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The Breusch–Godfrey test is a test for autocorrelation in the errors in a regression model. It makes use of the residuals from the model being considered in a regression analysis, and a test statistic is derived from these. The null hypothesis is that there is no serial correlation of any order up to p. [3]
Statistical tests are used to test the fit between a hypothesis and the data. [1] [2] Choosing the right statistical test is not a trivial task. [1]The choice of the test depends on many properties of the research question.
Leslie George Godfrey (born 1946) is a British econometrician. The Breusch–Godfrey test is named after him and Trevor S. Breusch . [ 1 ] He is an emeritus professor of econometrics at the University of York .
Breusch–Godfrey test; Breusch–Pagan statistic – redirects to Breusch–Pagan test; Breusch–Pagan test; Brown–Forsythe test; Brownian bridge; Brownian excursion; Brownian motion; Brownian tree; Bruck–Ryser–Chowla theorem; Burke's theorem; Burr distribution; Business statistics; Bühlmann model; Buzen's algorithm; BV4.1 (software)
Engle's LM test for autoregressive conditional heteroskedasticity (ARCH), a test for time-dependent volatility, the Breusch–Godfrey test, and Durbin's alternative test for serial correlation are also available. All (except -dwatson-) tests separately for higher-order serial correlations.
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He is noted for the Breusch–Pagan test from the paper (with Adrian Pagan) "A simple test for heteroscedasticity and random coefficient variation" (see Noted works, below). Another contribution to econometrics is the serial correlation Lagrange multiplier test, often called Breusch–Godfrey test after Breusch and Leslie G. Godfrey , which can ...
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