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Modelo ARDL Não Linear (NARDL)×Teste de Cointegração de Engle-Granger×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem20141987
Autor originalShin, Yu & Greenwood-NimmoRobert F. Engle and Clive W. J. Granger
TipoNonlinear cointegration modelCointegration test
Fonte seminalShin, 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 ↗Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗
Outros nomesNARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration modelEG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test
Relacionados55
ResumoThe 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.The Engle-Granger two-step method tests whether two or more non-stationary I(1) time series share a common stochastic trend — that is, whether a linear combination of them is stationary. If cointegration is confirmed, an error-correction model (ECM) can be estimated to capture both short-run dynamics and long-run equilibrium adjustment.
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ScholarGateComparar métodos: Nonlinear ARDL · Engle-Granger Cointegration Test. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare