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Structural Break Granger Causality/Evidence
Method evidence record

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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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Granger Causality Testing with Structural Breaks
Taxonomic method record · regression-model / econometrics
  • 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
  • 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.2010.05.015
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyGranger Causalitymachine-suggested · Relational suggestion, not evidence.Used in the same domainToda-Yamamoto Causalitymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketVector Autoregressionmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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