F Value and ajdusted R2 are missing

[Shyar Alen]

Could someone help me how i can get the F value and adjusted R Square after running a regression with robust clustering because they are missing in the output?

Thanks

[Andrew Musau]

Show us your exact regression command and the resulting output (see FAQ Advice #12 for details).

[Carlo Lazzaro]

Shyar:
welcome to this forum.
As an aside to Andrew's wise advice (that I do share), are you experiencing something like the following toy-example?

. use "C:\Program Files\Stata17\ado\base\a\auto.dta"
(1978 automobile data)

. regress price i.foreign, vce(cluster foreign)

Linear regression                               Number of obs     =         74
                                                F(0, 1)           =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0024
                                                Root MSE          =     2966.4

                                (Std. err. adjusted for 2 clusters in foreign)
------------------------------------------------------------------------------
             |               Robust
       price | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------+----------------------------------------------------------------
     foreign |
    Foreign  |   312.2587   1.28e-12  2.4e+14   0.000     312.2587    312.2587
       _cons |   6072.423   9.22e-13  6.6e+15   0.000     6072.423    6072.423
------------------------------------------------------------------------------

. 

See -help j_robustsingular-.

[Shyar Alen]

Thank you,exactly like this, here is my output with the command:

reg wlev unrated wtan wprof wmb ln_at ln_age i.fyear i.sic2, robust cluster(firmid)

Linear regression Number of obs = 639
F(46, 216) = .
Prob > F = .
R-squared = 0.4004
Root MSE = .17579

(Std. Err. adjusted for 217 clusters in firmid)
------------------------------------------------------------------------------
| Robust
wlev | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
unrated | -.0430187 .0185494 -2.32 0.021 -.0795797 -.0064578
wtan | .4078659 .0742174 5.50 0.000 .2615828 .554149
wprof | .0529737 .0300169 1.76 0.079 -.0061899 .1121373
wmb | -.0095561 .0046449 -2.06 0.041 -.0187112 -.000401
ln_at | .0088401 .0080668 1.10 0.274 -.0070596 .0247398
ln_age | -.1384733 .0955145 -1.45 0.149 -.3267331 .0497866
|
fyear |
2006 | .0737333 .0385688 1.91 0.057 -.002286 .1497526
2007 | .121934 .0464968 2.62 0.009 .0302883 .2135796
2008 | .0669079 .041587 1.61 0.109 -.0150605 .1488762
2009 | .0586276 .050501 1.16 0.247 -.0409101 .1581654
2010 | .0386035 .0471424 0.82 0.414 -.0543146 .1315215
2011 | .0629974 .0462657 1.36 0.175 -.0281927 .1541874
2012 | .0168702 .0456438 0.37 0.712 -.0730942 .1068345
2013 | .0197136 .0478374 0.41 0.681 -.0745742 .1140014
2014 | .0224715 .0550105 0.41 0.683 -.0859546 .1308976
2015 | -.0169337 .0532036 -0.32 0.751 -.1217984 .0879309
2016 | .0052202 .0641365 0.08 0.935 -.1211934 .1316338
2017 | .1494202 .2781899 0.54 0.592 -.3988941 .6977346
|
sic2 |
13 | .4260332 .0274769 15.51 0.000 .371876 .4801903
16 | .2959219 .0363972 8.13 0.000 .2241827 .367661
20 | .4344486 .0803927 5.40 0.000 .2759941 .5929031
22 | .4975663 .0840868 5.92 0.000 .3318305 .663302
25 | .4945587 .0497673 9.94 0.000 .396467 .5926504
26 | .2834483 .0784457 3.61 0.000 .1288313 .4380654
27 | .4536232 .0596915 7.60 0.000 .3359708 .5712756
28 | .4204435 .0657729 6.39 0.000 .2908046 .5500824
30 | .4974619 .0724177 6.87 0.000 .3547262 .6401976
32 | .4917271 .1564144 3.14 0.002 .1834331 .8000212
33 | .3592616 .0907852 3.96 0.000 .1803233 .5381999
34 | .4212081 .0744262 5.66 0.000 .2745135 .5679027
35 | .4223152 .0591657 7.14 0.000 .3056991 .5389313
36 | .4579435 .0572655 8.00 0.000 .3450728 .5708142
37 | .3822447 .0460778 8.30 0.000 .291425 .4730643
38 | .4806078 .0625903 7.68 0.000 .3572418 .6039738
42 | .469578 .0468144 10.03 0.000 .3773065 .5618495
45 | .500954 .0320499 15.63 0.000 .4377834 .5641246
48 | .5038276 .1198938 4.20 0.000 .2675161 .7401391
49 | .4585376 .0509937 8.99 0.000 .3580287 .5590466
50 | .5444845 .0599696 9.08 0.000 .426284 .6626849
51 | .7840936 .1436307 5.46 0.000 .5009963 1.067191
52 | .3835603 .0826416 4.64 0.000 .2206732 .5464475
53 | .6351976 .0488399 13.01 0.000 .5389337 .7314615
54 | .4690165 .0981627 4.78 0.000 .2755372 .6624959
55 | .5846759 .076382 7.65 0.000 .4341266 .7352253
56 | .3224043 .0490453 6.57 0.000 .2257357 .4190728
57 | .3249427 .0485295 6.70 0.000 .2292907 .4205946
58 | .3168368 .0500156 6.33 0.000 .2182557 .415418
59 | .4654041 .0751167 6.20 0.000 .3173485 .6134597
70 | .4295174 .0593466 7.24 0.000 .3125448 .5464901
73 | .4937743 .0669841 7.37 0.000 .3617481 .6258006
75 | .753608 .029789 25.30 0.000 .6948936 .8123225
78 | .4288632 .0667882 6.42 0.000 .2972231 .5605033
79 | .4305112 .0457718 9.41 0.000 .3402947 .5207278
80 | .513573 .0581239 8.84 0.000 .3990103 .6281356
81 | .4361687 .0655893 6.65 0.000 .3068917 .5654457
82 | .3240345 .0860312 3.77 0.000 .1544663 .4936026
83 | .7216773 .0414541 17.41 0.000 .6399709 .8033837
87 | .3795342 .0580462 6.54 0.000 .2651246 .4939437
99 | .6206127 .047087 13.18 0.000 .5278038 .7134216
|
_cons | .0326404 .2925719 0.11 0.911 -.5440211 .6093019
------------------------------------------------------------------------------

[Carlo Lazzaro]

Shyar:
why bothering yourself with a pooled OLS when you can go -xtreg,fe-?