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The Normality Test shows me if the residual VAR has a normal distribution (at 0.05). The prob. is 0.0000. What can I do in this case?

My question is why are you concerned about non-normality?

Because as I know this is one from the other tests that show me that VAR is ok. Doesn't it show us a VAR characteristic? What I want to do is to represent the impulse response function of 6 variable and I want to assure that VAR is correct represented.

Normality is of almost no importance for estimating an impulse response function. Sometimes people transform variables, for example taking logs, to get more normal residuals. But then of course you have to translate the transformed impulse response function back to the variable you actually care about.

Is there any way to solve this problem?

(1) You haven't said what the problem is. Non-normality does not invalidate a VAR.
(2) Sometimes you can take logs or make other transformations of the data to make residuals more normal.

I log data and after that I applied the first difference, but this didn't help. What other transformation should I do to test the normal distribution? This is for a project so I have to show it.

Perhaps you should ask your instructor why normality matters in this application.

After all, lots of things just aren't normal.

Hi, I have the "near singular matrix" problem in estimating panel PMG ARDL model in EViews. The strange thing is that I have no dummy variables - my dataset is annual data in a panel with 20 countries and 150 years, the variables are logs of GDP, Prices, Consumption and Money supply.

Different methods (panel VAR, panel VECM, ...) did not report this problem. Estimation was fine and in line with expectations. I cannot find where the problem is. Unfortunately I need the ARDL too.

I attach the file here.

Thank you very much if a prompt reply is possible.

Paul

You don't have enough data. Brazil, for example, only had 4 data points, which are non-consecutive. As soon as you take lags, you have no data.

Hi,

I'm trying to run LS estimation using attached data total_earnings is dependent variable and others are independent. I get estimation if I exclude IS_SPORTS, so can you please let me know what's wrong with IS_SPORTS.
All SC_* variables are scaled variables and running similar equation for SC_* variables I get Near Singular matrix error.
So kindly let me know if any other method would work for scaled variables.

Thanks,
Santosh

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EViews Gareth wrote:action+roleplaying+sports=1

Thanks Gareth

Hi, I have the "near singular matrix" problem in estimating panel Generalized Method of Moments (GMM) model in EViews. My dataset is annual data in a panel with 57firms and 10 years, the variables are logs of kar, yakit, personel, pazr, cari, kald, adh, dummy.

Different methods (Least Squares etc.) did not report this problem. Estimation was fine and in line with expectations. I cannot find where the problem is. Unfortunately I need the GMM.

I attach the file here.

Thank you very much if a prompt reply is possible.

Buket