Skripsi Adinda


Uploading data Adinda


In [127]:
data <- read.csv("adinda.clean2.csv")

In [132]:
summary(data[4:26])


Out[132]:
      CEI           BRIB_CORR         BUSS_ETH        FAIR_COMP     
 Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0.3051   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000  
 Median :0.4702   Median :0.0000   Median :0.5000   Median :0.0000  
 Mean   :0.4814   Mean   :0.2542   Mean   :0.4462   Mean   :0.2708  
 3rd Qu.:0.6958   3rd Qu.:0.6000   3rd Qu.:0.7500   3rd Qu.:0.5000  
 Max.   :0.9524   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
   POL_CONTR        INDIG_PPL        IND_EC_IMP        X0TH_ENG     
 Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0.0000   1st Qu.:0.6667   1st Qu.:1.0000   1st Qu.:0.3332  
 Median :0.0000   Median :1.0000   Median :1.0000   Median :0.5000  
 Mean   :0.3316   Mean   :0.7865   Mean   :0.8681   Mean   :0.5060  
 3rd Qu.:0.7500   3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:0.6667  
 Max.   :1.0000   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
    ALT_CEI          BRD_EFFC        BRD_INDP        BRD_MEET    
 Min.   :0.0000   Min.   :1.458   Min.   :1.167   Min.   :1.000  
 1st Qu.:0.3000   1st Qu.:2.059   1st Qu.:1.833   1st Qu.:2.000  
 Median :0.5000   Median :2.235   Median :1.833   Median :2.333  
 Mean   :0.4361   Mean   :2.231   Mean   :1.960   Mean   :2.333  
 3rd Qu.:0.6000   3rd Qu.:2.412   3rd Qu.:2.167   3rd Qu.:2.667  
 Max.   :0.8000   Max.   :2.882   Max.   :3.000   Max.   :3.000  
    BRD_SIZE      BRD_COMPT        DIVIDEND            LOSS       
 Min.   :1.00   Min.   :1.750   Min.   :   0.00   Min.   :0.0000  
 1st Qu.:1.00   1st Qu.:2.500   1st Qu.:   0.00   1st Qu.:0.0000  
 Median :3.00   Median :2.500   Median :   0.00   Median :0.0000  
 Mean   :2.09   Mean   :2.525   Mean   :  70.24   Mean   :0.3125  
 3rd Qu.:3.00   3rd Qu.:2.500   3rd Qu.:  50.00   3rd Qu.:1.0000  
 Max.   :3.00   Max.   :3.000   Max.   :1666.00   Max.   :1.0000  
   TOT_ASSETS         SLACK             ROE             BRD_INDP_DIV    
 Min.   : 7.998   Min.   : 6.423   Min.   :-2.030000   Min.   :   0.00  
 1st Qu.:11.878   1st Qu.:10.603   1st Qu.:-0.001275   1st Qu.:   0.00  
 Median :12.523   Median :11.487   Median : 0.045330   Median :   0.00  
 Mean   :12.438   Mean   :11.365   Mean   : 0.036846   Mean   : 147.22  
 3rd Qu.:13.129   3rd Qu.:12.203   3rd Qu.: 0.172300   3rd Qu.:  92.01  
 Max.   :26.558   Max.   :26.605   Max.   : 0.741000   Max.   :4442.67  
  BRD_MEET_DIV     BRD_SIZE_DIV    BRD_COMPT_DIV 
 Min.   :   0.0   Min.   :   0.0   Min.   :   0  
 1st Qu.:   0.0   1st Qu.:   0.0   1st Qu.:   0  
 Median :   0.0   Median :   0.0   Median :   0  
 Mean   : 180.4   Mean   : 203.5   Mean   : 182  
 3rd Qu.: 125.0   3rd Qu.: 100.0   3rd Qu.: 125  
 Max.   :4998.0   Max.   :4998.0   Max.   :4165  

In [133]:
head(data)


