方法对比
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| Dumitrescu-Hurlin面板格兰杰因果检验× | Kónya Bootstrap Panel Granger Causality× | 面板数据固定效应模型× | |
|---|---|---|---|
| 领域 | 计量经济学 | 计量经济学 | 计量经济学 |
| 方法族≠ | Hypothesis test | Hypothesis test | Regression model |
| 起源年份≠ | 2012 | 2006 | 2014 |
| 提出者≠ | Elena-Ivona Dumitrescu & Christophe Hurlin | László Kónya | Hsiao (textbook treatment); within transformation of panel data |
| 类型≠ | Non-causality test for heterogeneous panels | Non-parametric bootstrap hypothesis test | Panel data regression |
| 开创性文献≠ | Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460. 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 ↗ |
| 别名 | DH Causality Test, Panel Granger Causality Test (Heterogeneous), Dumitrescu-Hurlin Test, Heterojen Panel 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 |
| 相关≠ | 3 | 3 | 5 |
| 摘要≠ | The Dumitrescu-Hurlin (DH) test, introduced by Elena-Ivona Dumitrescu and Christophe Hurlin in their 2012 Economic Modelling article, tests for Granger non-causality in heterogeneous panel datasets. Unlike standard panel causality approaches, it permits each cross-sectional unit to have its own distinct causal relationship, making it well-suited for macro-panels of countries, firms, or regions where homogeneity cannot be assumed. | 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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