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Re: st: GLS interpretation
From
bucur sorana <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: GLS interpretation
Date
Fri, 16 Sep 2011 14:48:19 +0100 (BST)
Thank you very much for your answer.
----- Original Message -----
From: Maarten Buis <[email protected]>
To: [email protected]
Cc:
Sent: Thursday, 15 September 2011, 17:04
Subject: Re: st: GLS interpretation
On Thu, Sep 15, 2011 at 3:15 PM, bucur sorana wrote:
> Can you please tell me anything about the Wald chi2(5) value and the z for income variable, because the income z is very high in comparison to the other variables?
> . xtgls growth income trade population2 school_sec2 kaopen2, panels(correlated)corr(ar1)rhotype(dw)
>
> Cross-sectional time-series FGLS regression
>
> Coefficients: generalized least squares
> Panels: heteroskedastic with cross-sectional correlation
> Correlation: common AR(1) coefficient for all panels (0.5519)
>
> Estimated covariances = 190 Number of obs = 304
> Estimated autocorrelations = 1 Number of groups = 19
> Estimated coefficients = 6 Time periods = 16
> Wald chi2(5) = 3.54e+07
> Prob > chi2 = 0.0000
>
>
> growth Coef. Std. Err. z P>z [95% Conf. Interval]
>
> income .984125 .0001666 5907.06 0.000 .9837985 .9844515
> trade .0010546 .0000313 33.68 0.000 .0009933 .001116
> population2 -1.025569 .0011646 -880.65 0.000 -1.027852 -1.023287
> school_sec2 -.0004798 .0000128 -37.55 0.000 -.0005048 -.0004547
> kaopen2 .003106 .0004466 6.96 0.000 .0022308 .0039813
> _cons .0189592 .0024439 7.76 0.000 .0141693 .0237491
"Wald chi2(5) = 3.54e+07" means 3.54*10^7, i.e. 35.4 million.
That is a lot, under the null hypothesis you expected a draw from a
chi square distribution with 5 degrees of freedom, i.e. an average
value of 5. So this is a huge deviation form what you would expect
under the null hypothesis. I don't think the z-value of income is on
its own a problem, it looks to me consistent with all your other
z-values, all of which I would normally consider suspiciously large.
However, the kind of z-values you can reasonably expect differ greatly
from problem to problem. To see what is normal for your problem I
would look for articles on similar problems and see what they find.
Hope this helps,
Maarten
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
--------------------------
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