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Uji Kausalitas Granger Panel×Uji Kausalitas Toda-Yamamoto×
BidangEkonometrikaEkonometrika
KeluargaRegression modelRegression model
Tahun asal1988–20121995
PencetusHoltz-Eakin, Newey & Rosen (1988); Dumitrescu & Hurlin (2012)Toda, H. Y. and Yamamoto, T.
TipeCausality testCausality test
Sumber perintisDumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460. DOI ↗Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗
Aliaspanel causality test, Dumitrescu-Hurlin test, heterogeneous panel causality, panel Granger testToda-Yamamoto test, TY causality test, modified Wald test for Granger causality, TY-MWALD
Terkait55
RingkasanThe Panel Granger Causality test examines whether past values of one variable help predict another variable across multiple cross-sectional units observed over time. It extends the classical Granger causality framework to panel data, accounting for cross-sectional heterogeneity and enabling more powerful inference by pooling information across units.The Toda-Yamamoto (TY) causality test is a modified Wald procedure for testing Granger causality in vector autoregressions (VARs) estimated in levels, even when variables are nonstationary or cointegrated. By intentionally over-fitting the VAR with extra lags equal to the maximum integration order, it restores the standard chi-squared asymptotic distribution of the Wald statistic without requiring prior unit-root or cointegration pretesting.
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ScholarGateBandingkan metode: Panel Granger Causality · Toda-Yamamoto causality test. Diakses 2026-06-19 dari https://scholargate.app/id/compare