Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| PANIC tests: Vienlaides vienību saknes analīze ar kopējo faktoru sadalījumu× | Dinamiskais faktormodelis× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime≠ | Hypothesis test | Regression model |
| Izcelsmes gads≠ | 2004 | 2002 |
| Autors≠ | Jushan Bai & Serena Ng | James Stock & Mark Watson |
| Tips≠ | Panel unit root test | Latent-factor time-series model |
| Pirmavots≠ | Bai, J., & Ng, S. (2004). A PANIC attack on unit roots and cointegration. Econometrica, 72(4), 1127–1177. DOI ↗ | Stock, J. H., & Watson, M. W. (2002). Macroeconomic forecasting using diffusion indexes. Journal of Business & Economic Statistics, 20(2), 147–162. DOI ↗ |
| Citi nosaukumi | Panel Analysis of Non-stationarity in Idiosyncratic and Common Components, Bai-Ng PANIC Test, Second-Generation Panel Unit Root Test, Panel Birim Kök Testi (PANIC) | Diffusion Index Model, Large-Scale Factor Model, Approximate Factor Model, Dinamik Faktör Modeli |
| Saistītās≠ | 3 | 2 |
| Kopsavilkums≠ | PANIC (Panel Analysis of Non-stationarity in Idiosyncratic and Common Components) is a second-generation panel unit root test introduced by Bai and Ng (2004). It decomposes each panel series into common factors and idiosyncratic components, then tests for unit roots in each part separately, making it robust to cross-sectional dependence — a critical limitation of first-generation tests such as IPS or LLC. | 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. |
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