhou, Zhenyu, Yonghong Chen, Mingzhou Ding, Paul Wright, Zuhong Lu, and Yijun Liu. "Analyzing brain networks with PCA and conditional Granger causality." Human Brain Mapping 30, no. 7 (2009): 2197–206. http://dx.doi.org/10.1002/hbm.20661.

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Marica, Vasile George, and Alexandra Horobet. "Conditional Granger Causality and Genetic Algorithms in VAR Model Selection." Symmetry 11, no. 8 (2019): 1004. http://dx.doi.org/10.3390/sym11081004.

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Overcoming symmetry in combinatorial evolutionary algorithms is a challenge for existing niching methods. This research presents a genetic algorithm designed for the shrinkage of the coefficient matrix in vector autoregression (VAR) models, constructed on two pillars: conditional Granger causality and Lasso regression. Departing from a recent information theory proof that Granger causality and transfer entropy are equivalent, we propose a heuristic method for the identification of true structural dependencies in multivariate economic time series. Through rigorous testing, both empirically and

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Brovelli, Andrea. "Statistical Analysis of Single-Trial Granger Causality Spectra." Computational and Mathematical Methods in Medicine 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/697610.

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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 general linear models. The approach was assessed on synthetic and neurophysiological data. Synthetic bivariate data was generated using two autoregressive processes with unidirectional coupling. We simulated

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Seth, S., and J. C. Principe. "Assessing Granger Non-Causality Using Nonparametric Measure of Conditional Independence." IEEE Transactions on Neural Networks and Learning Systems 23, no. 1 (2012): 47–59. http://dx.doi.org/10.1109/tnnls.2011.2178327.

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KATIRCIOǦLU, SALIH TURAN. "TOURISM AND GROWTH IN SINGAPORE: NEW EXTENSION FROM BOUNDS TEST TO LEVEL RELATIONSHIPS AND CONDITIONAL GRANGER CAUSALITY TESTS." Singapore Economic Review 56, no. 03 (2011): 441–53. http://dx.doi.org/10.1142/s0217590811004365.

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This paper empirically investigates the tourism-led growth (TLG) hypothesis in the case of Singapore by employing the bounds test to cointegration, error correction models and Granger causality tests using annual data from 1960 to 2007. Results confirm the existence of long-term equilibrium relationship between international tourism and economic growth in the case of Singapore; real income growth converges to its long-term equilibrium level significantly by 51.4% in the TLG model. The major finding of this study is that the TLG hypothesis is confirmed for the Singaporean economy in the long-te

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Ai, Dongmei, Xiaoxin Li, Gang Liu, Xiaoyi Liang, and Li Xia. "Constructing the Microbial Association Network from Large-Scale Time Series Data Using Granger Causality." Genes 10, no. 3 (2019): 216. http://dx.doi.org/10.3390/genes10030216.

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The increasing availability of large-scale time series data allows the inference of microbial community dynamics by association network analysis. However, correlation-based association network analyses are noninformative of causal, mediating and time-dependent relationships between microbial community functional factors. To address this insufficiency, we introduced the Granger causality model to the analysis of a recent marine microbial time series dataset. We systematically constructed a directed acyclic network, representing both internal and external causal relationships among the microbial

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Nakajima, Tadahiro. "Test for volatility spillover effects in Japan’s oil futures markets by a realized variance approach." Studies in Economics and Finance 36, no. 2 (2019): 224–39. http://dx.doi.org/10.1108/sef-01-2017-0011.

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Purpose The purpose of this paper is twofold. First, the paper examines the risk transmission between crude oil and petroleum product prices of Japan’s oil futures market. Second, it compares the performance of two tests for Granger causality using realized variance (RV) and the exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model. Design/methodology/approach The author measures the daily RV of crude oil, kerosene and gasoline futures listed on the Tokyo Commodity Exchange using high-frequency data, and he examines the Granger causality in variance between these

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Mainali, Kumar, Sharon Bewick, Briana Vecchio-Pagan, David Karig, and William F. Fagan. "Detecting interaction networks in the human microbiome with conditional Granger causality." PLOS Computational Biology 15, no. 5 (2019): e1007037. http://dx.doi.org/10.1371/journal.pcbi.1007037.

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Taamouti, Abderrahim, Taoufik Bouezmarni, and Anouar El Ghouch. "Nonparametric estimation and inference for conditional density based Granger causality measures." Journal of Econometrics 180, no. 2 (2014): 251–64. http://dx.doi.org/10.1016/j.jeconom.2014.03.001.

