विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| संरचनात्मक विराम हौसमान परीक्षण (Structural Break Hausman Test)× | संरचनात्मक ब्रेक यादृच्छिक प्रभाव मॉडल× | |
|---|---|---|
| क्षेत्र | अर्थमिति | अर्थमिति |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 1978 (base); extended through 1990s–2000s | 1998–2000s |
| प्रवर्तक≠ | Jerry A. Hausman (base test, 1978); structural break extension developed in panel econometrics literature | Bai & Perron (break detection); Baltagi (panel RE framework) |
| प्रकार≠ | Specification test | Panel regression with regime shifts |
| मौलिक स्रोत≠ | Hausman, J. A. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271. DOI ↗ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ |
| उपनाम | Hausman test under structural change, structural change Hausman specification test, break-robust Hausman test, panel specification test with breaks | RE model with structural breaks, break-adjusted random effects, random effects break model, panel RE with regime shifts |
| संबंधित | 5 | 5 |
| सारांश≠ | The Structural Break Hausman Test extends the classical Hausman (1978) specification test to panel or time-series settings where the data-generating process shifts at one or more break points. By detecting structural breaks first and then running the Hausman comparison within each regime, researchers can reliably choose between fixed effects and random effects estimators even when the underlying relationship changes over time. | The structural break random effects model extends standard panel RE estimation by allowing one or more breakpoints at which slope coefficients or error variances shift across time. It combines structural change detection (e.g., Bai-Perron) with the GLS-based random effects estimator, producing regime-specific parameter estimates while retaining the efficiency gains of pooling individual-level variation as random draws from a common distribution. |
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