Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| GARCH-MIDAS× | Локальные проекции× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2012 | 2005 |
| Автор метода≠ | Engle and Ghysels | Oscar Jorda |
| Тип≠ | Time-varying variance model | Multi-horizon regression |
| Основополагающий источник≠ | Engle, R. F., & Ghysels, E. (2012). GARCH for long memory. Journal of Econometrics, 164(2), 385-391. link ↗ | Jorda, O. (2005). Estimation and inference of impulse responses by local projections. American Economic Review, 95(1), 161-182. DOI ↗ |
| Другие названия≠ | Mixed-frequency volatility model | LP-IR, Multi-horizon regression |
| Связанные | 3 | 3 |
| Сводка≠ | GARCH-MIDAS decomposes volatility into short-term (GARCH) and long-term (MIDAS) components, allowing low-frequency macroeconomic variables to drive medium-term volatility while high-frequency returns govern daily fluctuations. Introduced by Engle and Ghysels (2012), this framework elegantly separates volatility time scales. The approach is powerful for understanding how macro conditions (growth, inflation) drive risk premia and for improved volatility forecasting. | Local Projections (LP) is a semi-parametric method for estimating impulse responses directly via multi-horizon regressions, bypassing VAR-model specification. Introduced by Jorda (2005), it projects outcomes h periods ahead onto current shocks and lags, producing impulse-response functions without assuming a particular lag structure or VAR order. This flexibility has made it the dominant approach in applied macroeconomics for measuring policy effects and shock transmission. |
| ScholarGateНабор данных ↗ |
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