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| From | bucur sorana <sorana_bucur2003@yahoo.co.uk> |
| To | "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |
| 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 <maartenlbuis@gmail.com> To: statalist@hsphsun2.harvard.edu 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 -------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/