My total dataset contains 7 regions. The estimation results for the 7
regions are fine. All R square are positive, all LR chi() are
positive, and all degree of freedom are right.
2. I choose the last 4 regions of the total 7regions and create a new
data set(changed the dummy variables).
Here, all the R square are positive, all LR chi() are positive. But
the degree of freedom are strange.
4 regions Unrestricted
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Equation Obs Parms RMSE "R-sq" chi2 P
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lnc 72 40 .0987079 0.9693 7.62e+07 0.0000
sl 72 8 .0230819 0.3033 417.70 0.0000
se 72 8 .0023162 0.9399 1246.72 0.0000
sm 72 8 .0292372 0.5744 1094.54 0.0000
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_cons in equation lnc are dropped, no other variable droped
4 regions Restricted
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Equation Obs Parms RMSE "R-sq" chi2 P
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lnc 72 37 .0930231 0.9727 1.47e+07 0.0000
sl 72 7 .0195899 0.4982 347.11 0.0000
se 72 7 .0022661 0.9425 1275.65 0.0000
sm 72 7 .0270912 0.6346 1003.91 0.0000
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No _cons dropped, no variable dropped
Likelihood-ratio test LR chi2(2)
= 6.71
(Assumption: B nested in A) Prob > chi2
= 0.0350
I am thinking if the degree of freedom changed from 3 to 2 because of
_cons in unrestricted model is dropped, but kept in restricted model?
3. I chose the first 3 regions and created them as a new dataset
(changed the dummy variables). When I estimated equations lnc, sl, sm,
se, there are two negative R square values. So I changed them to ln,
sl, sk, se and got one negative R-sq this time. LR chi() here are
negative.
