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Breusch-Godfrey:

What does it do?It is used to detect autocorrelation. I.E whether there is any relationship between the

error terms. It tests for the rth order of autocorrelation.

How is it carried out? (Slide 130)Null H0: = p1 0 and pr = 0Alt. H1: p1 0 andpr 0

a) Estimate the linear regression using OLS methodology, obtain residuals

b) Regress ut on all regressors from step a. Obtain r^2

c) (T-r) R^2 ~ X^2 (r) [~ means this is this, and that is that]

d) If (T-r) R^2 > critical value, no autocorrelation probably > 0.05 accept null.

What do the values suggest?Reject the null because the value is lower than 0.05, therefore it is not significant whichmeans we do have autocorrelation in the residuals.

What are the consequences of ignoring autocorrelation if it is present?See slide 131

What are the remedies?

See slide 132-134

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Jarque-Bera:

What does it do? Testing for departures from normality. (Normality is when normal distribution is notskewed and kurtosis is 3 and excess kurtosis is 0.) Jarque-bera formalises this by testingfor normality by finding out whether skewness is 0 and kurtosis is 3 and excess is 0.

How is it carried out?1 and 2 can be estimated using the residuals from the OLS regression, Error term.

See slide 143 for more detail

What does the values suggest?

Because the p value is less than the significance we reject the H Null of normality.

What are the consequences of ignoring this?Any inferences we make through hypothesis testing may be incorrect as it does notfollow a normal distribution.

What are the remedies?Slide 144

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ARCH Test:

What does it do?

Defined as current volatility or conditional variance depends on the magnitude of pastshocks. Todays volatility depends on yesterdays volatility. Essentially for ARCH test, wecompute the residuals and run a regression on the residuals of past values.

How is it carried out?Estimate yt= 1 + 2xt + t and compute residuals.Estimate (hat on top) =

Look at slide 116 for more detail

What do the values suggest?

We do not reject the null as P value is greater than the significance level, thereforesuggesting that there is no heteroscedasticity with past values.

What are the remedies?

ALL YOU LOT FIGURE THIS OUT AND LET ME KNOW CANT FIND IT!

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White Test:

What does it do?

Related to the second assumption Var (Ut) =

2

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RESET Test:

What does it do?We assume that the appropriate functional form is linear and this may not be the case,

therefore the Ramsey RESET Test can formally test whether this is correct or not and isa general test for misspecification of functional form.

How is it carried out?

Essentially the method works by adding higher order terms of the fitted values intoan auxiliary regression

Regress u(hat on top)t on powers of the fitted value

Obtain R2

from this regression. The test statistic is given by TR2

and is distributedas a (p-1).

What do the values suggest?Since the P Value