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Bibliometric Analysis of Granger Causality Studies [PDF]
Entropy, 2023 Granger causality provides a framework that uses predictability to identify causation between time series variables. This is important to policymakers for effective policy management and recommendations.
Weng Siew Lam +3 more
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Frontiers in Computational Neuroscience, 2021 In recent years, affective computing based on electroencephalogram (EEG) data has attracted increased attention. As a classic EEG feature extraction model, Granger causality analysis has been widely used in emotion classification models, which construct ...
Dongwei Chen +5 more
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Hubungan Antara Perkembangan Sektor Keuangan dengan Volatilitas Ekonomi di Indonesia
Economic Journal of Emerging Markets, 2009 The study is conducted to analyze the causal relationship between financial sector development and economic volatility in Indonesia during the period of 1983.2-2000.4. The study uses three kinds of variables as proxies to the financial sector development.
Romi Mulyadi H.
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PLoS ONE, 2023 The elderly population and economic growth have been a contentious topic among researchers. Regardless of the economic growth rate, the population and its growth have a stimulating influence on economic development.
Thaveesha Jayawardhana +5 more
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New considerations on the validity of the Wiener-Granger causality test
Heliyon, 2020 The Wiener-Granger causality test is used to predict future experimental results from past observations in a purely mathematical way. For instance, in many scientific papers this test has been used to study the causality relations in the case of neuronal
Greta Grassmann
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Heliyon, 2022 This study aims to investigate the co-movement and Granger causality between Bitcoin prices (BTC) and M2 (cash, demand, and time deposits), inflation, and economic policy uncertainty (EPU) in the U.K. and Japan.
Provash Kumer Sarker, Lei Wang
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DLI: A Deep Learning-Based Granger Causality Inference
Complexity, 2020 Integrating autoencoder (AE), long short-term memory (LSTM), and convolutional neural network (CNN), we propose an interpretable deep learning architecture for Granger causality inference, named deep learning-based Granger causality inference (DLI).
Wei Peng
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The relationships between ASEAN stock markets: A spectral Granger causality approach
Tạp chí Khoa học Đại học Mở Thành phố Hồ Chí Minh - Kinh tế và Quản trị kinh doanh, 2021 This article collects data of ASEAN6’s daily stock returns to investigate the relationships among them by traditional Granger causality test in combination with spectral Granger causality test.
Trần Thị Tuấn Anh
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The Relation between Granger Causality and Directed Information Theory: A Review
Entropy, 2012 This report reviews the conceptual and theoretical links between Granger causality and directed information theory. We begin with a short historical tour of Granger causality, concentrating on its closeness to information theory.
Pierre-Olivier Amblard +1 more
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Energies, 2019 This paper investigates the co-movement and asymmetric interactions between energy and grain prices, based on the evidence from the crude oil and corn markets, the most important energy and grain markets, respectively. Time series analysis indicates that
Zhan-Ming Chen +3 more
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