Xtreg, fe fixed effect model - Missing F- value

[nassim ouali]

Dear statalist users,

I am new with Stata and I need your help : I ran a regression with xtreg, fe
However when I include i.year#i.industrynum (year and industry fixed effects) instead of just i.year : I don't get an F value, does it mean the model is wrong ?
Also, I was wondering if it is bad for my model to have several omitted dummy because of colinearity ?
Here is the output in Stata :

. egen industrynum = group (industry)
. egen companynum = group (company)
. xtset companynum year
panel variable: companynum (strongly balanced)
time variable: year, 2002 to 2015
delta: 1 year

. xtreg alpha esg lev cv asstln i.year#i.industrynum, fe vce(cluster companynum)
note: 2015.year#2.industrynum omitted because of collinearity
note: 2015.year#3.industrynum omitted because of collinearity
note: 2015.year#4.industrynum omitted because of collinearity
note: 2015.year#5.industrynum omitted because of collinearity
note: 2015.year#6.industrynum omitted because of collinearity
note: 2015.year#7.industrynum omitted because of collinearity
note: 2015.year#8.industrynum omitted because of collinearity
note: 2015.year#9.industrynum omitted because of collinearity
note: 2015.year#10.industrynum omitted because of collinearity

Fixed-effects (within) regression Number of obs = 9,515
Group variable: companynum Number of groups = 1,218

R-sq: Obs per group:
within = 0.5245 min = 1
between = 0.0804 avg = 7.8
overall = 0.4217 max = 14

F(131,1217) = .
corr(u_i, Xb) = -0.4203 Prob > F = .

