Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| ARFIMA: Модель дробово інтегрованої ARMA× | Панельна векторна авторегресія (Panel VAR)× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1980 | 1988 |
| Автор методу≠ | Granger & Joyeux (1980); Hosking (1981) | Holtz-Eakin, Newey & Rosen |
| Тип≠ | Long-memory time series model | Panel vector autoregression |
| Основоположне джерело≠ | Granger, C. W. J. & Joyeux, R. (1980). An Introduction to Long-Memory Time Series Models and Fractional Differencing. Journal of Time Series Analysis, 1(1), 15–29. DOI ↗ | Holtz-Eakin, D., Newey, W. & Rosen, H. S. (1988). Estimating Vector Autoregressions with Panel Data. Econometrica, 56(6), 1371-1395. DOI ↗ |
| Інші назви≠ | fractionally integrated ARMA, long-memory time series model, ARFIMA / FIGARCH, fractional differencing model | PVAR, panel vector autoregression, Panel VAR (PVAR) |
| Пов'язані≠ | 5 | 3 |
| Підсумок≠ | ARFIMA is a time series model that captures long-memory behaviour using a fractional differencing parameter d, generalising the integer differencing of ARIMA. It was introduced by Granger and Joyeux (1980) and formalised by Hosking (1981) to describe series whose autocorrelations decay slowly rather than abruptly. | Panel VAR extends the vector autoregression model to panel data, modelling the dynamic interactions among several variables while controlling for cross-unit heterogeneity through fixed effects. It was introduced by Holtz-Eakin, Newey and Rosen in 1988 and produces impulse-response functions and variance decompositions at the panel level. |
| ScholarGateНабір даних ↗ |
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