Compara mètodes

	Test de causalitat de Granger	Regressió per Mínims Quadrats Ordinàris (MQO)
Camp	Econometria	Econometria
Família	Regression model	Regression model
Any d'origen	1969	2019
Autor original	Clive W. J. Granger	Wooldridge (textbook treatment); classical least squares
Tipus	Time-series predictive causality test	Linear regression
Font seminal	Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Àlies	Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Relacionats	5	5
Resum	The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause.	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).