Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Modelo de Defasagem Autorregressiva Não Linear Distribuída (NARDL)× | Regressão por Mínimos Quadrados Ordinários (MQO)× | Modelo Autorregressivo de Transição Suave (STAR)× | |
|---|---|---|---|
| Área | Econometria | Econometria | Econometria |
| Família | Regression model | Regression model | Regression model |
| Ano de origem≠ | 2014 | 2019 | 1994 |
| Autor original≠ | Shin, Yu & Greenwood-Nimmo | Wooldridge (textbook treatment); classical least squares | Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002) |
| Tipo≠ | Asymmetric cointegration / error-correction model | Linear regression | Nonlinear time-series regime-switching model |
| Fonte seminal≠ | 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 | Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗ |
| Outros nomes≠ | nonlinear ARDL, asymmetric ARDL, Doğrusal Olmayan ARDL (NARDL) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu | smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR |
| Relacionados≠ | 4 | 5 | 4 |
| Resumo≠ | 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). | 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. |
| ScholarGateConjunto de dados ↗ |
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