विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| फूरियर रैंडम इफेक्ट्स मॉडल× | पैनल रैंडम इफेक्ट्स मॉडल× | |
|---|---|---|
| क्षेत्र | अर्थमिति | अर्थमिति |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 2006-2012 | 1966 |
| प्रवर्तक≠ | Becker, Enders & Lee; Enders & Lee | Balestra & Nerlove |
| प्रकार≠ | Panel regression with Fourier approximation | Panel data estimator |
| मौलिक स्रोत≠ | Becker, R., Enders, W., & Lee, J. (2006). A stationary test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409. DOI ↗ | Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612. DOI ↗ |
| उपनाम | Fourier RE model, FFF random effects, flexible Fourier random effects, Fourier augmented random effects | random effects estimator, RE model, GLS random effects, error components model |
| संबंधित | 5 | 5 |
| सारांश≠ | The Fourier Random Effects Model extends the standard random effects panel estimator by incorporating trigonometric (Fourier) terms to approximate smooth, gradual structural change in time trends or intercepts. It retains the GLS efficiency advantages of the random effects estimator while allowing parameters to shift continuously over time without requiring knowledge of exact break dates. | The panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation. |
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