## Search found 3326 matches

Wed Jul 18, 2018 8:29 am
Forum: Estimation
Topic: Panel VAR EViews 9
Replies: 8
Views: 263

### Re: Panel VAR EViews 9

Is it possible do do some of this by manually writing out the VAR as a standard regression?
Tue Jul 17, 2018 5:57 am
Forum: Estimation
Topic: Insufficient observations
Replies: 3
Views: 61

### Re: Insufficient observations

EViews starts estimation with whatever is stored in the c vector. In your case, this is causing some division by zero. Try saying

Code: Select all

`c = 1`
before you start the estimation.
Mon Jul 16, 2018 9:10 am
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

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

After all, lots of things just aren't normal.
Mon Jul 16, 2018 8:48 am
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

(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.
Mon Jul 16, 2018 7:35 am
Forum: Econometric Discussions
Topic: Interpretation of the Breusch Pagan Godfrey test for heteroskedasticity
Replies: 1
Views: 37

### Re: Interpretation of the Breusch Pagan Godfrey test for heteroskedasticity

You are interpreting p-values backwards. A low p-value means reject the null.
Sun Jul 15, 2018 12:31 pm
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

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 abo...
Sun Jul 15, 2018 8:09 am
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

My question is why are you concerned about non-normality?
Sun Jul 15, 2018 6:13 am
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

What do you think the problem is?
Sun Jul 15, 2018 6:12 am
Forum: Data Manipulation
Topic: Correlation
Replies: 2
Views: 53

### Re: Correlation

Look at the function

Code: Select all

`@movcor(x,y,n)`
Sat Jul 14, 2018 10:45 am
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

No, the VAR is fine with highly correlated variables.
Sat Jul 14, 2018 10:15 am
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

Perhaps run with one lag and run with two and see if it makes any difference. The real issue is that only having 20 observations limits what you can do.
Sat Jul 14, 2018 9:24 am
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

This probably suggests adding one more lag to the VAR. But you have very few observations, so it's not entirely obvious whether you should.
Sat Jul 14, 2018 8:37 am
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

The article is just wrong.

A VAR is just a collection of least squares regressions. Normality and heteroskedasticity matter for coefficient tests, but usually no one is interested in doing those for a VAR. Autocorrelation does matter-it's usually handled by adding lags to the VAR.
Sat Jul 14, 2018 8:16 am
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

I would just proceed without the test.

And why do you want to test for heteroskedasticity anyway?
Sat Jul 14, 2018 7:58 am
Forum: Estimation
Topic: Near Singular Matrix Error
Replies: 37
Views: 29164

### Re: Near Singular Matrix Error

Even if there is heteroskedasticity, the estimated equations should be unbiased. What would you differently if you found there is heteroskedasticity?