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Testing for Granger Causality in Heterogeneous Mixed Panels

, 2020
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Testing for time-varying Granger causality

The Stata Journal: Promoting communications on statistics and Stata, 2022
The concept of Granger causality is an important tool in applied macroeconomics. Recently, recursive econometric methods have been developed to analyze the temporal stability of Granger-causal relationships. This article offers an implementation of these recursive procedures in Stata.
Christopher F. Baum, Stan Hurn, Jesús Otero   +2 more
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Testing for Granger's Full Causality

The Review of Economics and Statistics, 1992
A procedure is proposed to test for the existence of a fully causal relationship between two variables. The method involves contrasting the probabilistic forecasting performance of a univariate and bivariate specification for the same variable Y. If there exists some theory or belief that X causes Y, and the addition of a variable X to the information ...
Covey, Ted, Bessler, David A
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OUT-OF-SAMPLE TESTS FOR GRANGER CAUSALITY

Macroeconomic Dynamics, 2001
Clive W.J. Granger has summarized his personal viewpoint on testing for causality in numerous articles over the past 30 years and has outlined what he considers to be a useful operational version of his original definition of Granger causality, which he notes is partially alluded to in the Ph.D. dissertation of Norbert Wiener.
Chao, John, Corradi, Valentina, Swanson, Norman R.   +2 more
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Surrogate-based test for Granger causality

2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718), 2003
An approach for testing the presence of Granger causality between two time series is proposed. The residue of the destination signal after self-prediction is computed, after which a cross-prediction of the source signal over this residue is examined. In the absence of causality, there should be no cross-predictive power, due to which the performance of
T. Gautama, M.M. Van Hulle
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Statistical Tests for Detecting Granger Causality

IEEE Transactions on Signal Processing, 2018
Detection of a causal relationship between two or more sets of data is an important problem across various scientific disciplines. The Granger causality index and its derivatives are important metrics developed and used for this purpose. However, the test statistics based on these metrics ignore the effect of practical measurement impairments such as ...
Chopra, Ribhu, Murthy, Chandra Ramabhadra, Rangarajan, Govindan   +2 more
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Testing for Granger causality with mixed frequency data

Journal of Econometrics, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ghysels, Eric, Hill, Jonathan B., Motegi, Kaiji   +2 more
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Granger causality tests based on reduced variable information

Journal of Time Series Analysis, 2023
Granger causality is a classical and important technique for measuring predictability from one group of time series to another by incorporating information of the variables described by a full vector autoregressive (VAR) process. However, in some applications economic forecasts need to be made based on information provided merely by a portion of ...
Neng‐Fang Tseng, Ying‐Chao Hung, Junji Nakano   +2 more
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A note on tests of Granger causality

Applied Economics, 1984
(1984). A note on tests of Granger causality. Applied Economics: Vol. 16, No. 3, pp. 335-342.
D. A. Bessler, J. L. Kling
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Granger Causality Testing with Intensive Longitudinal Data

Prevention Science, 2018
The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling.
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