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Uji Kausalitas Toda-Yamamoto Bayesian

Prosedur kausalitas Toda-Yamamoto Bayesian menggabungkan strategi augmentasi VAR Toda-Yamamoto — yang menghindari kebutuhan pengujian awal integrasi dan kointegrasi — dengan pembaruan prior-posterior Bayesian. Prosedur ini menguji non-kausalitas Granger antara deret waktu yang mungkin terintegrasi atau terkointegrasi tanpa memerlukan differencing atau pemodelan koreksi-kesalahan, sambil menggabungkan informasi prior dan menghasilkan distribusi posterior penuh atas parameter kausal.

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Sumber

  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. Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471982326

Cara menyitasi halaman ini

ScholarGate. (2026, June 3). Bayesian Toda-Yamamoto Granger Causality Test. ScholarGate. https://scholargate.app/id/econometrics/bayesian-toda-yamamoto-causality

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ScholarGateBayesian Toda-Yamamoto Causality (Bayesian Toda-Yamamoto Granger Causality Test). Diakses 2026-06-15 dari https://scholargate.app/id/econometrics/bayesian-toda-yamamoto-causality · Set data: https://doi.org/10.5281/zenodo.20539026