เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| แบบจำลองนัยถดถอยแบบอัตโนมัติแบบไม่เชิงเส้น (NARDL)× | การถดถอยควอนไทล์× | แบบจำลอง STAR (Smooth Transition Autoregressive Model)× | |
|---|---|---|---|
| สาขาวิชา | เศรษฐมิติ | เศรษฐมิติ | เศรษฐมิติ |
| ตระกูล | Regression model | Regression model | Regression model |
| ปีกำเนิด≠ | 2014 | 1978 | 1994 |
| ผู้ริเริ่ม≠ | Shin, Yu & Greenwood-Nimmo | Koenker & Bassett | Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002) |
| ประเภท≠ | Asymmetric cointegration / error-correction model | Conditional quantile regression | Nonlinear time-series regime-switching model |
| แหล่งต้นตำรับ≠ | Shin, Y., Yu, B. & Greenwood-Nimmo, M. (2014). Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework. In: Sickles, R. & Horrace, W. (Eds.), Festschrift in Honor of Peter Schmidt. Springer. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ | Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗ |
| ชื่อเรียกอื่น≠ | nonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL) | conditional quantile regression, regression quantiles, Kantil Regresyon | smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR |
| ที่เกี่ยวข้อง≠ | 4 | 5 | 4 |
| สรุป≠ | The NARDL model, introduced by Shin, Yu and Greenwood-Nimmo in 2014, extends the ARDL framework to capture asymmetric long-run and short-run relationships, testing whether positive and negative changes in a regressor affect the dependent variable differently. | Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails. | The Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations. |
| ScholarGateชุดข้อมูล ↗ |
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