I'm running a series of regression with industry and year fixed effect
My dependent variable is a proxy for manipulation of earnings. My key variable of interest is a dummy (quint1) that doesn't change over time and after I have a series of controls.
Since I have several proxies of manipulation of earnings I'm running multiple regression.
I'm struggling to understand why, for some of the regressions, I have this output.
Code:
reg absmoddd quintB1 aver_shareturn analysts_log logat salevolatility cashvolatility workcapit proploss delsalegrowth earn futearn ppe deltaWRC changesale cfo accr bigaud roa i.fyear i.ffind, cluster(gvkey) note: 2016.fyear omitted because of collinearity note: 2017.fyear omitted because of collinearity note: 2018.fyear omitted because of collinearity Linear regression Number of obs = 38,454 F(54, 5145) = . Prob > F = . R-squared = 0.5437 Root MSE = .08192 (Std. Err. adjusted for 5,146 clusters in gvkey) ------------------------------------------------------------------------------- | Robust absmoddd | Coef. Std. Err. t P>|t| [95% Conf. Interval] --------------+---------------------------------------------------------------- quintB1 | .0021172 .0063768 0.33 0.740 -.010384 .0146185 aver_sharet~n | 4.83e-08 4.07e-09 11.86 0.000 4.03e-08 5.63e-08 analysts_log | -.0030811 .0005967 -5.16 0.000 -.0042508 -.0019114 logat | -.0055064 .0003689 -14.93 0.000 -.0062296 -.0047832 salevolatil~y | 1.110494 . . . . . cashvolatil~y | 2.592445 . . . . . workcapit | .6596937 . . . . . proploss | -3.900873 . . . . . delsalegrowth | .0014231 .0008765 1.62 0.105 -.0002953 .0031414 earn | -.2315857 .0174807 -13.25 0.000 -.2658552 -.1973161 futearn | -.0102936 .0073057 -1.41 0.159 -.0246158 .0040287 ppe | -.0255437 .0037311 -6.85 0.000 -.0328583 -.0182291 deltaWRC | .1210259 .1170141 1.03 0.301 -.1083714 .3504233 changesale | .0291029 .0031282 9.30 0.000 .0229703 .0352355 cfo | .1973238 .0143676 13.73 0.000 .1691573 .2254903 accr | .8036271 .2924855 2.75 0.006 .2302311 1.377023 bigaud | -.182379 . . . . . roa | -.0468239 .0108017 -4.33 0.000 -.0679998 -.0256479 | fyear | 2002 | .0684815 . . . . . 2003 | .0275448 . . . . . 2004 | -.0781455 . . . . . 2005 | -.1743677 . . . . . 2006 | -.3005914 . . . . . 2007 | -.3505113 . . . . . 2008 | -.2788789 . . . . . 2009 | -.1475632 . . . . . 2010 | -.0795899 . . . . . 2011 | -.0488357 . . . . . 2012 | -.0239605 . . . . . 2013 | -.0673017 . . . . . 2014 | -.136407 . . . . . 2015 | -.0694582 . . . . . 2016 | 0 (omitted) 2017 | 0 (omitted) 2018 | 0 (omitted) | ffind | 2 | .0165133 .0038744 4.26 0.000 .0089178 .0241088 3 | .0061173 .0060999 1.00 0.316 -.005841 .0180757 4 | .0137559 .0068625 2.00 0.045 .0003026 .0272092 6 | .0261899 .0050341 5.20 0.000 .016321 .0360588 7 | .0271067 .0040535 6.69 0.000 .0191601 .0350534 8 | .0307849 .0091985 3.35 0.001 .012752 .0488178 9 | .0121585 .0038337 3.17 0.002 .0046428 .0196742 10 | .0129211 .0041018 3.15 0.002 .0048799 .0209624 11 | .0387873 .0049461 7.84 0.000 .0290907 .0484838 12 | .0333732 .0042868 7.79 0.000 .0249692 .0417772 13 | .0778667 .0053883 14.45 0.000 .0673034 .0884301 14 | .0248361 .007387 3.36 0.001 .0103544 .0393177 15 | .0124818 .0077165 1.62 0.106 -.0026458 .0276094 16 | .0252366 .0113663 2.22 0.026 .0029538 .0475195 17 | .0180586 .0073686 2.45 0.014 .0036129 .0325043 18 | .0174014 .0080347 2.17 0.030 .00165 .0331528 19 | .0161763 .0074397 2.17 0.030 .0015914 .0307612 20 | -.0102544 .0102338 -1.00 0.316 -.030317 .0098081 21 | .0195901 .0073257 2.67 0.008 .0052287 .0339515 22 | .0173262 .0078094 2.22 0.027 .0020165 .0326359 23 | .021891 .0074394 2.94 0.003 .0073066 .0364754 24 | .0132493 .00759 1.75 0.081 -.0016303 .0281289 25 | .0011462 .0076273 0.15 0.881 -.0138066 .016099 26 | .0048563 .0175949 0.28 0.783 -.0296372 .0393498 27 | .0379749 .0078397 4.84 0.000 .0226057 .053344 28 | .0451368 .0079863 5.65 0.000 .0294803 .0607933 29 | .0075163 .0079214 0.95 0.343 -.0080129 .0230455 30 | .0469983 .0075624 6.21 0.000 .0321727 .0618239 33 | .0141865 .0074641 1.90 0.057 -.0004464 .0288194 34 | .0422195 .0072676 5.81 0.000 .0279718 .0564671 35 | .0408326 .0075694 5.39 0.000 .0259933 .0556719 36 | .0478678 .0073668 6.50 0.000 .0334258 .0623099 37 | .0174294 .007406 2.35 0.019 .0029105 .0319483 38 | .0110031 .0074203 1.48 0.138 -.0035438 .0255501 39 | .0037448 .0075109 0.50 0.618 -.0109796 .0184693 40 | .0172039 .0082013 2.10 0.036 .0011259 .033282 41 | .0172645 .00734 2.35 0.019 .002875 .031654 42 | .0130322 .0072594 1.80 0.073 -.0011993 .0272637 43 | .0102852 .0077753 1.32 0.186 -.0049577 .0255281 46 | .0520101 .0101473 5.13 0.000 .0321171 .071903 47 | .0435883 .0092769 4.70 0.000 .0254015 .061775 -------------------------------------------------------------------------------
But why do I have a series of dots between year dummies 2002 and 2015 for the columns of std error, p statistcs etc.?
The same problem happens also for three controls (cashvolatility, salesvolatility, proprloss)
Do you have any suggestions?
Thanks
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