Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Furjē paneļa datu analīze× | Fjūrjēra Grangera cēloniskuma tests× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2006 (Fourier framework); panel extensions 2010s | 2016 |
| Autors≠ | Becker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometricians | Enders and Jones |
| Tips≠ | Panel regression with Fourier terms | Causality test |
| Pirmavots≠ | Becker, R., Enders, W., & Lee, J. (2006). A stationary test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409. DOI ↗ | Enders, W., & Jones, P. (2016). Grain prices, oil prices, and multiple smooth breaks in a VAR. Studies in Nonlinear Dynamics and Econometrics, 20(4), 399–419. DOI ↗ |
| Citi nosaukumi | Fourier panel regression, smooth structural break panel model, trigonometric panel data model, Fourier-flexible panel estimator | Fourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causality |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | Fourier panel data analysis embeds trigonometric sine and cosine terms into a standard panel regression to approximate smooth, gradual structural shifts in the data-generating process. Rather than assuming a sharp break at a known date, the Fourier approach lets the data reveal the timing and shape of any structural change through a flexible trigonometric approximation, while retaining the cross-sectional and time-series structure of panel data. | The Fourier Granger causality test extends the classic Granger causality framework by embedding low-frequency Fourier terms in the VAR equation, allowing the causal relationship to shift gradually over time without requiring the researcher to pre-specify the number or location of structural breaks. |
| ScholarGateDatu kopa ↗ |
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