Out[133]:
XFirmYearCEIBRIB_CORRBUSS_ETHFAIR_COMPPOL_CONTRINDIG_PPLIND_EC_IMPellip.hDIVIDENDLOSSTOT_ASSETSSLACKROEBRD_INDP_DIVBRD_MEET_DIVBRD_SIZE_DIVBRD_COMPT_DIVBRD_EFFC_DIV
10120110.5714300.50.50.250.25130.35013.7113512.706030.2260.775.87591.0575.87575.875
21120120.5476200.250.250.51155.82524013.8127412.686450.14193.04225158.1713167.4757139.5631131.3534
32120130.5238100.50.250.251115.36585013.9144612.919520.07428.1706735.853646.0975538.4146334.34713
43120140.5238100.50.250.251129.375013.9040412.969210.05644.062573.437588.12573.437563.93381
54220110.488100.50.750110012.3619911.555290.056900000
65220120.738101110.66710112.4629911.18364-0.077300000

In [134]:
tail(data)


Out[134]:
XFirmYearCEIBRIB_CORRBUSS_ETHFAIR_COMPPOL_CONTRINDIG_PPLIND_EC_IMPellip.hDIVIDENDLOSSTOT_ASSETSSLACKROEBRD_INDP_DIVBRD_MEET_DIVBRD_SIZE_DIVBRD_COMPT_DIVBRD_EFFC_DIV
1391383520130.90.8111110012.1810811.014430.006500000
1401393520140.90.8111110111.19110.80838-0.200200000
14114036201100000000011.7358210.375720.248500000
14214136201200000000011.5899610.74650.199800000
1431423620130.0952400000.6667050011.8841610.859130.03979091.666550112.593.75
1441433620140.0952400000.666708011.9529310.623480.179214.414.6666481815

In [135]:
names(data)


Out[135]:
  1. 'X'
  2. 'Firm'
  3. 'Year'
  4. 'CEI'
  5. 'BRIB_CORR'
  6. 'BUSS_ETH'
  7. 'FAIR_COMP'
  8. 'POL_CONTR'
  9. 'INDIG_PPL'
  10. 'IND_EC_IMP'
  11. 'X0TH_ENG'
  12. 'ALT_CEI'
  13. 'BRD_EFFC'
  14. 'BRD_INDP'
  15. 'BRD_MEET'
  16. 'BRD_SIZE'
  17. 'BRD_COMPT'
  18. 'DIVIDEND'
  19. 'LOSS'
  20. 'TOT_ASSETS'
  21. 'SLACK'
  22. 'ROE'
  23. 'BRD_INDP_DIV'
  24. 'BRD_MEET_DIV'
  25. 'BRD_SIZE_DIV'
  26. 'BRD_COMPT_DIV'
  27. 'BRD_EFFC_DIV'

