The Data and Wrangling
#omx <- read.csv("C:/Users/emretoros/Desktop/omx.csv", encoding="UTF-8")
omx <- read.csv("C:/Users/emretoros/Desktop/emre_model/omx1.csv", encoding="UTF-8")
#The Analysis
EDA
options(scipen=10000)
#solvency
omx %>%
ggplot(aes(x= solvency, y= tobins_q)) +
stat_summary( fun.data=mean_cl_normal, width=0.1, conf.int=0.95, fill="lightblue") +
stat_summary(geom="line", fun.y=mean, linetype="dashed")+
stat_summary(geom="point", fun.y=mean, color="red") +
labs(y = "Tobins Q", x= "Solvency ")

#roa
omx %>%
ggplot(aes(x= roa, y= tobins_q)) +
stat_summary( fun.data=mean_cl_normal, width=0.1, conf.int=0.95, fill="lightblue") +
stat_summary(geom="line", fun.y=mean, linetype="dashed")+
stat_summary(geom="point", fun.y=mean, color="red") +
labs(y = "Tobins Q", x= "Roa ")

#toplam varlık
omx %>%
ggplot(aes(x= log10(toplam_varlik), y= tobins_q)) +
stat_summary( fun.data=mean_cl_normal, width=0.1, conf.int=0.95, fill="lightblue") +
stat_summary(geom="line", fun.y=mean, linetype="dashed")+
stat_summary(geom="point", fun.y=mean, color="red") +
labs(y = "Tobins Q", x= "Toplam Varlık(log10)")

DV: Tobins q Linear Models
tob_mod0 <- lm(tobins_q ~ denetim_komitesi_kadin_sayi + denetim_komitesi_kadin_baskan, data=omx)
tob_mod1 <- lm(tobins_q ~ denetim_komitesi_kadin_sayi + denetim_komitesi_kadin_baskan + solvency + roa + log10(toplam_varlik), data=omx)
tob_mod11 <- lm(tobins_q ~ denetim_komitesi_kadin_sayi + denetim_komitesi_kadin_baskan + trucost + big_4 + denetim_top_say + denetim_komitesi_uye, data=omx)
tob_mod2 <- lm(tobins_q ~ denetim_komitesi_kadin_sayi + denetim_komitesi_kadin_baskan + solvency + roa + log10(toplam_varlik) +trucost + big_4 + denetim_top_say + denetim_komitesi_uye, data= omx)
tab_model(tob_mod0, tob_mod1, tob_mod11, tob_mod2)
|
|
tobins q
|
tobins q
|
tobins q
|
tobins q
|
|
Predictors
|
Estimates
|
CI
|
p
|
Estimates
|
CI
|
p
|
Estimates
|
CI
|
p
|
Estimates
|
CI
|
p
|
|
(Intercept)
|
0.48
|
0.45 – 0.51
|
<0.001
|
0.60
|
0.44 – 0.75
|
<0.001
|
0.26
|
0.13 – 0.38
|
<0.001
|
0.52
|
0.30 – 0.73
|
<0.001
|
|
denetim_komitesi_kadin_sayi
|
0.06
|
0.04 – 0.08
|
<0.001
|
0.04
|
0.03 – 0.05
|
<0.001
|
0.05
|
0.02 – 0.07
|
<0.001
|
0.03
|
0.01 – 0.04
|
0.008
|
|
denetim_komitesi_kadin_baskan
|
-0.06
|
-0.10 – -0.03
|
0.001
|
-0.03
|
-0.06 – -0.00
|
0.023
|
-0.09
|
-0.13 – -0.04
|
<0.001
|
-0.03
|
-0.07 – 0.00
|
0.071
|
|
solvency
|
|
|
|
-0.01
|
-0.01 – -0.01
|
<0.001
|
|
|
|
-0.01
|
-0.01 – -0.01
|
<0.001
|
|
roa
|
|
|
|
-0.00
|
-0.00 – -0.00
|
0.001
|
|
|
|
-0.00
|
-0.01 – -0.00
|
<0.001
|
|
toplam_varlik [log10]
|
|
|
|
0.03
|
0.01 – 0.05
|
0.010
|
|
|
|
0.02
|
-0.01 – 0.05
|
0.109
|
|
trucost
|
|
|
|
|
|
|
0.01
|
-0.03 – 0.05
|
0.631
|
0.03
|
-0.01 – 0.06
|
0.123
|
|
big_4
|
|
|
|
|
|
|
0.05
|
-0.03 – 0.14
|
0.195
|
0.08
|
0.02 – 0.14
|
0.015
|
|
denetim_top_say
|
|
|
|
|
|
|
0.01
|
-0.00 – 0.02
|
0.052
|
-0.00
|
-0.01 – 0.01
|
0.637
|
|
denetim_komitesi_uye
|
|
|
|
|
|
|
0.03
|
0.01 – 0.05
|
0.003
|
0.02
|
0.00 – 0.04
|
0.017
|
|
Observations
|
847
|
847
|
427
|
427
|
|
R2 / R2 adjusted
|
0.060 / 0.058
|
0.402 / 0.399
|
0.109 / 0.096
|
0.488 / 0.477
|
plot_model(tob_mod2, type = "pred")
## $denetim_komitesi_kadin_sayi

