Add to ORKGtextabstractWe develop a bivariate spectral Granger-causality test that can be applied at each individual frequency of the spectrum. The spectral approach to Granger causality has the distinct advantage that it allows to disentangle (potentially) di®erent Granger- causality relationships over di®erent time horizons. We illustrate the usefulness of the proposed approach in the context of the predictive value of European production expectation surveys
A time series is said to Granger cause another series if it has incremental predictive power when fo...
A straightforward nonlinear extension of Grangers concept of causality in the kernel framework is s...
The traditional parametric approach to Granger causality (GC), based on linear vector autoregressive...
We develop a bivariate spectral Granger-causality test that can be applied at each individual freque...
Decomposing Granger causality over the spectrum allows us to disentangle potentially different Grang...
Granger-causality is a popular definition of causality that permits a statistical test to determine ...
We would like to thank the Associate Editor and the referees for their constructive comments. This r...
A widely agreed upon definition of time series causality inference, established in the sem-inal 1969...
In this article, I introduce a command (bcgcausality) to implement Breitung and Candelon's (2006, Jo...
We propose a bootstrap test for unconditional and conditional Granger-causality spectra in the frequ...
Granger causality is a statistical concept of causality that is based on prediction. According to Gr...
Spectral measures of causality are used to explore the role of different rhythms in the causal conne...
This paper discusses the Granger causality test by a spectrum estimator which allows the transfer fu...
Granger-causality in the frequency domain is an emerging tool to analyze the causal relationship be...
We present a novel test of nonlinear Granger causality in bivariate time series. The trace norm of c...
A time series is said to Granger cause another series if it has incremental predictive power when fo...
A straightforward nonlinear extension of Grangers concept of causality in the kernel framework is s...
The traditional parametric approach to Granger causality (GC), based on linear vector autoregressive...
We develop a bivariate spectral Granger-causality test that can be applied at each individual freque...
Decomposing Granger causality over the spectrum allows us to disentangle potentially different Grang...
Granger-causality is a popular definition of causality that permits a statistical test to determine ...
We would like to thank the Associate Editor and the referees for their constructive comments. This r...
A widely agreed upon definition of time series causality inference, established in the sem-inal 1969...
In this article, I introduce a command (bcgcausality) to implement Breitung and Candelon's (2006, Jo...
We propose a bootstrap test for unconditional and conditional Granger-causality spectra in the frequ...
Granger causality is a statistical concept of causality that is based on prediction. According to Gr...
Spectral measures of causality are used to explore the role of different rhythms in the causal conne...
This paper discusses the Granger causality test by a spectrum estimator which allows the transfer fu...
Granger-causality in the frequency domain is an emerging tool to analyze the causal relationship be...
We present a novel test of nonlinear Granger causality in bivariate time series. The trace norm of c...
A time series is said to Granger cause another series if it has incremental predictive power when fo...
A straightforward nonlinear extension of Grangers concept of causality in the kernel framework is s...
The traditional parametric approach to Granger causality (GC), based on linear vector autoregressive...