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Dhifaoui, Zouhaier, and Faicel Gasmi. "Linear and nonlinear linkage of conditional stochastic volatility of interbank interest rates: Empirical evidence of the BRICS countries." BRICS Journal of Economics 2, no. 2 (2021): 4–16. http://dx.doi.org/10.38050/2712-7508-2021-2-1.

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The purpose of this article is to detect a possible linear and nonlinear causal relationship between the conditional stochastic volatility of log return of interbank interest rates for the BRICS countries in the period from January 2015 to October 2018. To extract the volatility of the analyzed time series, we use a stochastic volatility model with moving average innovations. To test a causal relationship between the estimated stochastic volatilities, two steps are applied. First, we used the Granger causality test and a vector autoregressive model (VAR). Secondly, we applied the nonlinear Gra

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Ballester, Laura, Ana Mónica Escrivá, and Ana González-Urteaga. "The Nexus between Sovereign CDS and Stock Market Volatility: New Evidence." Mathematics 9, no. 11 (2021): 1201. http://dx.doi.org/10.3390/math9111201.

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This paper extends the studies published to date by performing an analysis of the causal relationships between sovereign CDS spreads and the estimated conditional volatility of stock indices. This estimation is performed using a vector autoregressive model (VAR) and dynamically applying the Granger causality test. The conditional volatility of the stock market has been obtained through various univariate GARCH models. This methodology allows us to study the information transmissions, both unidirectional and bidirectional, that occur between CDS spreads and stock volatility between 2004 and 202

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Xiaoguang Liu, Xiaoguang Liu, Renping Song Xiaoguang Liu, Guoliang Ding Renping Song, Mingxia Zu Guoliang Ding, Xiaomei Wang Mingxia Zu, and Yuan Wang Xiaomei Wang. "A Prediction Model for Substation Investment Benefit Based on Granger Causality." 電腦學刊 33, no. 6 (2022): 107–17. http://dx.doi.org/10.53106/199115992022123306009.

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<p>The construction of a lean operation and inspection integrated management system for substations is an important part of the development and maintenance of the power system. Forecasting the investment benefits of substation project development is an important issue in feasibility analysis. Therefore, we need to use a highly accurate method to make a prediction of the investment benefit of this project. Granger causation is a causal relationship based on &quot;prediction&quot;, and inferring about its causality is a key task in time series analysis. In this paper, we propose a

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Falasca, N. W., and R. Franciotti. "Ability of Granger Causality Analysis to Detect Indirect Links: A Simulation Study." Nonlinear Phenomena in Complex Systems 23, no. 2 (2020): 121–24. http://dx.doi.org/10.33581/1561-4085-2020-23-2-121-124.

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Granger causality (G-causality) has emerged as a useful tool to investigate the influence that one system can exert over another system, but challenges remain when applying it to biological data. Specifically, it is not clear if G-causality can distinguish between direct and indirect influences. In this study time domain G-causality connectivity analysis was performed on simulated electroencephalographic cerebral signals. Conditional multivariate autoregressive model was applied to 19 virtual time series (nodes) to identify the effects of direct and indirect links while varying one of the foll

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Xi, Zhuo. "The Asymmetric Volatility Spillover and Dynamic Correlation Across Equity Markets in China and The United States." International Journal of Business & Management Studies 04, no. 06 (2023): 31–43. http://dx.doi.org/10.56734/ijbms.v4n6a5.

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This paper aims to study the volatility spillover effects as well as the dynamic conditional correlation between stock market returns in China and the U.S. Firstly, the analysis uses a vector autoregression with a bivariate BEKK-GARCH model to capture the asymmetric volatility transmissions between the two markets during the sample of 1996-2019. Then a VAR-DCC-GARCH model is employed to estimate the dynamic conditional correlation between these two market returns. Finally, linear regression and Granger Causality test are conducted to further explore the effect of the U.S policy rates on such c

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Maneejuk, Paravee, and Woraphon Yamaka. "The Role of Economic Contagion in the Inward Investment of Emerging Economies: The Dynamic Conditional Copula Approach." Mathematics 9, no. 20 (2021): 2540. http://dx.doi.org/10.3390/math9202540.

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Contagion has been one of the most widely studied and challenging problems in recent economic research. This paper aims at capturing the main impact of contagion risk of the U.S. on foreign direct investment inflows in 18 emerging countries. To quantify the degree of contagion, the time-varying tail dependence copula is employed. Then, the Granger causality test and time series regression analysis are used to investigate the temporal and contemporaneous effects of contagion risk on investment inflows, respectively. Overall, the results confirm the time-varying contagion effects of the U.S. eco

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Bouezmarni, Taoufik, Jeroen V. K. Rombouts, and Abderrahim Taamouti. "Nonparametric Copula-Based Test for Conditional Independence with Applications to Granger Causality." Journal of Business & Economic Statistics 30, no. 2 (2012): 275–87. http://dx.doi.org/10.1080/07350015.2011.638831.