(Std. Err. adjusted for 1,218 clusters in companynum)
------------------------------------------------------------------------------
| Robust
alpha | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
esg | .0000449 .0000225 2.00 0.046 7.66e-07 .000089
lev | -.0001189 .000055 -2.16 0.031 -.0002267 -.000011
cv | -.0000119 1.07e-06 -11.03 0.000 -.000014 -9.75e-06
asstln | -.0078213 .0011677 -6.70 0.000 -.0101122 -.0055304
|
year#|
industrynum |
2002 2 | -.0127656 .0057297 -2.23 0.026 -.0240067 -.0015245
2002 3 | -.0159944 .0051937 -3.08 0.002 -.026184 -.0058047
2002 4 | -.0212955 .0030359 -7.01 0.000 -.0272516 -.0153394
2002 5 | -.0318961 .0062033 -5.14 0.000 -.0440664 -.0197257
2002 6 | -.0103962 .0054568 -1.91 0.057 -.0211021 .0003096
2002 7 | .0317583 .0103797 3.06 0.002 .0113943 .0521223
2002 8 | -.0448218 .0074441 -6.02 0.000 -.0594265 -.0302171
2002 9 | -.0269165 .0142812 -1.88 0.060 -.054935 .001102
2002 10 | -.0374953 .0093361 -4.02 0.000 -.055812 -.0191787
2003 1 | .0045428 .0100447 0.45 0.651 -.0151642 .0242497
2003 2 | .0120816 .0057684 2.09 0.036 .0007645 .0233986
2003 3 | .0268392 .0043559 6.16 0.000 .0182933 .035385
2003 4 | .0085214 .002549 3.34 0.001 .0035204 .0135224
2003 5 | -.0004766 .0052298 -0.09 0.927 -.010737 .0097838
2003 6 | .0202892 .0047494 4.27 0.000 .0109712 .0296072
2003 7 | .0342716 .008436 4.06 0.000 .0177208 .0508224
2003 8 | .0266196 .0053798 4.95 0.000 .016065 .0371743
2003 9 | -.0144742 .0129091 -1.12 0.262 -.0398007 .0108523
2003 10 | .0159944 .0084898 1.88 0.060 -.0006618 .0326506
2004 1 | .0100962 .0085724 1.18 0.239 -.0067221 .0269145
2004 2 | .0085298 .0041708 2.05 0.041 .0003469 .0167126
2004 3 | .0108053 .004677 2.31 0.021 .0016296 .0199811
2004 4 | .0010115 .0022801 0.44 0.657 -.0034619 .0054848
2004 5 | -.0127741 .005736 -2.23 0.026 -.0240277 -.0015206
2004 6 | .0090729 .003483 2.60 0.009 .0022395 .0159063
2004 7 | .056008 .0054936 10.20 0.000 .0452301 .066786
2004 8 | -.0019224 .0050205 -0.38 0.702 -.0117723 .0079274
2004 9 | -.0099279 .0140244 -0.71 0.479 -.0374426 .0175867
2004 10 | .0091218 .0041736 2.19 0.029 .0009334 .0173101
2005 1 | -.0391968 .0099927 -3.92 0.000 -.0588015 -.019592
2005 2 | -.0199054 .0052454 -3.79 0.000 -.0301965 -.0096142
2005 3 | -.0143248 .0042645 -3.36 0.001 -.0226914 -.0059582
2005 4 | -.0076033 .002259 -3.37 0.001 -.0120353 -.0031713
2005 5 | -.0237129 .0061733 -3.84 0.000 -.0358243 -.0116015
2005 6 | -.00911 .0035544 -2.56 0.010 -.0160833 -.0021366
2005 7 | .0025636 .0060854 0.42 0.674 -.0093755 .0145027
2005 8 | -.0139762 .0049757 -2.81 0.005 -.0237381 -.0042144
2005 9 | -.052515 .0092328 -5.69 0.000 -.070629 -.0344011
2005 10 | -.0133868 .003832 -3.49 0.000 -.0209049 -.0058688
2006 1 | -.0234977 .0084292 -2.79 0.005 -.0400351 -.0069604
2006 2 | -.047726 .0068749 -6.94 0.000 -.0612141 -.034238
2006 3 | -.0402014 .0068032 -5.91 0.000 -.0535488 -.026854
2006 4 | -.0473841 .0041103 -11.53 0.000 -.0554481 -.03932
2006 5 | -.0755899 .0080353 -9.41 0.000 -.0913545 -.0598254
2006 6 | -.0372019 .0047668 -7.80 0.000 -.0465539 -.0278498
2006 7 | .0375421 .0084009 4.47 0.000 .0210602 .054024
2006 8 | -.0516832 .0057886 -8.93 0.000 -.0630399 -.0403265
2006 9 | .0025603 .0211127 0.12 0.903 -.0388611 .0439817
2006 10 | -.0183385 .0044364 -4.13 0.000 -.0270424 -.0096346
2007 1 | -.0103011 .0127575 -0.81 0.420 -.0353303 .0147281
2007 2 | -.0564883 .0071011 -7.95 0.000 -.0704201 -.0425565
2007 3 | -.053128 .0048575 -10.94 0.000 -.062658 -.043598
2007 4 | -.0715314 .0033673 -21.24 0.000 -.0781377 -.064925
2007 5 | -.0538616 .0068039 -7.92 0.000 -.0672104 -.0405129
2007 6 | -.0342822 .0051015 -6.72 0.000 -.0442909 -.0242734
2007 7 | .0533518 .009237 5.78 0.000 .0352296 .0714739
2007 8 | -.0405579 .0057707 -7.03 0.000 -.0518796 -.0292362
2007 9 | -.0456788 .0117393 -3.89 0.000 -.0687104 -.0226472
2007 10 | -.0171499 .0051104 -3.36 0.001 -.027176 -.0071238
2008 1 | -.088727 .0081837 -10.84 0.000 -.1047828 -.0726713
2008 2 | -.0588547 .0049946 -11.78 0.000 -.0686536 -.0490557
2008 3 | -.0696933 .0063985 -10.89 0.000 -.0822466 -.0571399
2008 4 | -.0713426 .0036729 -19.42 0.000 -.0785485 -.0641367
2008 5 | -.0566834 .0058157 -9.75 0.000 -.0680932 -.0452735
