Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Модель випадкових ефектів Фур'є× | Модель випадкових ефектів з часовими параметрами× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2006-2012 | 1970–1975 |
| Автор методу≠ | Becker, Enders & Lee; Enders & Lee | Swamy (1970); Hsiao (1975) |
| Тип≠ | Panel regression with Fourier approximation | Panel regression with time-varying random coefficients |
| Основоположне джерело≠ | 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 ↗ | Swamy, P. A. V. B. (1970). Efficient inference in a random coefficient regression model. Econometrica, 38(2), 311–323. DOI ↗ |
| Інші назви | Fourier RE model, FFF random effects, flexible Fourier random effects, Fourier augmented random effects | TVP-RE model, random coefficient random effects model, time-varying random effects, TVP panel random effects |
| Пов'язані | 5 | 5 |
| Підсумок≠ | 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 time-varying parameter random effects model extends the classic random effects panel framework by allowing regression coefficients to change over time and across units. Rather than imposing a single fixed slope for all individuals and periods, each coefficient is treated as a random draw that evolves, capturing genuine parameter instability while preserving the random effects assumption that unit-specific components are uncorrelated with the regressors. |
| ScholarGateНабір даних ↗ |
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