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Liao, Wei, Dante Mantini, Zhiqiang Zhang, et al. "Evaluating the effective connectivity of resting state networks using conditional Granger causality." Biological Cybernetics 102, no. 1 (2009): 57–69. http://dx.doi.org/10.1007/s00422-009-0350-5.

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Lawal, Gold Olamide, Bisola Aladenika, Seyi Saint Akadiri, Ayodeji Samson Fatigun, and Victoria Olushola Olanrewaju. "Geopolitical Risk, Globalization and Environmental Degradation in South Africa: Evidence from Advanced Quantiles Approach." Problemy Ekorozwoju 18, no. 1 (2023): 207–15. http://dx.doi.org/10.35784/pe.2023.1.22.

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Sustainable development involves the incorporation of socio-economic concerns and environmental protection into the economic decision-making process, in such a way that, any developmental effort would eventually be favorable to immediate and future generations. It is against this backdrop this study investigates the effects of geopolitical risk and globalization on environmental degradation in South Africa over the period 1985Q1-2018Q4. This study improves on existing studies and raises concerns on the potential twin-effect of geopolitical risk and globalization on the environment. We deviate

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Корнилов, М. В., та И. В. Сысоев. "Реконструкция архитектуры связей в цепочке из трех однонаправленно связанных систем методом причинности по Грейнджеру". Письма в журнал технической физики 44, № 10 (2018): 86. http://dx.doi.org/10.21883/pjtf.2018.10.46103.17201.

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AbstractWe propose a method for reconstructing links in a chain of unidirectionally coupled systems by means of three tests for estimating direct and mediated coupling with the aid of Granger conditional causality in terms of prognostic models with polynomial nonlinearity. It is shown that this approach allows the architecture of links in these systems to be correctly identified in more than 80% of cases.

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Seghouane, Abd-Krim, and Shun-ichi Amari. "Identification of Directed Influence: Granger Causality, Kullback-Leibler Divergence, and Complexity." Neural Computation 24, no. 7 (2012): 1722–39. http://dx.doi.org/10.1162/neco_a_00291.

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Detecting and characterizing causal interdependencies and couplings between different activated brain areas from functional neuroimage time series measurements of their activity constitutes a significant step toward understanding the process of brain functions. In this letter, we make the simple point that all current statistics used to make inferences about directed influences in functional neuroimage time series are variants of the same underlying quantity. This includes directed transfer entropy, transinformation, Kullback-Leibler formulations, conditional mutual information, and Granger ca

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Chowdhury, Abdur. "Inflation and inflation-uncertainty in India: the policy implications of the relationship." Journal of Economic Studies 41, no. 1 (2014): 71–86. http://dx.doi.org/10.1108/jes-04-2012-0046.

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Purpose – Inflation and its related uncertainty can impose costs on real economic output in any economy. This paper aims to analyze the relationship between inflation and inflation uncertainty in India. Design/methodology/approach – The methodology uses a generalized autoregressive conditional heteroscedasticity (GARCH) model and Granger Causality test. Findings – Initial estimates show the inflation rate to be a stationary process. The maximum likelihood estimates from the GARCH model reveal strong support for the presence of a positive relationship between the level of inflation and its unce

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Hasbullah, Endang Soeryana, Endang Rusyaman, and Alit Kartiwa. "THE GARCH MODEL VOLATILITY OF SHARIA STOCKS ASSOCIATED CAUSALITY WITH MARKET INDEX." International Journal of Quantitative Research and Modeling 1, no. 1 (2020): 18–28. http://dx.doi.org/10.46336/ijqrm.v1i1.3.

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The purpose of this paper is to examine the volatility of Islamic stocks related to the causality of the composite stock price index (CSPI). The aim is to investigate the causality of several levels of stock returns with the movement of the CSPI, and determine its volatility as a measure of risk. To determine the causality relationship is done by using the granger causality test method, with Vector Autoregressive (VAR) modeling. Whereas to determine the volatility is done using the Generalized Autoregressive Conditional Heteroscedastisiy (GARCH) model approach. The results of the causality tes

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Nath Sahu, Tarak, Kalpataru Bandopadhyay, and Debasish Mondal. "An empirical study on the dynamic relationship between oil prices and Indian stock market." Managerial Finance 40, no. 2 (2014): 200–215. http://dx.doi.org/10.1108/mf-06-2013-0131.