In [137]:
# ncol(data)
dataMean <- data[4:26]
dataMean


Warning message:
In `[<-.factor`(`*tmp*`, ri, value = "⋱"): invalid factor level, NA generatedWarning message:
In `[<-.factor`(`*tmp*`, ri, value = "⋱"): invalid factor level, NA generated
Out[137]:
CEIBRIB_CORRBUSS_ETHFAIR_COMPPOL_CONTRINDIG_PPLIND_EC_IMPX0TH_ENGALT_CEIBRD_EFFCellip.hBRD_COMPTDIVIDENDLOSSTOT_ASSETSSLACKROEBRD_INDP_DIVBRD_MEET_DIVBRD_SIZE_DIVBRD_COMPT_DIV
10.5714300.50.50.250.25110.72.52.530.35013.711347004412.70602844120.2260.775.87591.0575.875
20.5476200.250.250.5110.83330.52.352942.555.82524013.812735318212.68645229990.14193.0422527508158.171327249167.47572139.5631
30.5238100.50.250.25110.66670.52.235292.515.36585013.914459257812.91952007260.07428.170673780535.853598780546.0975538.414625
40.5238100.50.250.25110.66670.52.176472.529.375013.904038968612.96921083220.05644.062573.437588.12573.4375
50.488100.50.750110.16670.32.264582.2250012.361989089411.55529159050.05690000
60.738101110.66710.50.52.176472.50112.462986445411.1836429401-0.07730000
70.4523801000.666710.50.62.411762.750112.586116420210.351711481-0.07990000
80.785710111110.50.42.294122.750112.627300553910.722222464-0.22930000
90000000001.770832.250111.04789796199.5402516202-0.64310000
100.19444000010.50.16670.32.058822018.17848658226.4482448881-0.3820000
110.1904800000.66670.50.16670.22.1176520012.17299383777.47942962360.0120000
120.488100.2500.5110.66670.42.058822.50111.17848658229.5032344573-0.3610000
130.404760000110.83330.62.083332.53.55013.272263657112.67483776420.30739.46667857.69167853.558.875
140.48611010.250110.66670.62.4117637.76699113.319197049512.5483202289-0.740918.122950776715.5339823.3009723.30097
150.721430.810.2501110.62.411762.750113.387438009312.6970048826-2.030000
160.804760.8110110.833330.61.6666720113.345618748612.6277011786-2.020000
170.776190.6101110.83330.62.104172.750013.240659329812.05083619920.047260000
180.6750.80.50.251110.50.72.529412.750113.285384019112.0537505376-0.040000
190.78810.60.750.750.75110.66670.62.42.50113.384407392512.15279253850.040000
200.680950.60.7500.75110.66670.62.352942.750113.36724659310.8946206959-0.1250000
210.642860110110.50.52.458332.580013.157946093712.18412193310.285160186.6664240200
220.642860110110.50.522.5200026.557647676226.60458106860.078400300600500
230.580950.40.7500.750.666710.50.51.941182.5200013.367015958112.27022230550.078366.666300600500
240.5238100.50.50110.66670.72.058822.50113.161987670312.0004251778-0.740000
250.540480.20.250.250.25110.83330.72.06252.750112.567268001611.5286472517-0.080000
260.488890.60.50.500.66710.66670.52.411762.50112.630097737811.3602530756-0.140000
270.56190.60.50.500.666710.66670.52.176472.50112.729121111211.45927644890.140000
280.876190.8110.5110.83330.72.352942.50012.648187975611.230338545500000
290.4523800.250.250110.66670.62.854172.750113.034227260812.2860071221-0.160210000
300.4523800.250.250110.66670.62.764712.50113.051620761711.74303762810.160000
31NA
1150.709520.80.501110.66670.52.529412.556.29012.896707723511.7879547080.13140.725140.725168.87140.725
1160.709520.80.501110.66670.62.529412.50012.989114934811.56169276670.130000
1170.2857100.5000.333310.16670.11.791672.50011.338957286210.01791470830.010000
1180.3611100.250.250.5110.16670.41.8752.50011.245515135410.15227443630.0350000
1190.500.7500.750.666710.33330.21.882352.50011.514494624710.1155631040.00610000
1200.4642900.500.750.666710.33330.21.882352.50011.563543970510.01342475230.01150000
1210.42857000.50.51100.32.06252.750011.171845560710.52214777440.43750000
1220.194440000110.16670.32.31252.750011.171846343310.52214777440.2330000
1230.2142900000.333310.16670.12.529412.52011.195880288510.69902998010.19725565
1240.4047600.500110.33330.32.529412.50011.559522409610.67749989680.02780000
1250.2142900000.333310.16670.11.8752.50012.23317115810.47503072020.110000
1260.0833300000.333310.166701.941182.50012.177103454110.43502528010.090000
1270.2142900000.333310.16670.11.866672.50012.74163388939.18452561760.0260000
1280.2142900000.333310.1670.11.866672.50112.741344894711.3527985687-0.0310000
1290.6547600.750.750.750.666710.66670.52.252.5190.90909012.349935877811.74136252830.34286.363635381.81818572.72727477.272725
1300.4305600.50.50.250.666710.66670.22.117652.5436.8932012.416006766911.44188422960.24728.156789644946.6033896441310.67961092.233
1310.697620.80.2501110.83330.62.117652.5457.31707012.524175980211.70599447120.25685.9756051067.071638941371.951211143.292675
1320.697620.80.2501110.83330.62.117652.5468.5012.511707937411.69566770030.17702.751093.1651051405.51171.25
1330.740480.60.750.750.75110.33330.32.3752.574013.261353692312.5357553920.14123.33358172.66642222185
1340.622220.40.50.50.5110.83330.72.235292.560013.357724720812.53169670870.03109.9998139.9998180150
1350.676190.40.50.50.5110.83330.72.294122.544.47561113.450985324612.6001590316-7e-0481.5384700813111.189025133.42683111.189025
1360.676190.40.50.50.5110.833330.72.294122.50113.456812301812.6189591745-0.03150000
1370.780950.8111010.66670.62.3752.510111.964390469410.9298073638-0.043418.333321.66673025
1380.744440.8111010.66670.52.294122.250112.030980722310.8882940238-0.15160000
1390.90.8111110.50.52.294122.50012.181076342811.01442832890.00650000
1400.90.8111110.50.52.294122.50111.190996640110.8083797949-0.20020000
1410000000002.145832.250011.73582397210.3757151690.24850000
1420000000001.882352.250011.589957416310.74649827770.19980000
1430.0952400000.66670001.8752.2550011.884161527810.85912710230.03979091.666550112.5
1440.0952400000.66670001.8752.258011.9529287910.623478620.179214.414.66664818

