Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Modeli Autoregresiv i Vonesës së Shpërndarë Jo-lineare (NARDL)× | Regresioni me Mënyrën më të Vogël të Katrorëve (OLS)× | Regresioni kuantil× | Model Autoregresiv me Tranzicion të Lëmuar (STAR)× | |
|---|---|---|---|---|
| Fusha | Ekonometri | Ekonometri | Ekonometri | Ekonometri |
| Familja | Regression model | Regression model | Regression model | Regression model |
| Viti i origjinës≠ | 2014 | 2019 | 1978 | 1994 |
| Krijuesi≠ | Shin, Yu & Greenwood-Nimmo | Wooldridge (textbook treatment); classical least squares | Koenker & Bassett | Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002) |
| Lloji≠ | Asymmetric cointegration / error-correction model | Linear regression | Conditional quantile regression | Nonlinear time-series regime-switching model |
| Burimi themelues≠ | 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 ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 | 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 ↗ |
| Emërtime të tjera≠ | nonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu | conditional quantile regression, regression quantiles, Kantil Regresyon | smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR |
| Të lidhura≠ | 4 | 5 | 5 | 4 |
| Përmbledhja≠ | 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. | 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). | 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. |
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