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Schwert’s (1989) principle, that is kmax=12(n/100)^(0.25)

where n is the sample size

Schwert, G.W. (1989). Tests for Unit-Roots: A Monte Carlo investigation. Journal of Business and Economic Statistics 7, 147-159.

hello.

Search the forum

http://forums.eviews.com/viewtopic.php? ... nger#p4031

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Hello,


There is a nice chapter for Instrumental Variables in Stock and Watson Introduction to Econometrics, 2ed.

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hi,

Read carefully the forum. See for example the following link:

http://forums.eviews.com/viewtopic.php?f=18&t=1247

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Hi,

Yes correct. We fail to reject the null hypothesis whenever the p-value is greater than the 0.05 (given that this is the selected level of significance).

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Hello,

Read carefully the manual and you will find the answer! Try to think if the critical values are of interest whenever the p-values are reported. The p-value does the job.

Hi, As you have realized there is no unique way to select the optimal lag length, therefore is quite easy to support your selection. Whenever multiple lag lengths appear two strategies can be followed: 1) Consider all the available criteria and let democracy to do the job 2) Choose one criterion (I ...

Hi, Initially run the VAR model of your interest without caring for the optimal lag structure. From the VAR window now select: view/ lag structure / Lag length criteria. A new window appears where the Lag specification is desired. Specify the maximum lag length (depending on the frequency of your da...

Hi,

I think the solution to your problem is quite easy. Simply remember the definition of the p-value and that’s it. The following paper will help you since the authors perform a similar task. (page 619)

http://journals.cambridge.org/action/di ... id=1389068

regards

Hi,

Please be more specific. Upload your file and state the desired specification.

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Hi, Correctly you have adjusted the sample, dropping just two observations and not two whole months. You do not need to change the first sample. The new message is associated to the LR statistic for selecting between univariate versus bivariate specifications. It receives a negative value something ...

Hi,

Simply re-size your estimation sample. Find within the code

sample s1 07/01/2002 07/04/2008
and replace it by:
sample s1 09/01/2002 07/04/2008


I think now it works!

Regards

Hello,

Open both the file and the code at the same work file and replace: load eex spot.wf1 with : ‘load eex spot.wf1


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Hello,

You should import your dummy variable as any other quantitative variable and then you may proceed to the estimation of the equation without any concern. (Of course if the dummy variable is the dependent one then binary models are appropriate)

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Hi,

The above Granger causality test is linear. E-views do not perform a non-linear Causality tests. I am afraid that you need to construct your own code.

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