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Measuring Granger Causality in Quantiles [PDF]
Journal of Business & Economic Statistics, 2020 We consider measures of Granger causality in quantiles, which detect and quantify both linear and nonlinear causal effects between random variables. The measures are based on nonparametric quantile regressions and defined as logarithmic functions of restricted and unrestricted expectations of quantile check loss functions.
Song, X., Taamouti, A.
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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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A homogeneous approach to testing for Granger non-causality in heterogeneous panels
Empirical Economics, 2020 This paper develops a new method for testing for Granger non-causality in panel data models with large cross-sectional (N) and time series (T) dimensions. The method is valid in models with homogeneous or heterogeneous coefficients.
Artūras Juodis +2 more
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From FDI to economic complexity: a panel Granger causality analysis
Structural Change and Economic Dynamics, 2020 In this paper, we assess whether attracting higher amounts of FDI induces a greater level of economic complexity in a country. Using a panel of 117 countries and 22 years, from 1995 to 2016, we test for the causal relationship between inward FDI and ...
R. Antonietti, C. Franco
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Analyzing Multiple Nonlinear Time Series with Extended Granger Causality [PDF]
, 2004 Identifying causal relations among simultaneously acquired signals is an important problem in multivariate time series analysis. For linear stochastic systems Granger proposed a simple procedure called the Granger causality to detect such relations.
Arnhold +28 more
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NeuroImage, 2014 This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality.
Friston, Karl J. +5 more
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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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Meta-Granger Causality Testing [PDF]
SSRN Electronic Journal, 2015 Understanding the (causal) mechanisms at work is important for formulating evidence-based policy. But evidence from observational studies is often inconclusive with many studies finding conflicting results. In small to moderately sized samples, the outcome of Granger causality testing heavily depends on the lag length chosen for the underlying vector ...
Stephan B. Bruns, David I. Stern
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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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