Hi all,
Hopefully someone can help me figure this out. I am running a panel regression with random effects due to a dummy variable moderator (0 or 1). However, to assess the model fit for my regression I am trying to find the Adjusted R-squared. On a different log I read that you can use the display "adjusted R2 =" e(r2_a) command. When I run this, I get adjusted R2 =. - from what I understand this means that my R2 cannot be calculated. Can anyone figure out what causing this? I'll paste the output here:
. xtreg relROA L1.c.distinctiveness##L1.c.distinctiveness i..industry L.c.firmsize c.age c.orgaslack, re vce(robust)
Random-effects GLS regression Number of obs = 4,478
Group variable: comp Number of groups = 773
R-squared: Obs per group:
Within = 0.0141 min = 1
Between = 0.0017 avg = 5.8
Overall = 0.0004 max = 28
Wald chi2(26) = 95.35
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
(Std. err. adjusted for 773 clusters in comp)
-------------------------------------------------------------------------------------------------------
| Robust
relROA | Coefficient std. err. z P>|z| [95% conf. interval]
--------------------------------------+----------------------------------------------------------------
distinctiveness |
L1. | .0012422 .0012418 1.00 0.317 -.0011917 .0036762
|
cL.distinctiveness#cL.distinctiveness | -.0001762 .0000861 -2.05 0.041 -.0003448 -7.50e-06
|
industry |
312221 | .0299084 .0196738 1.52 0.128 -.0086515 .0684683
312230 | .0655258 .04593 1.43 0.154 -.0244954 .155547
325180 | .0782712 .0504928 1.55 0.121 -.0206929 .1772352
325211 | .0343295 .0193113 1.78 0.075 -.00352 .0721789
3253 | .0414234 .0198629 2.09 0.037 .0024928 .080354
325320 | .0463667 .0227546 2.04 0.042 .0017685 .0909649
325613 | .0445484 .0215069 2.07 0.038 .0023957 .0867011
325998 | .0085806 .0370069 0.23 0.817 -.0639516 .0811127
332994 | .0389192 .0197072 1.97 0.048 .0002938 .0775446
336992 | .0327879 .0236444 1.39 0.166 -.0135543 .0791301
424940 | .0544769 .0254782 2.14 0.033 .0045405 .1044134
7132 | .0662448 .02703 2.45 0.014 .013267 .1192227
713290 | .0116132 .0197492 0.59 0.557 -.0270945 .0503209
722211 | -.2074768 .2281428 -0.91 0.363 -.6546284 .2396749
722513 | .0402662 .0201712 2.00 0.046 .0007315 .0798009
19 | -.0042073 .0251653 -0.17 0.867 -.0535303 .0451158
20 | -.0087678 .0417463 -0.21 0.834 -.0905891 .0730535
21 | -.016968 .0448973 -0.38 0.705 -.1049652 .0710292
22 | .0287678 .022271 1.29 0.196 -.0148826 .0724183
25 | -.0084245 .0438825 -0.19 0.848 -.0944326 .0775835
26 | -.0036282 .0480767 -0.08 0.940 -.0978569 .0906004
|
firmsize |
L1. | -.0032258 .0009794 -3.29 0.001 -.0051455 -.0013062
|
age | -.0024088 .0021972 -1.10 0.273 -.0067151 .0018976
orgaslack | 9.24e-08 2.61e-08 3.54 0.000 4.12e-08 1.44e-07
_cons | .016506 .0478726 0.34 0.730 -.0773227 .1103346
--------------------------------------+----------------------------------------------------------------
sigma_u | 2.7467005
sigma_e | .02738524
rho | .9999006 (fraction of variance due to u_i)
-------------------------------------------------------------------------------------------------------
. display "adjusted R2 =" e(r2_a)
adjusted R2 =.
However, when I run a fixed effects model, it does calculate the adjusted R2 (=0.1326381). If anyone understands the problem, please let me know!
