Investigating causal relations by econometric models and cross-spectral methods

By Clive W. J. Granger. 1969

Subfields: Causal Inference & Discovery, Signal Processing

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Citations in the corpus

Invariant Causal Prediction for Sequential Data (2017, background): “The problem of identifying causal directions is greatly reduced in the time series setting, where the concept of Granger causality (Granger 1969) plays a prominent role; see also structural vector auto-regressive models (SVAR) that are popular in econometrics (e.g., Lütkepohl 2005).”
From Deterministic ODEs to Dynamic Structural Causal Models (2016, methodology): “In this sense, we view our main re- sults as ‘orthogonal’ to methods such as Granger causality (Granger, 1969) and difference-in-differences (Card and Krueger, 1993) which aim to infer causal effects given time-series observations of a system.”
Telling cause from effect in deterministic linear dynamical systems (2015, methodology): “additive noise term, the “innovation of the process” (Granger, 1969; Peters et al., 2013).”
How to learn about teaching: An evolutionary framework for the study of teaching behavior in humans and other animals. (2014, background): “Granger-causality (Granger 1969; Seth 2010) enables investigation of directionality of information transmission in the teaching process; a teacher’s time series causes a pupil’s time series (sensu Granger-causality) if past teacher’s data significantly improve the prediction of future pupil’s data (”
Tools of the trade: psychophysiological interactions and functional connectivity. (2012, methodology): “…regions in any context, including when the brain is at rest (Biswal et al., 1995); other techniques for functional connectivity analysis include Dynamic Causal Modelling [DCM (Friston et al., 2003)], independent components analysis [ICA (Hyvarinen, 1999)] and Granger causality (Granger, 1969).”
Fire‐Sale Spillovers and Systemic Risk (2015, unknown): “The second and third columns show the p-values of Granger (1969) causality tests.”
Counting Chickens when they Hatch: Timing and the Effects of Aid on Growth* (2012, unknown): “That is, does aid exhibit Granger (1969) causation of growth?”
Testing for Granger Non-causality in Heterogeneous Panels (2012, methodology): “with i = (1) i ; :::; (K) i 0 : Under the alternative, we allow for i to di¤er across groups.”
Testing nonparametric and semiparametric hypotheses in vector stationary processes (2008, background): “For instance, one might be interested in whether the process {XA(t)} is white noise or whether one component of {XA(t)} Granger-causes another component after removal of the linear effects of {XB(t)} (for the concept of Granger causality, see [32]).”
Does Improvement in Trade Openness Facilitate Renewable Energy Transition? Evidence from Selected South Asian Economies (2018, background): “When y and x are taken as the variables of interest, then the Granger causality test (Granger, 1969) determines whether past values of y add to the explanation of current values of x as provided by information in past values of x itself.”