Summary Statistics


In [112]:
library(stargazer)

In [113]:
summary(data)


Out[113]:
      Firm            Year           CEI           BRIB_CORR     
 Min.   : 1.00   Min.   :2011   Min.   :0.0000   Min.   :0.0000  
 1st Qu.: 9.75   1st Qu.:2012   1st Qu.:0.3051   1st Qu.:0.0000  
 Median :18.50   Median :2012   Median :0.4702   Median :0.0000  
 Mean   :18.50   Mean   :2012   Mean   :0.4814   Mean   :0.2542  
 3rd Qu.:27.25   3rd Qu.:2013   3rd Qu.:0.6958   3rd Qu.:0.6000  
 Max.   :36.00   Max.   :2014   Max.   :0.9524   Max.   :1.0000  
    BUSS_ETH        FAIR_COMP        POL_CONTR        INDIG_PPL     
 Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.6667  
 Median :0.5000   Median :0.0000   Median :0.0000   Median :1.0000  
 Mean   :0.4462   Mean   :0.2708   Mean   :0.3316   Mean   :0.7865  
 3rd Qu.:0.7500   3rd Qu.:0.5000   3rd Qu.:0.7500   3rd Qu.:1.0000  
 Max.   :1.0000   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
   IND_EC_IMP        X0TH_ENG         ALT_CEI          BRD_EFFC    
 Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :1.458  
 1st Qu.:1.0000   1st Qu.:0.3332   1st Qu.:0.3000   1st Qu.:2.059  
 Median :1.0000   Median :0.5000   Median :0.5000   Median :2.235  
 Mean   :0.8681   Mean   :0.5060   Mean   :0.4361   Mean   :2.231  
 3rd Qu.:1.0000   3rd Qu.:0.6667   3rd Qu.:0.6000   3rd Qu.:2.412  
 Max.   :1.0000   Max.   :1.0000   Max.   :0.8000   Max.   :2.882  
    BRD_INDP        BRD_MEET        BRD_SIZE      BRD_COMPT    
 Min.   :1.167   Min.   :1.000   Min.   :1.00   Min.   :1.750  
 1st Qu.:1.833   1st Qu.:2.000   1st Qu.:1.00   1st Qu.:2.500  
 Median :1.833   Median :2.333   Median :3.00   Median :2.500  
 Mean   :1.960   Mean   :2.333   Mean   :2.09   Mean   :2.525  
 3rd Qu.:2.167   3rd Qu.:2.667   3rd Qu.:3.00   3rd Qu.:2.500  
 Max.   :3.000   Max.   :3.000   Max.   :3.00   Max.   :3.000  
    DIVIDEND            LOSS          TOT_ASSETS            SLACK          
 Min.   :   0.00   Min.   :0.0000   Min.   :9.957e+07   Min.   :2.649e+06  
 1st Qu.:   0.00   1st Qu.:0.0000   1st Qu.:7.557e+11   1st Qu.:4.009e+10  
 Median :   0.00   Median :0.0000   Median :3.332e+12   Median :3.073e+11  
 Mean   :  70.24   Mean   :0.3125   Mean   :2.508e+24   Mean   :2.794e+24  
 3rd Qu.:  50.00   3rd Qu.:1.0000   3rd Qu.:1.348e+13   3rd Qu.:1.597e+12  
 Max.   :1666.00   Max.   :1.0000   Max.   :3.611e+26   Max.   :4.023e+26  
      ROE             BRD_INDP_DIV      BRD_MEET_DIV     BRD_SIZE_DIV   
 Min.   :-2.030000   Min.   :   0.00   Min.   :   0.0   Min.   :   0.0  
 1st Qu.:-0.001275   1st Qu.:   0.00   1st Qu.:   0.0   1st Qu.:   0.0  
 Median : 0.045330   Median :   0.00   Median :   0.0   Median :   0.0  
 Mean   : 0.036846   Mean   : 147.22   Mean   : 180.4   Mean   : 203.5  
 3rd Qu.: 0.172300   3rd Qu.:  92.01   3rd Qu.: 125.0   3rd Qu.: 100.0  
 Max.   : 0.741000   Max.   :4442.67   Max.   :4998.0   Max.   :4998.0  
 BRD_COMPT_DIV   BRD_EFFC_DIV   
 Min.   :   0   Min.   :   0.0  
 1st Qu.:   0   1st Qu.:   0.0  
 Median :   0   Median :   0.0  
 Mean   : 182   Mean   : 172.0  
 3rd Qu.: 125   3rd Qu.: 110.6  
 Max.   :4165   Max.   :4606.0  

