Sammenlign metoder

	Durbin-Watson-testen for autokorrelation	Breusch-Godfrey LM-test for seriel korrelation
Fagområde	Økonometri	Økonometri
Familie	Regression model	Regression model
Oprindelsesår	1950	1978
Ophavsperson	James Durbin & Geoffrey Watson	Trevor Breusch & Leslie Godfrey
Type	Test for first-order residual autocorrelation	Lagrange-multiplier test for serial correlation
Oprindelig kilde	Durbin, J., & Watson, G. S. (1950). Testing for serial correlation in least squares regression: I. Biometrika, 37(3/4), 409–428.	Godfrey, L. G. (1978). Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica, 46(6), 1293–1301.
Aliasser	DW test, Durbin-Watson statistic, Durbin-Watson otokorelasyon testi	BG test, LM test for autocorrelation, Breusch-Godfrey serial correlation test, Breusch-Godfrey otokorelasyon testi
Relaterede	4	3
Resumé	The Durbin-Watson test, developed by James Durbin and Geoffrey Watson in 1950–1951, detects first-order serial correlation in the residuals of a linear regression. Its statistic ranges from 0 to 4, with a value near 2 indicating no autocorrelation, values toward 0 indicating positive autocorrelation, and values toward 4 indicating negative autocorrelation. It remains one of the most reported regression diagnostics despite well-known limitations.	The Breusch-Godfrey test is a Lagrange-multiplier test for serial correlation in regression residuals, developed independently by Trevor Breusch (1978) and Leslie Godfrey (1978). Unlike the Durbin-Watson test, it detects autocorrelation up to any chosen order p, remains valid when the model includes lagged dependent variables, and produces a definite chi-square p-value rather than an inconclusive region — making it the modern standard for autocorrelation testing.