Sammenlign metoder

	ARDL-grænsetesten (Pesaran Bounds Test)	Almindelig mindste kvadraters metode (OLS) regression	Vektor fejlkorrektionsmodel (VECM)
Fagområde	Økonometri	Økonometri	Økonometri
Familie	Regression model	Regression model	Regression model
Oprindelsesår	2001	2019	1987
Ophavsperson	Pesaran, Shin & Smith	Wooldridge (textbook treatment); classical least squares	Engle & Granger
Type	Cointegration test / Autoregressive distributed lag model	Linear regression	Multivariate time-series model
Oprindelig kilde	Pesaran, 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.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860	Engle, R. F. & Granger, C. W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276.
Aliasser	Pesaran 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 regresyonu	vector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli)
Relaterede	4	5	4
Resumé	The 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.