I am looking for advice on my model, analyzing if high ceo pay ratios have an impact on a companies esg-rating. Below you can see the outcome of the specification, indicating that both the pay ratio (lncprw) and the market cap (lncapw) do influence the esg ratings. As a robustness test, i now split the companies along the median, grouping them into big market cap and small market cap categories (large cap =1), and interacted this variable with the ceo pay ratio (second output).
Am i correct with my interpretation of the insignificant interaction term, that ceo pay ratio only affects the esg-rating of small cap companies? Or is this form of robustness check not making sense? I greatly appreciate any form of help or push in the right direction.
. asdoc xtreg lnesg lncprw lndebtw roaw lncapw i.year i.industry
Random-effects GLS regression Number of obs = 378
Group variable: id Number of groups = 72
R-squared: Obs per group:
Within = 0.3450 min = 1
Between = 0.2702 avg = 5.2
Overall = 0.3786 max = 6
Wald chi2(14) = 180.33
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
------------------------------------------------------------------------------
lnesg | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
lncprw | .0326537 .0160507 2.03 0.042 .0011949 .0641126
lndebtw | .0198029 .0115212 1.72 0.086 -.0027782 .0423841
roaw | -.0012461 .0022023 -0.57 0.572 -.0055624 .0030703
lncapw | .1039689 .0202222 5.14 0.000 .064334 .1436037
|
year |
2 | .0075412 .0291055 0.26 0.796 -.0495046 .064587
3 | .1173459 .0286406 4.10 0.000 .0612114 .1734804
4 | .137357 .028574 4.81 0.000 .0813529 .193361
5 | .2003007 .0292682 6.84 0.000 .142936 .2576654
6 | .2318731 .0287288 8.07 0.000 .1755656 .2881805
|
industry |
2 | -.2258393 .1233899 -1.83 0.067 -.4676792 .0160006
3 | -.2486235 .1410259 -1.76 0.078 -.5250291 .0277821
4 | .0804007 .1718355 0.47 0.640 -.2563907 .4171921
5 | -.1236049 .1198287 -1.03 0.302 -.3584648 .111255
6 | -.0007003 .1410232 -0.00 0.996 -.2771007 .2757001
|
_cons | 2.215179 .3151133 7.03 0.000 1.597568 2.832789
-------------+----------------------------------------------------------------
sigma_u | .21701252
sigma_e | .14300232
rho | .69723982 (fraction of variance due to u_i)
------------------------------------------------------------------------------
. xtreg lnscope lncsrstrat lnesg c.lncprw#i.largecap lndebtw roaw i.year i.industry re
Random-effects GLS regression Number of obs = 371
Group variable: id Number of groups = 70
R-squared: Obs per group:
Within = 0.0732 min = 1
Between = 0.0910 avg = 5.3
Overall = 0.0987 max = 6
Wald chi2(17) = 28.85
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0359
-----------------------------------------------------------------------------------
lnscope | Coefficient Std. err. z P>|z| [95% conf. interval]
------------------+----------------------------------------------------------------
lncsrstrat | .1438839 .0728789 1.97 0.048 .0010439 .286724
lnesg | -.3894373 .1686043 -2.31 0.021 -.7198956 -.0589789
|
largecap#c.lncprw |
0 | -.1049655 .0445654 -2.36 0.019 -.192312 -.0176189
1 | -.0649495 .0423145 -1.53 0.125 -.1478843 .0179853
|
lndebtw | -.0438299 .0298084 -1.47 0.141 -.1022534 .0145935
roaw | -.0035022 .0053485 -0.65 0.513 -.0139852 .0069808
|
year |
2 | .0519943 .0727962 0.71 0.475 -.0906836 .1946721
3 | .0068917 .0722662 0.10 0.924 -.1347475 .1485309
4 | .1009946 .0733629 1.38 0.169 -.042794 .2447833
5 | .0682871 .0791128 0.86 0.388 -.086771 .2233453
6 | .163254 .0794656 2.05 0.040 .0075042 .3190038
|
industry |
2 | -.7025008 .2870299 -2.45 0.014 -1.265069 -.1399325
3 | -.2654213 .3294975 -0.81 0.421 -.9112246 .380382
4 | .0987919 .3974654 0.25 0.804 -.6802259 .8778097
5 | -.0794056 .2830836 -0.28 0.779 -.6342393 .4754282
6 | .055311 .325204 0.17 0.865 -.5820771 .692699
|
relativelti | -.0106507 .1518421 -0.07 0.944 -.3082557 .2869544
_cons | 5.83631 .6264509 9.32 0.000 4.608488 7.064131
------------------+----------------------------------------------------------------
sigma_u | .52549987
sigma_e | .37084696
rho | .66754914 (fraction of variance due to u_i)
-----------------------------------------------------------------------------------
Am i correct with my interpretation of the insignificant interaction term, that ceo pay ratio only affects the esg-rating of small cap companies? Or is this form of robustness check not making sense? I greatly appreciate any form of help or push in the right direction.
