Quantile Granger causality in the presence of instability

We propose a new framework for assessing Granger causality in quantiles in unstable environments, for a fixed quantile or over a continuum of quantile levels. Our proposed test statistics are consistent against fixed alternatives, they have nontrivial power against local alternatives, and they are pivotal in certain important special cases. In addition, we show the validity of a bootstrap procedure when asymptotic distributions depend on nuisance parameters. Monte Carlo simulations reveal that the proposed test statistics have correct empirical size and high power, even in absence of structural breaks. Moreover, a procedure providing additional insight into the timing of Granger causal regimes based on our new tests is proposed. Finally, an empirical application in energy economics highlights the applicability of our method as the new tests provide stronger evidence of Granger causality.

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Publication Details

Journal
Journal of Econometrics
Published
2025-03-23
DOI
https://doi.org/10.1016/j.jeconom.2025.105992
Citations
5
Primary Topic
Statistical and numerical algorithms
Type
article
Field-Weighted Citation Impact
18.64

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article

Quantile Granger causality in the presence of instability

Victor Troster, Dominik Wied, Alexander Mayer
5 citations
Journal of Econometrics
Statistical and numerical algorithms
18.64
article

Quantile Granger causality in the presence of instability

Victor Troster, Dominik Wied, Alexander Mayer
article en
5 citations

Abstract

We propose a new framework for assessing Granger causality in quantiles in unstable environments, for a fixed quantile or over a continuum of quantile levels. Our proposed test statistics are consistent against fixed alternatives, they have nontrivial power against local alternatives, and they are pivotal in certain important special cases. In addition, we show the validity of a bootstrap procedure when asymptotic distributions depend on nuisance parameters. Monte Carlo simulations reveal that the proposed test statistics have correct empirical size and high power, even in absence of structural breaks. Moreover, a procedure providing additional insight into the timing of Granger causal regimes based on our new tests is proposed. Finally, an empirical application in energy economics highlights the applicability of our method as the new tests provide stronger evidence of Granger causality.

Journal of EconometricsVol. 249
Ca' Foscari University of Venice (IT), University of Cologne (DE), Fundació Universitat-Empresa de les Illes Balears (ES), Universitat de les Illes Balears (ES)
Ministerio de Educación y Formación Profesional
Climate action
Openalex Percentile: Top 1%
Statistical and numerical algorithms
18.64
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Quantile Granger causality in the presence of instability — Victor Troster, Dominik Wied, et al. · Journal of Econometrics (2025) | TGRS Research Map | TGRS