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| Nichtlineare OLS-Schätzung (Nichtlineare Kleinste-Quadrate-Schätzung)× | Nichtlineares ARDL (NARDL)-Modell× | |
|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 1974–1987 | 2014 |
| Urheber≠ | Gallant (1987); Wooldridge (2010) for econometric treatment | Shin, Yu & Greenwood-Nimmo |
| Typ≠ | Nonlinear regression estimator | Nonlinear cointegration model |
| Wegweisende Quelle≠ | Gallant, A. R. (1987). Nonlinear Statistical Models. John Wiley & Sons. ISBN: 978-0471802600 | 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. link ↗ |
| Aliasnamen | nonlinear least squares, NLS, NLLS, nonlinear regression | NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | Nonlinear Ordinary Least Squares (NLS) estimates regression models in which the conditional mean function is nonlinear in the parameters. Like standard OLS it minimises the sum of squared residuals, but because no closed-form solution exists the estimator is found by iterative numerical optimisation. Under standard regularity conditions NLS is consistent and asymptotically normal. | The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically. |
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