. asdoc xtreg lnesg lncprw lndebtw roaw lncapw i.year i.industry
Random-effects GLS regression Number of obs = 378
Group variable: id Number of groups = 72
R-squared: Obs per group:
Within = 0.3450 min = 1
Between = 0.2702 avg = 5.2
Overall = 0.3786 max = 6
Wald chi2(14) = 180.33
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
------------------------------------------------------------------------------
lnesg | Coefficient Std. err. z P>|z| [95% conf. interval]
-------------+----------------------------------------------------------------
lncprw | .0326537 .0160507 2.03 0.042 .0011949 .0641126
lndebtw | .0198029 .0115212 1.72 0.086 -.0027782 .0423841
roaw | -.0012461 .0022023 -0.57 0.572 -.0055624 .0030703
lncapw | .1039689 .0202222 5.14 0.000 .064334 .1436037
|
year |
2 | .0075412 .0291055 0.26 0.796 -.0495046 .064587
3 | .1173459 .0286406 4.10 0.000 .0612114 .1734804
4 | .137357 .028574 4.81 0.000 .0813529 .193361
5 | .2003007 .0292682 6.84 0.000 .142936 .2576654
6 | .2318731 .0287288 8.07 0.000 .1755656 .2881805
|
industry |
2 | -.2258393 .1233899 -1.83 0.067 -.4676792 .0160006
3 | -.2486235 .1410259 -1.76 0.078 -.5250291 .0277821
4 | .0804007 .1718355 0.47 0.640 -.2563907 .4171921
5 | -.1236049 .1198287 -1.03 0.302 -.3584648 .111255
6 | -.0007003 .1410232 -0.00 0.996 -.2771007 .2757001
|
_cons | 2.215179 .3151133 7.03 0.000 1.597568 2.832789
-------------+----------------------------------------------------------------
sigma_u | .21701252
sigma_e | .14300232
rho | .69723982 (fraction of variance due to u_i)
------------------------------------------------------------------------------
. xtreg lnscope lncsrstrat lnesg c.lncprw#i.largecap lndebtw roaw i.year i.industry re
Random-effects GLS regression Number of obs = 371
Group variable: id Number of groups = 70
R-squared: Obs per group:
Within = 0.0732 min = 1
Between = 0.0910 avg = 5.3
Overall = 0.0987 max = 6
Wald chi2(17) = 28.85
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0359
-----------------------------------------------------------------------------------
lnscope | Coefficient Std. err. z P>|z| [95% conf. interval]
------------------+----------------------------------------------------------------
lncsrstrat | .1438839 .0728789 1.97 0.048 .0010439 .286724
lnesg | -.3894373 .1686043 -2.31 0.021 -.7198956 -.0589789
|
largecap#c.lncprw |
0 | -.1049655 .0445654 -2.36 0.019 -.192312 -.0176189
1 | -.0649495 .0423145 -1.53 0.125 -.1478843 .0179853
|
lndebtw | -.0438299 .0298084 -1.47 0.141 -.1022534 .0145935
roaw | -.0035022 .0053485 -0.65 0.513 -.0139852 .0069808
|
year |
2 | .0519943 .0727962 0.71 0.475 -.0906836 .1946721
3 | .0068917 .0722662 0.10 0.924 -.1347475 .1485309
4 | .1009946 .0733629 1.38 0.169 -.042794 .2447833
5 | .0682871 .0791128 0.86 0.388 -.086771 .2233453
6 | .163254 .0794656 2.05 0.040 .0075042 .3190038
|
industry |
2 | -.7025008 .2870299 -2.45 0.014 -1.265069 -.1399325
3 | -.2654213 .3294975 -0.81 0.421 -.9112246 .380382
4 | .0987919 .3974654 0.25 0.804 -.6802259 .8778097
5 | -.0794056 .2830836 -0.28 0.779 -.6342393 .4754282
6 | .055311 .325204 0.17 0.865 -.5820771 .692699
|
relativelti | -.0106507 .1518421 -0.07 0.944 -.3082557 .2869544
_cons | 5.83631 .6264509 9.32 0.000 4.608488 7.064131
------------------+----------------------------------------------------------------
sigma_u | .52549987
sigma_e | .37084696
rho | .66754914 (fraction of variance due to u_i)
-----------------------------------------------------------------------------------
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