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Purpose – This study aims to investigate the dynamic relationships between oil price shocks and Indian stock market. Design/methodology/approach – The study used daily data for the period starting from January 2001 to March 2013. In this study, Johansen's cointegration test, vector error correction model (VECM), Granger causality test, impulse response functions (IRFs) and variance decompositions (VDCs) test have been applied to exhibit the long-run and short-run relationship between them. Findings – The cointegration result indicates the existence of long-term relationship. Further, the error

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Yurdakul, Funda, and Erdogan Cevher. "Determinants of Current Account Deficit in Turkey: The Conditional and Partial Granger Causality Approach." Procedia Economics and Finance 26 (2015): 92–100. http://dx.doi.org/10.1016/s2212-5671(15)00884-9.

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Chen, Yonghong, Steven L. Bressler, and Mingzhou Ding. "Frequency decomposition of conditional Granger causality and application to multivariate neural field potential data." Journal of Neuroscience Methods 150, no. 2 (2006): 228–37. http://dx.doi.org/10.1016/j.jneumeth.2005.06.011.

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Zhou, Zhenyu, Xunheng Wang, Nelson J. Klahr, et al. "A conditional Granger causality model approach for group analysis in functional magnetic resonance imaging." Magnetic Resonance Imaging 29, no. 3 (2011): 418–33. http://dx.doi.org/10.1016/j.mri.2010.10.008.

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Yamaka, Woraphon, Jianxu Liu, Mingyang Li, Paravee Maneejuk, and Hai Q. Dinh. "Analyzing the Causality and Dependence between Exchange Rate and Real Estate Prices in Boom-and-Bust Markets: Quantile Causality and DCC Copula GARCH Approaches." Axioms 11, no. 3 (2022): 113. http://dx.doi.org/10.3390/axioms11030113.

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Unlike most previous studies examining the causal relationship and dependence between exchange rates and real estate prices, this study aims to investigate the causal relationship and dependence between these two variables in a boom-and-bust market setting using the panel quantile Granger causality and dynamic conditional correlation (DCC) copula GARCH approaches, respectively. In the panel quantile Granger causality test, quantiles 0.1 and 0.9 are considered to represent extreme markets (bust and boom, respectively). Our first results showed the causal effects at extreme quantiles to be very

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Oliveira, Wendy Sidon Meira de, and André Nunes Maranhão. "Spillovers de Volatilidades Cambiais e de Mercados Financeiros Internacionais no Mercado Acionário Brasileiro." Brazilian Review of Finance 15, no. 4 (2018): 569. http://dx.doi.org/10.12660/rbfin.v15n4.2017.63341.

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We present in this study the results of volatility spillover in the Brazilian stock market, measured by conditional correlations. Using GARCH multivariate conditional correlations were estimated at 3 different models combining the Ibovespa index of the three types of exchange rate shocks and a shock of international financial markets. The existence and direction of spillovers of volatility of forward exchange shocks, international financial market shocks and the Ibovespa were tested by Granger causality test of second order. The results show the existence of spillovers from exchange rate shock

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Detto, Matteo, Gil Bohrer, Jennifer Nietz, et al. "Multivariate Conditional Granger Causality Analysis for Lagged Response of Soil Respiration in a Temperate Forest." Entropy 15, no. 12 (2013): 4266–84. http://dx.doi.org/10.3390/e15104266.

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Chen, Han-Sheng, Zhengbing Yan, Xuelei Zhang, Yi Liu, and Yuan Yao. "Root Cause Diagnosis of Process Faults Using Conditional Granger Causality Analysis and Maximum Spanning Tree." IFAC-PapersOnLine 51, no. 18 (2018): 381–86. http://dx.doi.org/10.1016/j.ifacol.2018.09.330.

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Ogede, Jimoh, Musa Oduola, Olumuyiwa Yinusa, and Lukman Raimi. "Modelling the influence of financial inclusion on the remittance growth nexus in Nigeria." Ekonomski anali 68, no. 237 (2023): 137–63. http://dx.doi.org/10.2298/eka2337137s.

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In this paper, we explore the nexus between remittances and Nigeria?s economic growth over the period 1996 to 2020 from the perspective of financial inclusion (FI). The fully modified ordinary least square (FMOLS) and Granger (1969) causality methodologies were employed. The findings of the FMOLS show that the increasing flow of remittances can significantly contribute to the growth of the Nigerian economy. Also, the interaction of financial inclusion and remittances has a significant impact on the country?s development. The study concludes that the interaction of remittances with the measures

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Tiwari, Aviral Kumar, and Phouphet Kyophilavong. "Exchange Rates and International Reserves in India." South Asia Economic Journal 18, no. 1 (2017): 76–93. http://dx.doi.org/10.1177/1391561416684237.