Hopefully someone can help me figure this out. I am running a panel regression with random effects due to a dummy variable moderator (0 or 1). However, to assess the model fit for my regression I am trying to find the Adjusted R-squared. On a different log I read that you can use the display "adjusted R2 =" e(r2_a) command. When I run this, I get adjusted R2 =. - from what I understand this means that my R2 cannot be calculated. Can anyone figure out what causing this? I'll paste the output here:
. xtreg relROA L1.c.distinctiveness##L1.c.distinctiveness i..industry L.c.firmsize c.age c.orgaslack, re vce(robust)
Random-effects GLS regression Number of obs = 4,478
Group variable: comp Number of groups = 773
R-squared: Obs per group:
Within = 0.0141 min = 1
Between = 0.0017 avg = 5.8
Overall = 0.0004 max = 28
Wald chi2(26) = 95.35
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
(Std. err. adjusted for 773 clusters in comp)
-------------------------------------------------------------------------------------------------------
| Robust
relROA | Coefficient std. err. z P>|z| [95% conf. interval]
--------------------------------------+----------------------------------------------------------------
distinctiveness |
L1. | .0012422 .0012418 1.00 0.317 -.0011917 .0036762
|
cL.distinctiveness#cL.distinctiveness | -.0001762 .0000861 -2.05 0.041 -.0003448 -7.50e-06
|
industry |
312221 | .0299084 .0196738 1.52 0.128 -.0086515 .0684683
312230 | .0655258 .04593 1.43 0.154 -.0244954 .155547
325180 | .0782712 .0504928 1.55 0.121 -.0206929 .1772352
325211 | .0343295 .0193113 1.78 0.075 -.00352 .0721789
3253 | .0414234 .0198629 2.09 0.037 .0024928 .080354
325320 | .0463667 .0227546 2.04 0.042 .0017685 .0909649
325613 | .0445484 .0215069 2.07 0.038 .0023957 .0867011
325998 | .0085806 .0370069 0.23 0.817 -.0639516 .0811127
332994 | .0389192 .0197072 1.97 0.048 .0002938 .0775446
336992 | .0327879 .0236444 1.39 0.166 -.0135543 .0791301
424940 | .0544769 .0254782 2.14 0.033 .0045405 .1044134
7132 | .0662448 .02703 2.45 0.014 .013267 .1192227
713290 | .0116132 .0197492 0.59 0.557 -.0270945 .0503209
722211 | -.2074768 .2281428 -0.91 0.363 -.6546284 .2396749
722513 | .0402662 .0201712 2.00 0.046 .0007315 .0798009
19 | -.0042073 .0251653 -0.17 0.867 -.0535303 .0451158
20 | -.0087678 .0417463 -0.21 0.834 -.0905891 .0730535
21 | -.016968 .0448973 -0.38 0.705 -.1049652 .0710292
22 | .0287678 .022271 1.29 0.196 -.0148826 .0724183
25 | -.0084245 .0438825 -0.19 0.848 -.0944326 .0775835
26 | -.0036282 .0480767 -0.08 0.940 -.0978569 .0906004
|
firmsize |
L1. | -.0032258 .0009794 -3.29 0.001 -.0051455 -.0013062
|
age | -.0024088 .0021972 -1.10 0.273 -.0067151 .0018976
orgaslack | 9.24e-08 2.61e-08 3.54 0.000 4.12e-08 1.44e-07
_cons | .016506 .0478726 0.34 0.730 -.0773227 .1103346
--------------------------------------+----------------------------------------------------------------
sigma_u | 2.7467005
sigma_e | .02738524
rho | .9999006 (fraction of variance due to u_i)
-------------------------------------------------------------------------------------------------------
. display "adjusted R2 =" e(r2_a)
adjusted R2 =.
However, when I run a fixed effects model, it does calculate the adjusted R2 (=0.1326381). If anyone understands the problem, please let me know!
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