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Teste de Limites ARDL (Teste de Limites de Pesaran)×Teste de Cointegração (Johansen / Engle-Granger)×Regressão por Mínimos Quadrados Ordinários (MQO)×
ÁreaEconometriaEconometriaEconometria
FamíliaRegression modelRegression modelRegression model
Ano de origem200119882019
Autor originalPesaran, Shin & SmithEngle & Granger (1987); Johansen (1988)Wooldridge (textbook treatment); classical least squares
TipoCointegration test / Autoregressive distributed lag modelTime-series cointegration testLinear regression
Fonte seminalPesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(3), 289–326. DOI ↗Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Outros nomesPesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)Johansen cointegration test, Engle-Granger cointegration test, long-run equilibrium test, Eşbütünleşme Testi (Johansen/Engle-Granger)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Relacionados455
ResumoThe ARDL bounds test is an autoregressive distributed lag method that tests for a cointegrating (long-run level) relationship between time series, introduced by Pesaran, Shin and Smith in 2001. Unlike the Johansen procedure, it remains valid whether the variables are I(0), I(1) or a mix of the two, and it is more reliable than Johansen in small samples of roughly 30 to 80 observations.The cointegration test examines whether non-stationary time series that each contain a unit root share a stable long-run equilibrium relationship. The single-equation residual approach was introduced by Engle and Granger (1987) and the system-based rank approach by Johansen (1988).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).
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ScholarGateComparar métodos: ARDL Bounds Test · Cointegration Test · OLS Regression. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare