Bandingkan metode
Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.
| Panel Kausalitas Bootstrap Kónya× | Model Efek Tetap Data Panel× | |
|---|---|---|
| Bidang | Ekonometrika | Ekonometrika |
| Keluarga≠ | Hypothesis test | Regression model |
| Tahun asal≠ | 2006 | 2014 |
| Pencetus≠ | László Kónya | Hsiao (textbook treatment); within transformation of panel data |
| Tipe≠ | Non-parametric bootstrap hypothesis test | Panel data regression |
| Sumber perintis≠ | 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 ↗ |
| Alias | 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 |
| Terkait≠ | 3 | 5 |
| Ringkasan≠ | 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). |
| ScholarGateSet data ↗ |
|
|