Plotting


In [114]:
library("ggplot2")

In [115]:
qplot( y = data$TOBINQ, x = data$SIZE)


Error in exists(name, envir = env, mode = mode): argument "env" is missing, with no default

Regression


In [138]:
library("plm")

In [139]:
data_panel <- pdata.frame(data, index = c("Firm", "Year"), drop.index =  TRUE, row.names = TRUE)

In [140]:
head(data_panel)


Out[140]:
XCEIBRIB_CORRBUSS_ETHFAIR_COMPPOL_CONTRINDIG_PPLIND_EC_IMPX0TH_ENGALT_CEIellip.hDIVIDENDLOSSTOT_ASSETSSLACKROEBRD_INDP_DIVBRD_MEET_DIVBRD_SIZE_DIVBRD_COMPT_DIVBRD_EFFC_DIV
1-201100.5714300.50.50.250.25110.730.35013.7113512.706030.2260.775.87591.0575.87575.875
1-201210.5476200.250.250.5110.83330.555.82524013.8127412.686450.14193.04225158.1713167.4757139.5631131.3534
1-201320.5238100.50.250.25110.66670.515.36585013.9144612.919520.07428.1706735.853646.0975538.4146334.34713
1-201430.5238100.50.250.25110.66670.529.375013.9040412.969210.05644.062573.437588.12573.437563.93381
2-201140.488100.50.750110.16670.30012.3619911.555290.056900000
2-201250.738101110.66710.50.50112.4629911.18364-0.077300000

In [141]:
tabel2_reg1 <- plm(CEI ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT, data = data_panel, model = "within" )
tabel2_reg2 <- plm(CEI ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel2_reg3 <- plm(BRIB_CORR ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel2_reg4 <- plm(BUSS_ETH ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel2_reg5 <- plm(FAIR_COMP ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel2_reg6 <- plm(POL_CONTR ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel2_reg7 <- plm(INDIG_PPL ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel2_reg8 <- plm(IND_EC_IMP ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel2_reg9 <- plm(X0TH_ENG ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )

In [ ]:


In [142]:
library(lmtest)

In [143]:
tabel3_reg2 <- plm(CEI ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + DIVIDEND +  LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel3_reg2 <- plm(CEI ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + DIVIDEND + BRD_INDP_DIV + LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel3_reg3 <- plm(CEI ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + DIVIDEND + BRD_MEET_DIV +LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel3_reg4 <- plm(CEI ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + DIVIDEND + BRD_SIZE_DIV +LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )
tabel3_reg5 <- plm(CEI ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + DIVIDEND + BRD_COMPT_DIV +LOSS + TOT_ASSETS + SLACK + ROE , data = data_panel, model = "within" )

In [144]:
summary(tabel3_reg5)


Out[144]:
Oneway (individual) effect Within Model

Call:
plm(formula = CEI ~ BRD_INDP + BRD_MEET + BRD_SIZE + BRD_COMPT + 
    DIVIDEND + BRD_COMPT_DIV + LOSS + TOT_ASSETS + SLACK + ROE, 
    data = data_panel, model = "within")

Balanced Panel: n=36, T=4, N=144

Residuals :
    Min.  1st Qu.   Median  3rd Qu.     Max. 
-0.29200 -0.06850 -0.00508  0.07040  0.29800 