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This article aims to study the relationship between real effective exchange rate (REER) and international reserve in India by applying the bivariate and conditional bivariate Granger causality test in frequency domain framework proposed by Breitung and Candelon (2006). The variables that are included to condition the frequency domain are the industrial production index, stock prices and wholesale producer index. Results found the evidence of business cyclical causality running from international reserve to REER for frequencies between 0.01 and 1.63 that corresponds to the 4 months and higher m

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Yadav, Miklesh Prasad, and Asheesh Pandey. "Volatility Spillover Between Indian and MINT Stock Exchanges: Portfolio Diversification Implication." Indian Economic Journal 67, no. 3-4 (2019): 299–311. http://dx.doi.org/10.1177/0019466220947501.

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We examine the spillover effect from the Indian stock market to Mexico, Indonesia, Nigeria and Turkey (MINT) stock markets in order to check if suitable diversification opportunities are available to global portfolio managers investing in India. We apply Granger causality test, vector auto-regression (VAR) and dynamic conditional correlation (DCC)–MGARCH to investigate the level of integration between India and MINT economies. We observe bidirectional causality between India and Nigeria, unidirectional causality in Mexico and Indonesia, while no causality is found between India and Turkey. Our

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Singh, Amanjot, and Manjit Singh. "Conditional co-movement and dynamic interactions: US and BRIC equity markets." Ekonomski anali 62, no. 212 (2017): 85–111. http://dx.doi.org/10.2298/eka1712085s.

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The present study attempts to capture conditional or time-varying co-movement and dynamic interactions between the US and BRIC (Brazil, Russia, India, and China) equity markets across the sample period 2004 to 2014 by employing diverse econometric models. The sample period is further divided into three different sub-periods concerning the US financial crisis period, viz. pre-crisis, crisis, and post-crisis periods. The vector autoregression- dynamic conditional correlation-multivariate asymmetric generalized autoregressive conditional heteroskedastic [VAR-DCC-MVAGARCH (1.1)] model and Toda-Yam

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Gao, Qing, Xujun Duan, and Huafu Chen. "Evaluation of effective connectivity of motor areas during motor imagery and execution using conditional Granger causality." NeuroImage 54, no. 2 (2011): 1280–88. http://dx.doi.org/10.1016/j.neuroimage.2010.08.071.

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Casile, Antonino, Rose T. Faghih, and Emery N. Brown. "Robust point-process Granger causality analysis in presence of exogenous temporal modulations and trial-by-trial variability in spike trains." PLOS Computational Biology 17, no. 1 (2021): e1007675. http://dx.doi.org/10.1371/journal.pcbi.1007675.

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Assessing directional influences between neurons is instrumental to understand how brain circuits process information. To this end, Granger causality, a technique originally developed for time-continuous signals, has been extended to discrete spike trains. A fundamental assumption of this technique is that the temporal evolution of neuronal responses must be due only to endogenous interactions between recorded units, including self-interactions. This assumption is however rarely met in neurophysiological studies, where the response of each neuron is modulated by other exogenous causes such as,

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Karagianni, Stella, Maria Pempetzoglou, and Anastasios Saraidaris. "Government Expenditures and Economic Growth: a Nonlinear Causality Investigation for the UK." European Journal of Marketing and Economics 2, no. 2 (2019): 52. http://dx.doi.org/10.26417/ejme-2019.v2i2-70.

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This study aims to explore the causal relationship between government expenditures and economic growth in the UK. The analysis emphasizes on the nonlinearity facet of the explored causality. In this aspect, existing conditional heteroscedasticity as a potential source of bias, is filtered out with the use of the nonparametric Diks and Panchenko causality test. The UK government expenditures are disaggregated into total managed expenditure (TGE), current expenditure (CGE) and net investment (IGE), in order to account for a possible heterogeneity in a causality disclosure linked to the nature of

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Singh, Amanjot, and Manjit Singh. "A revisit to how linkages fuel dependent economic policy initiatives." International Journal of Law and Management 59, no. 6 (2017): 1068–108. http://dx.doi.org/10.1108/ijlma-08-2016-0074.

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Purpose The authors aim to report empirical linkages between the US and Brazil, Russia, India and China (BRIC) financial stress indices catalyzing catalyzing dependent economic policy initiatives (an extended version of Singh and Singh, 2017a). Design/methodology/approach Initially, the study develops financial stress indices for the respective BRIC financial markets. Later, it captures linkages among the said US-BRIC indices by using Johansen cointegration, vector autoregression/vector error correction models (VECM), generalized impulse response functions, Toda–Yamamoto Granger causality, var

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