I have run a regression of cash flow volatility (s_oina_v1_w01) on several independent variables. The coefficients of the independent variables are much greater than 1. After a while searching for the reasons, this issue might be caused by multicollinearity. I use vif command to check and found that if I exclude year fixed effect, the vif will decrease to normal. However, the betas of independent variables are still greater than 1. The question is: can betas be greater than 1 or they should be bounded between 0 and 1?
My first model including year fixed effects
Code:
reg s_oina_v1_w01 vc pe $CONTROLSF i.fyear if nomiss==1, cluster (gvkey_n)
Linear regression Number of obs = 42,240
F(64, 5187) = 55.64
Prob > F = 0.0000
R-squared = 0.3537
Root MSE = 23.421
(Std. Err. adjusted for 5,188 clusters in gvkey_n)
Robust
s_oina_v1~01 Coef. Std. Err. t P>t [95% Conf. Interval]
vc 2.60776 .5108771 5.10 0.000 1.606225 3.609294
pe -.431211 .4109789 -1.05 0.294 -1.236903 .3744809
MB2_w01 2.588564 .1564188 16.55 0.000 2.281917 2.89521
fsize_w01 -2.044109 .13061 -15.65 0.000 -2.300159 -1.788058
tang_w01 -4.856372 .6371705 -7.62 0.000 -6.105495 -3.60725
prof2_w01 -23.1196 1.482164 -15.60 0.000 -26.02527 -20.21394
LnRnD_w01 22.105 1.338913 16.51 0.000 19.48017 24.72984
capex_w01 15.53585 2.653995 5.85 0.000 10.3329 20.7388
abne_w01 1.614974 .6722279 2.40 0.016 .2971238 2.932824
indlev_w01 -4.6235 .6954019 -6.65 0.000 -5.986781 -3.260219
fyear
1963 -2.70082 1.855219 -1.46 0.146 -6.337831 .9361915
1964 -4.36412 2.44979 -1.78 0.075 -9.166741 .4385007
1965 -3.483502 2.541331 -1.37 0.171 -8.465583 1.498578
1966 -2.861024 2.190433 -1.31 0.192 -7.155195 1.433147
1967 -3.777086 2.748357 -1.37 0.169 -9.165025 1.610852
1968 -1.183331 3.818591 -0.31 0.757 -8.669378 6.302716
1969 -4.279388 2.535129 -1.69 0.091 -9.24931 .6905337
1970 -2.396924 1.959319 -1.22 0.221 -6.238015 1.444168
1971 -5.224563 2.179666 -2.40 0.017 -9.497626 -.9515
1972 -5.423982 2.626562 -2.07 0.039 -10.57315 -.2748138
1973 -3.160456 2.739316 -1.15 0.249 -8.530669 2.209758
1974 -1.109184 2.648728 -0.42 0.675 -6.301808 4.083439
1975 -1.772796 2.62446 -0.68 0.499 -6.917842 3.372251
1976 -1.968919 2.604779 -0.76 0.450 -7.075383 3.137546
1977 -3.536893 2.602726 -1.36 0.174 -8.639332 1.565547
1978 -3.240465 2.626672 -1.23 0.217 -8.389849 1.90892
1979 -3.14485 2.587022 -1.22 0.224 -8.216504 1.926803
1980 -3.663743 2.586793 -1.42 0.157 -8.734947 1.407461
1981 -4.014471 2.67717 -1.50 0.134 -9.262852 1.23391
1982 -4.120776 2.651059 -1.55 0.120 -9.317968 1.076416
1983 -5.077192 2.616589 -1.94 0.052 -10.20681 .0524262
1984 -1.935351 2.664314 -0.73 0.468 -7.158529 3.287827
1985 -2.99127 2.628142 -1.14 0.255 -8.143537 2.160997
1986 -1.640733 2.643156 -0.62 0.535 -6.822432 3.540965
1987 -1.961486 2.624165 -0.75 0.455 -7.105956 3.182984
1988 -2.4146 2.619251 -0.92 0.357 -7.549435 2.720235
1989 -2.59247 2.617404 -0.99 0.322 -7.723685 2.538745
1990 -1.634035 2.621029 -0.62 0.533 -6.772357 3.504287
1991 -2.309193 2.621048 -0.88 0.378 -7.447551 2.829166
1992 -2.145213 2.631998 -0.82 0.415 -7.305038 3.014611
1993 -4.298855 2.602566 -1.65 0.099 -9.400981 .8032715
1994 -3.740801 2.596153 -1.44 0.150 -8.830355 1.348752
1995 -2.85765 2.593843 -1.10 0.271 -7.942675 2.227376
1996 -2.550483 2.595195 -0.98 0.326 -7.638159 2.537193
1997 -2.886435 2.598277 -1.11 0.267 -7.980153 2.207284
1998 -.6481403 2.612095 -0.25 0.804 -5.768947 4.472667
1999 -1.143714 2.627518 -0.44 0.663 -6.294757 4.007328
2000 2.853986 2.648816 1.08 0.281 -2.33881 8.046782
