Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Modeli Autoregresiv me Vonesë Jolineare (NARDL)× | Regresioni me Mënyrën më të Vogël të Katrorëve (OLS)× | |
|---|---|---|
| Fusha | Ekonometri | Ekonometri |
| Familja | Regression model | Regression model |
| Viti i origjinës≠ | 2014 | 2019 |
| Krijuesi≠ | Shin, Yu, and Greenwood-Nimmo | Wooldridge (textbook treatment); classical least squares |
| Lloji≠ | Nonlinear cointegration model | Linear regression |
| Burimi themelues≠ | Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281-314). Springer. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Emërtime të tjera | NARDL, nonlinear ARDL, asymmetric ARDL, nonlinear bounds test | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Të lidhura≠ | 4 | 5 |
| Përmbledhja≠ | The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing an explanatory variable into its positive and negative partial sums, it tests whether increases and decreases in a regressor have different effects on the dependent variable — a feature that linear cointegration methods cannot capture. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
| ScholarGateSeti i të dhënave ↗ |
|
|