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The null hypothesis of Godfrey’s tests is that the equation residuals are white noise. If the residuals have second- but not higher-order autocorrelation, the lag 2 test might be more likely to reject the same is true for third-order autocorrelation and the lag 3 test. Thus, if the residuals in fact have only first-order autocorrelation, the lag 1 test has the most power for rejecting the null hypothesis of uncorrelated residuals. Godfrey's Serial Correlation Test Equation Alternative LM Pr >LM y 1 6.63 0.0100 2 6.89 0.0319 3 6.96 0.0732 The three variations of the test reported by the GODFREY=3 option are designed to have power against different alternative hypothesis. The following is an example of the output produced by the GODFREY=3 option. When a nonlinear model is estimated, the test is computed by using a linearized model. The tests are performed separately for each equation estimated by the FIT statement.

Is the maximum autoregressive order, and specifies that Godfrey’s tests be computed for lags 1 through. The GODFREY= option in the FIT statement produces the Godfrey Lagrange multiplier test for serially correlated residuals for each equation (Godfrey 1978a and 1978b). The standard, text-book, approach is to use the regressors from the original equation (and EViews usually adds those variables to that white box by default). Whichever regressors you wish to use in the auxiliary regression for the BPG Test.

Sorry, I meant the Breusch-Pagan-Godfrey test.

WGTRESID are the residuals, weighted by whatever weight series you used in the original equation. QMS Gareth wrote:Which 'blank' area are you talking about? If you're using the Breusch-Goodfrey Serial Correlation LM Test from the menus, there is no 'blank' area. Descargar Resident Evil Code Veronica Ps2 Iso Files here. 0 =0, consider the following simple regression for the Phillips curve.

STATA NOTES: To demonstrate that replacing the missing value of.

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