2008 6 | -.0643339 .0037807 -17.02 0.000 -.0717514 -.0569164
2008 7 | -.0475156 .0071282 -6.67 0.000 -.0615006 -.0335306
2008 8 | -.0786531 .0051496 -15.27 0.000 -.0887562 -.06855
2008 9 | -.0648947 .0126644 -5.12 0.000 -.0897412 -.0400483
2008 10 | -.0310453 .0043689 -7.11 0.000 -.0396167 -.0224739
2009 1 | .0488865 .0090571 5.40 0.000 .0311172 .0666558
2009 2 | .0332563 .005195 6.40 0.000 .0230642 .0434484
2009 3 | .0556784 .0053267 10.45 0.000 .0452279 .0661289
2009 4 | .0179704 .0031811 5.65 0.000 .0117293 .0242115
2009 5 | .0230069 .0060112 3.83 0.000 .0112135 .0348004
2009 6 | .0372002 .0034784 10.69 0.000 .0303758 .0440247
2009 7 | .0755507 .0057905 13.05 0.000 .0641902 .0869112
2009 8 | .0541522 .0055706 9.72 0.000 .0432232 .0650813
2009 9 | .0156067 .0164411 0.95 0.343 -.0166494 .0478627
2009 10 | .0158635 .0042142 3.76 0.000 .0075956 .0241313
2010 1 | .0205266 .0068431 3.00 0.003 .0071011 .0339521
2010 2 | .0180498 .0041193 4.38 0.000 .009968 .0261315
2010 3 | .0249884 .0033626 7.43 0.000 .0183913 .0315856
2010 4 | .0120637 .00208 5.80 0.000 .007983 .0161444
2010 5 | .002626 .0047691 0.55 0.582 -.0067305 .0119826
2010 6 | .0232283 .0033085 7.02 0.000 .0167373 .0297192
2010 7 | .0554711 .0047837 11.60 0.000 .046086 .0648563
2010 8 | .0127945 .0038825 3.30 0.001 .0051774 .0204117
2010 9 | .0085704 .0104815 0.82 0.414 -.0119934 .0291341
2010 10 | .0081319 .0039405 2.06 0.039 .000401 .0158628
2011 1 | -.0108961 .0073286 -1.49 0.137 -.0252743 .003482
2011 2 | .0012436 .0036485 0.34 0.733 -.0059145 .0084016
2011 3 | .0097557 .0030302 3.22 0.001 .0038108 .0157006
2011 4 | -.0098711 .001826 -5.41 0.000 -.0134536 -.0062886
2011 5 | -.0046446 .0051559 -0.90 0.368 -.01476 .0054708
2011 6 | .0004895 .0026715 0.18 0.855 -.0047518 .0057308
2011 7 | .0314122 .0054761 5.74 0.000 .0206686 .0421558
2011 8 | -.0089549 .003544 -2.53 0.012 -.0159079 -.0020019
2011 9 | -.0132973 .0097622 -1.36 0.173 -.0324498 .0058553
2011 10 | .0167069 .003815 4.38 0.000 .0092222 .0241917
2012 1 | .0186447 .0070392 2.65 0.008 .0048344 .0324549
2012 2 | .0196289 .0040155 4.89 0.000 .0117509 .0275069
2012 3 | .0225365 .0032321 6.97 0.000 .0161954 .0288776
2012 4 | .0186958 .0019234 9.72 0.000 .0149222 .0224693
2012 5 | .014361 .004753 3.02 0.003 .0050361 .0236859
2012 6 | .026621 .0027702 9.61 0.000 .0211861 .0320558
2012 7 | .0448544 .0048443 9.26 0.000 .0353503 .0543586
2012 8 | .0159262 .003463 4.60 0.000 .009132 .0227203
2012 9 | .0047074 .0110329 0.43 0.670 -.0169381 .0263529
2012 10 | .0103758 .0045462 2.28 0.023 .0014565 .019295
2013 1 | .02034 .009565 2.13 0.034 .0015743 .0391058
2013 2 | .0229216 .0047011 4.88 0.000 .0136985 .0321448
2013 3 | .0316453 .004068 7.78 0.000 .0236643 .0396263
2013 4 | .0099353 .0031861 3.12 0.002 .0036844 .0161861
2013 5 | .0099333 .0060991 1.63 0.104 -.0020326 .0218992
2013 6 | .0285243 .0033924 8.41 0.000 .0218688 .0351799
2013 7 | .0838776 .0093003 9.02 0.000 .0656313 .102124
2013 8 | .0189752 .0047098 4.03 0.000 .0097351 .0282154
2013 9 | .0288557 .0095273 3.03 0.003 .0101639 .0475475
2013 10 | -.0031959 .0055467 -0.58 0.565 -.0140781 .0076863
2014 1 | -.0181258 .0086122 -2.10 0.036 -.0350222 -.0012294
2014 2 | .0043579 .0031473 1.38 0.166 -.0018168 .0105326
2014 3 | .0121303 .0031814 3.81 0.000 .0058887 .0183719
2014 4 | .0066074 .0016522 4.00 0.000 .003366 .0098488
2014 5 | .0117334 .0047521 2.47 0.014 .0024101 .0210566
2014 6 | -.0001793 .0024745 -0.07 0.942 -.005034 .0046754
2014 7 | -.0045121 .005464 -0.83 0.409 -.0152321 .0062078
2014 8 | .0057465 .0036706 1.57 0.118 -.0014548 .0129479
2014 9 | -.0038645 .0116483 -0.33 0.740 -.0267175 .0189885
2014 10 | .0351099 .0034945 10.05 0.000 .028254 .0419658
2015 1 | -.0375983 .0103731 -3.62 0.000 -.0579494 -.0172471
2015 2 | 0 (omitted)
2015 3 | 0 (omitted)
2015 4 | 0 (omitted)
2015 5 | 0 (omitted)
2015 6 | 0 (omitted)
2015 7 | 0 (omitted)
2015 8 | 0 (omitted)
2015 9 | 0 (omitted)
2015 10 | 0 (omitted)
|
_cons | .1210431 .0188249 6.43 0.000 .0841101 .157976
-------------+----------------------------------------------------------------
sigma_u | .01995735
sigma_e | .03024393
rho | .30335002 (fraction of variance due to u_i)
------------------------------------------------------------------------------

