เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| แบบจำลองปัจจัยพลวัต× | แบบจำลอง Vector Autoregression (VAR)× | |
|---|---|---|
| สาขาวิชา | เศรษฐมิติ | เศรษฐมิติ |
| ตระกูล | Regression model | Regression model |
| ปีกำเนิด≠ | 2002 | 2005 |
| ผู้ริเริ่ม≠ | James Stock & Mark Watson | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| ประเภท≠ | Latent-factor time-series model | Multivariate time-series model |
| แหล่งต้นตำรับ≠ | Stock, J. H., & Watson, M. W. (2002). Macroeconomic forecasting using diffusion indexes. Journal of Business & Economic Statistics, 20(2), 147–162. DOI ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| ชื่อเรียกอื่น | Diffusion Index Model, Large-Scale Factor Model, Approximate Factor Model, Dinamik Faktör Modeli | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| ที่เกี่ยวข้อง≠ | 2 | 4 |
| สรุป≠ | A Dynamic Factor Model (DFM) extracts a small number of latent common factors from a large panel of economic time series and uses those factors to forecast or nowcast a target variable. Formalized for macroeconomic forecasting by James Stock and Mark Watson in their 2002 Journal of Business & Economic Statistics paper, DFMs handle hundreds of indicators simultaneously while avoiding the curse of dimensionality that plagues traditional multivariate models. | Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005). |
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