##
## $denetim_komitesi_kadin_baskan

##
## $solvency

##
## $roa

##
## $toplam_varlik

##
## $trucost

##
## $big_4

##
## $denetim_top_say

##
## $denetim_komitesi_uye

DV: Roa Linear Models
roa_mod0 <- lm(roa ~ denetim_komitesi_kadin_sayi + denetim_komitesi_kadin_baskan, data=omx)
roa_mod1 <- lm(roa ~ denetim_komitesi_kadin_sayi + denetim_komitesi_kadin_baskan + solvency + tobins_q + log10(toplam_varlik), data=omx)
roa_mod11 <- lm(roa ~ denetim_komitesi_kadin_sayi + denetim_komitesi_kadin_baskan + trucost + big_4 + denetim_top_say + denetim_komitesi_uye, data=omx)
roa_mod2 <- lm(roa ~ solvency + tobins_q + log10(toplam_varlik) + trucost + big_4 + denetim_komitesi_kadin_sayi + denetim_komitesi_kadin_baskan + denetim_top_say + denetim_komitesi_uye, data= omx)
tab_model(roa_mod0, roa_mod1, roa_mod11, roa_mod2)
|
|
roa
|
roa
|
roa
|
roa
|
|
Predictors
|
Estimates
|
CI
|
p
|
Estimates
|
CI
|
p
|
Estimates
|
CI
|
p
|
Estimates
|
CI
|
p
|
|
(Intercept)
|
5.82
|
4.77 – 6.86
|
<0.001
|
40.17
|
33.69 – 46.65
|
<0.001
|
9.65
|
4.99 – 14.32
|
<0.001
|
40.51
|
30.90 – 50.13
|
<0.001
|
|
denetim_komitesi_kadin_sayi
|
0.67
|
0.07 – 1.27
|
0.029
|
1.35
|
0.76 – 1.94
|
<0.001
|
0.68
|
-0.23 – 1.59
|
0.143
|
1.10
|
0.23 – 1.96
|
0.013
|
|
denetim_komitesi_kadin_baskan
|
-0.38
|
-1.67 – 0.90
|
0.557
|
-0.17
|
-1.39 – 1.04
|
0.779
|
0.86
|
-0.90 – 2.61
|
0.338
|
0.72
|
-0.94 – 2.38
|
0.396
|
|
solvency
|
|
|
|
-0.05
|
-0.08 – -0.01
|
0.006
|
|
|
|
-0.07
|
-0.12 – -0.02
|
0.004
|
|
tobins_q
|
|
|
|
-4.77
|
-7.69 – -1.84
|
0.001
|
|
|
|
-9.21
|
-13.57 – -4.84
|
<0.001
|
|
toplam_varlik [log10]
|
|
|
|
-4.37
|
-5.24 – -3.50
|
<0.001
|
|
|
|
-4.22
|
-5.55 – -2.88
|
<0.001
|
|
trucost
|
|
|
|
|
|
|
0.96
|
-0.71 – 2.63
|
0.258
|
0.61
|
-0.95 – 2.17
|
0.444
|
|
big_4
|
|
|
|
|
|
|
2.50
|
-0.58 – 5.57
|
0.112
|
3.05
|
0.14 – 5.96
|
0.040
|
|
denetim_top_say
|
|
|
|
|
|
|
-0.91
|
-1.37 – -0.44
|
<0.001
|
-0.38
|
-0.83 – 0.08
|
0.107
|
|
denetim_komitesi_uye
|
|
|
|
|
|
|
-0.50
|
-1.26 – 0.25
|
0.192
|
0.38
|
-0.36 – 1.11
|
0.317
|
|
Observations
|
856
|
847
|
431
|
427
|
|
R2 / R2 adjusted
|
0.006 / 0.003
|
0.128 / 0.123
|
0.052 / 0.038
|
0.179 / 0.161
|
plot_model(roa_mod2, type = "pred")
## $solvency

##
## $tobins_q

##
## $toplam_varlik

##
## $trucost

##
## $big_4

##
## $denetim_komitesi_kadin_sayi

##
## $denetim_komitesi_kadin_baskan

##
## $denetim_top_say

##
## $denetim_komitesi_uye