. xtreg alpha esg lev cv asstln i.year, fe vce(cluster companynum)

Fixed-effects (within) regression Number of obs = 9,515
Group variable: companynum Number of groups = 1,218

R-sq: Obs per group:
within = 0.4464 min = 1
between = 0.0860 avg = 7.8
overall = 0.3757 max = 14

F(17,1217) = 319.91
corr(u_i, Xb) = -0.3641 Prob > F = 0.0000

(Std. Err. adjusted for 1,218 clusters in companynum)
------------------------------------------------------------------------------
| Robust
alpha | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
esg | .000045 .000024 1.87 0.061 -2.09e-06 .000092
lev | -.0001691 .0000651 -2.60 0.010 -.0002969 -.0000414
cv | -.0000129 6.80e-07 -18.94 0.000 -.0000142 -.0000115
asstln | -.0087708 .001223 -7.17 0.000 -.0111702 -.0063714
|
year |
2003 | .034507 .002652 13.01 0.000 .029304 .03971
2004 | .0256297 .0020629 12.42 0.000 .0215826 .0296768
2005 | .0041134 .0024578 1.67 0.094 -.0007086 .0089354
2006 | -.0202043 .0025091 -8.05 0.000 -.025127 -.0152817
2007 | -.0224241 .0027428 -8.18 0.000 -.0278053 -.0170429
2008 | -.0470288 .0025877 -18.17 0.000 -.0521057 -.0419519
2009 | .0563364 .0023679 23.79 0.000 .0516908 .060982
2010 | .0374875 .0021523 17.42 0.000 .0332649 .04171
2011 | .0190847 .0022633 8.43 0.000 .0146443 .0235251
2012 | .039946 .0022096 18.08 0.000 .035611 .044281
2013 | .043063 .0024468 17.60 0.000 .0382626 .0478635
2014 | .0239797 .0025157 9.53 0.000 .0190441 .0289153
2015 | .0170462 .002552 6.68 0.000 .0120394 .0220529
|
_cons | .1193004 .0186655 6.39 0.000 .0826801 .1559206
-------------+----------------------------------------------------------------
sigma_u | .01867957
sigma_e | .03240462
rho | .24941386 (fraction of variance due to u_i)
------------------------------------------------------------------------------

. log close
name: <unnamed>
log: F:\Question.log
log type: text
closed on: 10 Nov 2016, 17:16:32
--------------------------------------------------------------------------------

Thanks for your help and understanding

[Alfonso Sánchez-Peñalver]

My first thought is that you're trying to do too much with the interaction variable. My first question is, does a company's industry change in the time period you're observing? I doubt it. You therefore could have nested fixed effects first at the level of the industry and second at the level of the company. The problem is that if the panel variable is the company, the industry would be time invariant and thus become ineffective. Why not set the panel variable to the industry and then include the company as the factor variable. That way you capture the nested fixed effects. You can also include year as a factor variable to capture the year specific effects. I think this would work better. It's not exactly what you're trying to do with the interaction variable.

[Carlo Lazzaro]

Nassim:
as an aside to Alfonso's skillful insight, the following thread may be interesting: http://www.statalist.org/forums/foru...terpret-prob-f

[nassim ouali]

Thanks a lot Alfonso and Carlo