2001 1.088894 2.631785 0.41 0.679 -4.070513 6.248301
2002 .4298029 2.626765 0.16 0.870 -4.719764 5.57937
2003 -3.096295 2.617106 -1.18 0.237 -8.226926 2.034336
2004 -1.838908 2.626983 -0.70 0.484 -6.988901 3.311085
2005 -2.909433 2.629826 -1.11 0.269 -8.065 2.246134
2006 -1.747426 2.633339 -0.66 0.507 -6.90988 3.415028
2007 -2.096727 2.643802 -0.79 0.428 -7.279694 3.086239
2008 1.854633 2.66005 0.70 0.486 -3.360186 7.069451
2009 2.525076 2.653766 0.95 0.341 -2.677423 7.727576
2010 2.350179 2.672366 0.88 0.379 -2.888786 7.589143
2011 1.023631 2.682469 0.38 0.703 -4.235139 6.282401
2012 .217227 2.656954 0.08 0.935 -4.991522 5.425976
2013 -3.136067 2.644907 -1.19 0.236 -8.321199 2.049064
2014 -.691762 2.678946 -0.26 0.796 -5.943625 4.560101
2015 .3019233 2.697211 0.11 0.911 -4.985747 5.589594
2016 .1598025 2.719114 0.06 0.953 -5.170807 5.490412
_cons 24.0461 2.597978 9.26 0.000 18.95297 29.13923Code:
. vif
Variable VIF 1/VIF
vc 1.34 0.746548
pe 1.17 0.856759
MB2_w01 1.27 0.787382
fsize_w01 1.79 0.557760
tang_w01 1.46 0.683080
prof2_w01 2.01 0.497613
LnRnD_w01 1.82 0.548491
capex_w01 1.45 0.691691
abne_w01 1.07 0.930430
indlev_w01 1.65 0.606256
fyear
1963 2.11 0.473790
1964 2.33 0.428682
1965 2.89 0.346256
1966 3.33 0.300107
1967 4.11 0.243356
1968 4.22 0.236961
1969 4.55 0.219642
1970 5.00 0.200127
1971 5.44 0.183805
1972 6.55 0.152660
1973 22.83 0.043792
1974 33.10 0.030214
1975 34.71 0.028808
1976 34.05 0.029371
1977 35.25 0.028365
1978 34.82 0.028723
1979 36.90 0.027101
1980 38.31 0.026101
1981 41.38 0.024169
1982 52.71 0.018970
1983 57.15 0.017497
1984 77.92 0.012834
1985 85.74 0.011663
1986 90.22 0.011083
1987 103.02 0.009707
1988 110.87 0.009020
1989 105.88 0.009445
1990 103.77 0.009637
1991 101.83 0.009821
1992 108.93 0.009180
1993 127.18 0.007863
1994 143.60 0.006964
1995 156.90 0.006373
1996 172.69 0.005791
1997 191.50 0.005222
1998 187.52 0.005333
1999 172.17 0.005808
2000 168.06 0.005950
2001 166.50 0.006006
2002 154.39 0.006477
2003 140.76 0.007104
2004 132.61 0.007541
2005 130.84 0.007643
2006 126.53 0.007903
2007 122.74 0.008147
2008 118.64 0.008429
2009 111.12 0.008999
2010 106.88 0.009356
2011 105.61 0.009469
2012 104.55 0.009565
2013 103.71 0.009643
2014 108.16 0.009246
2015 110.81 0.009025
2016 109.64 0.009120
Mean VIF 72.47Code:
reg s_oina_v1_w01 vc pe $CONTROLSF if nomiss==1, cluster(gvkey_n) Linear regression Number of obs = 42,240 F(10, 5187) = 326.72 Prob > F = 0.0000 R-squared = 0.3497 Root MSE = 23.479 (Std. Err. adjusted for 5,188 clusters in gvkey_n) Robust s_oina_v1~01 Coef. Std. Err. t P>t [95% Conf. Interval] vc 2.786415 .5083468 5.48 0.000 1.789841 3.782989 pe -.4794882 .399109 -1.20 0.230 -1.26191 .3029337 MB2_w01 2.578851 .1551001 16.63 0.000 2.274789 2.882912 fsize_w01 -1.711538 .1023789 -16.72 0.000 -1.912244 -1.510832 tang_w01 -4.678255 .6267758 -7.46 0.000 -5.907 -3.44951 prof2_w01 -24.49453 1.459964 -16.78 0.000 -27.35667 -21.63238 LnRnD_w01 22.10426 1.336092 16.54 0.000 19.48495 24.72356 capex_w01 11.85221 2.584446 4.59 0.000 6.785603 16.91881 abne_w01 1.551582 .6725154 2.31 0.021 .2331683 2.869995 indlev_w01 -4.388744 .61205 -7.17 0.000 -5.58862 -3.188868 _cons 21.09565 .791491 26.65 0.000 19.544 22.64731
Code:
Variable VIF 1/VIF
prof2_w01 1.88 0.531979
LnRnD_w01 1.80 0.554424
tang_w01 1.42 0.704543
indlev_w01 1.35 0.738034
vc 1.33 0.751402
capex_w01 1.33 0.752730
MB2_w01 1.25 0.799959
fsize_w01 1.23 0.815327
pe 1.15 0.868929
abne_w01 1.07 0.937740
Mean VIF 1.38Regards,
Huyen
0 Response to Betas greater than one
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