方法对比
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| ARFIMA：分数阶积分自回归滑动平均模型× | 面板向量自回归模型 (Panel VAR)× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1980 | 1988 |
| 提出者≠ | Granger & Joyeux (1980); Hosking (1981) | Holtz-Eakin, Newey & Rosen |
| 类型≠ | Long-memory time series model | Panel vector autoregression |
| 开创性文献≠ | 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 ↗ |
| 别名≠ | fractionally integrated ARMA, long-memory time series model, ARFIMA / FIGARCH, fractional differencing model | PVAR, panel vector autoregression, Panel VAR (PVAR) |
| 相关≠ | 5 | 3 |
| 摘要≠ | 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. |
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