Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Epälineaarinen autoregressiivinen hajautettu viive (NARDL) -malli× | Kvanttiiliregressio× | Järjestelmä-GMM (Arellano-Bover / Blundell-Bond)× | |
|---|---|---|---|
| Tieteenala | Ekonometria | Ekonometria | Ekonometria |
| Menetelmäperhe | Regression model | Regression model | Regression model |
| Syntyvuosi≠ | 2014 | 1978 | 1998 |
| Kehittäjä≠ | Shin, Yu & Greenwood-Nimmo | Koenker & Bassett | Arellano & Bover (1995); Blundell & Bond (1998) |
| Tyyppi≠ | Asymmetric cointegration / error-correction model | Conditional quantile regression | Dynamic panel data estimator |
| Alkuperäislähde≠ | 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 ↗ | Arellano, M. & Bond, S. (1991). Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies, 58(2), 277-297. DOI ↗ |
| Rinnakkaisnimet≠ | nonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL) | conditional quantile regression, regression quantiles, Kantil Regresyon | Arellano-Bover estimator, Blundell-Bond estimator, dynamic panel GMM, Sistem GMM (Arellano-Bover / Blundell-Bond) |
| Liittyvät≠ | 4 | 5 | 4 |
| Tiivistelmä≠ | 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. | System GMM is a generalized method of moments estimator for dynamic panel models that contain a lagged dependent variable. Introduced by Blundell and Bond (1998), building on Arellano and Bover, it augments the differenced equation of the earlier difference GMM (Arellano-Bond) with the equation in levels to deliver consistent estimates when N is large and T is small. |
| ScholarGateAineisto ↗ |
|
|
|