Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Grindžera koeficientu pārbaude× | Kónya Būta Foršas Paneļa Grāndžera Kauzalitāte× | Fiksēto efektu paneļa datu modelis× | |
|---|---|---|---|
| Nozare | Ekonometrija | Ekonometrija | Ekonometrija |
| Saime≠ | Regression model | Hypothesis test | Regression model |
| Izcelsmes gads≠ | 1969 | 2006 | 2014 |
| Autors≠ | Clive W. J. Granger | László Kónya | Hsiao (textbook treatment); within transformation of panel data |
| Tips≠ | Time-series predictive causality test | Non-parametric bootstrap hypothesis test | Panel data regression |
| Pirmavots≠ | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗ | Kónya, L. (2006). Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978–992. DOI ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Citi nosaukumi | Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi | Bootstrap Panel Causality Test, Kónya Panel Granger Causality, SUR-Based Bootstrap Causality, Kónya Önyükleme Nedensellik Testi | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Saistītās≠ | 5 | 3 | 5 |
| Kopsavilkums≠ | The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause. | Introduced by László Kónya in 2006, this method tests Granger causality in heterogeneous panels by estimating a Seemingly Unrelated Regressions (SUR) system and deriving country-specific critical values through bootstrapping. Unlike pooled panel tests, it delivers a separate causality verdict for each cross-section, making it particularly valuable in applied macroeconomics and international economics when panel units are expected to behave differently. | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). |
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