Regression modelEconometrics / time series

Structural Break Granger Causality

Structural break Granger causality extends the classic Granger causality framework to accommodate regime shifts and parameter instability in time series. By detecting break points and testing causality within sub-samples or via rolling/recursive windows, it reveals whether a predictive relationship between variables switches on, switches off, or changes direction over time.

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Sources

  1. Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI: 10.1016/0304-4076(94)01616-8
  2. Balcilar, M., Ozdemir, Z. A., & Arslanturk, Y. (2010). Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window. Energy Economics, 32(6), 1398-1410. DOI: 10.1016/j.eneco.2010.05.006

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Referenced by

ScholarGateStructural Break Granger Causality (Granger Causality Testing with Structural Breaks). Retrieved 2026-06-04 from https://scholargate.app/en/econometrics/structural-break-granger-causality