Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Tofauti-katika-Tofauti (Diff-in-Diff)× | Kipimo cha Granger Causality× | |
|---|---|---|
| Nyanja | Ekonometriki | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1994 | 1969 |
| Mwanzilishi≠ | Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment) | Clive W. J. Granger |
| Aina≠ | Causal inference / panel regression | Time-series predictive causality test |
| Chanzo asilia≠ | Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355 | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗ |
| Majina mbadala≠ | diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff) | Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes. | 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. |
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