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Test granic ARDL (Pesaran Bounds Test)×Regresja metodą najmniejszych kwadratów (OLS)×Model Korekcji Błędów Wektorowych (VECM)×
DziedzinaEkonometriaEkonometriaEkonometria
RodzinaRegression modelRegression modelRegression model
Rok powstania200120191987
TwórcaPesaran, Shin & SmithWooldridge (textbook treatment); classical least squaresEngle & Granger
TypCointegration test / Autoregressive distributed lag modelLinear regressionMultivariate time-series model
Źródło pierwotnePesaran, 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 ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Engle, R. F. & Granger, C. W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276. DOI ↗
Inne nazwyPesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuvector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli)
Pokrewne454
PodsumowanieThe 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.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 Vector Error Correction Model is a multivariate time-series model for cointegrated series that captures both their short-run dynamics and their long-run equilibrium relationship. It was introduced by Engle and Granger in 1987 as part of the cointegration and error-correction framework.
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