Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Teste de Causalidade de Granger× | Causalidade de Granger em Painel Bootstrap de Kónya× | |
|---|---|---|
| Área | Econometria | Econometria |
| Família≠ | Regression model | Hypothesis test |
| Ano de origem≠ | 1969 | 2006 |
| Autor original≠ | Clive W. J. Granger | László Kónya |
| Tipo≠ | Time-series predictive causality test | Non-parametric bootstrap hypothesis test |
| Fonte seminal≠ | 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 ↗ |
| Outros nomes | 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 |
| Relacionados≠ | 5 | 3 |
| Resumo≠ | 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. |
| ScholarGateConjunto de dados ↗ |
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