So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Mô hình Tham số Thay đổi theo Thời gian NARDL (TVP-NARDL)× | Mô hình Tự hồi quy Phân phối Trễ Phi tuyến (NARDL)× | |
|---|---|---|
| Lĩnh vực | Kinh tế lượng | Kinh tế lượng |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 2019 (TVP extension); 2014 (NARDL base) | 2014 |
| Người khởi xướng≠ | Bagnai & Ospina-Rojas (TVP extension); NARDL base by Shin, Yu & Greenwood-Nimmo | Shin, Yu & Greenwood-Nimmo |
| Loại≠ | Nonlinear time-series model with time-varying coefficients | Asymmetric cointegration / error-correction model |
| Công trình gốc≠ | Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In W. Horrace & R. Sickles (Eds.), Festschrift in Honor of Peter Schmidt (pp. 281–314). Springer. link ↗ | 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 ↗ |
| Tên gọi khác≠ | TVP-NARDL, time-varying NARDL, rolling NARDL, dynamic asymmetric ARDL | nonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL) |
| Liên quan≠ | 3 | 4 |
| Tóm tắt≠ | The Time-Varying Parameter NARDL (TVP-NARDL) model extends the Nonlinear ARDL framework by allowing the coefficients on positive and negative partial sums of a regressor to change over time. This combination captures both asymmetric responses and structural instability in long-run and short-run relationships within a single cointegrating specification. | 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. |
| ScholarGateBộ dữ liệu ↗ |
|
|