Coefficients :
                 Estimate  Std. Error t-value Pr(>|t|)   
BRD_INDP       8.4966e-02  6.6897e-02  1.2701 0.207055   
BRD_MEET       5.1229e-02  4.7156e-02  1.0864 0.279983   
BRD_SIZE      -7.4791e-03  2.3705e-02 -0.3155 0.753051   
BRD_COMPT      1.0300e-03  7.6946e-02  0.0134 0.989347   
DIVIDEND      -3.5305e-05  1.1281e-03 -0.0313 0.975098   
BRD_COMPT_DIV -3.8764e-05  4.4336e-04 -0.0874 0.930507   
LOSS          -4.9450e-02  3.5688e-02 -1.3856 0.169012   
TOT_ASSETS     2.6793e-02  2.3470e-02  1.1416 0.256414   
SLACK         -1.9605e-02  2.1756e-02 -0.9011 0.369748   
ROE           -1.6469e-01  5.5440e-02 -2.9707 0.003737 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Total Sum of Squares:    1.7267
Residual Sum of Squares: 1.5156
R-Squared      :  0.12226 
      Adj. R-Squared :  0.083202 
F-statistic: 1.36499 on 10 and 98 DF, p-value: 0.2079

In [145]:
names(data)


Out[145]:
  1. 'X'
  2. 'Firm'
  3. 'Year'
  4. 'CEI'
  5. 'BRIB_CORR'
  6. 'BUSS_ETH'
  7. 'FAIR_COMP'
  8. 'POL_CONTR'
  9. 'INDIG_PPL'
  10. 'IND_EC_IMP'
  11. 'X0TH_ENG'
  12. 'ALT_CEI'
  13. 'BRD_EFFC'
  14. 'BRD_INDP'
  15. 'BRD_MEET'
  16. 'BRD_SIZE'
  17. 'BRD_COMPT'
  18. 'DIVIDEND'
  19. 'LOSS'
  20. 'TOT_ASSETS'
  21. 'SLACK'
  22. 'ROE'
  23. 'BRD_INDP_DIV'
  24. 'BRD_MEET_DIV'
  25. 'BRD_SIZE_DIV'
  26. 'BRD_COMPT_DIV'
  27. 'BRD_EFFC_DIV'

In [146]:
tabel4_reg1 <- plm(CEI ~ BRD_EFFC +  DIVIDEND +  LOSS + TOT_ASSETS + SLACK + ROE, data = data_panel, model = "within" )
tabel4_reg2 <- plm(ALT_CEI ~ BRD_EFFC +  DIVIDEND +  LOSS + TOT_ASSETS + SLACK + ROE, data = data_panel, model = "within" )
tabel4_reg3 <- plm(CEI ~ BRD_EFFC +  DIVIDEND + BRD_EFFC_DIV + LOSS + TOT_ASSETS + SLACK + ROE, data = data_panel, model = "within" )
tabel4_reg4 <- plm(ALT_CEI ~ BRD_EFFC +  DIVIDEND + BRD_EFFC_DIV + LOSS + TOT_ASSETS + SLACK + ROE, data = data_panel, model = "within" )
tabel4_reg5 <- plm(BRD_EFFC ~ ALT_CEI + LOSS + TOT_ASSETS + SLACK + ROE, data = data_panel, model = "within" )
tabel4_reg6 <- plm(ALT_CEI ~ BRD_EFFC +LOSS + TOT_ASSETS + SLACK + ROE, data = data_panel, model = "within" )

In [147]:
robust111 <- coeftest(tabel4_reg1, vcov=function(x) vcovHC(x, method="arellano",
                                                          type="HC1", cluster="group"))
robust222 <- coeftest(tabel4_reg2, vcov=function(x) vcovHC(x, method="arellano",
                                                          type="HC1", cluster="group"))
robust333 <- coeftest(tabel4_reg3, vcov=function(x) vcovHC(x, method="arellano",
                                                          type="HC1", cluster="group"))
robust445 <- coeftest(tabel4_reg4, vcov=function(x) vcovHC(x, method="arellano",
                                                          type="HC1", cluster="group"))
robust555 <- coeftest(tabel4_reg5, vcov=function(x) vcovHC(x, method="arellano",
                                                          type="HC1", cluster="group"))
robust666 <- coeftest(tabel4_reg5, vcov=function(x) vcovHC(x, method="arellano",
                                                          type="HC1", cluster="group"))

Coba Regresi Billy

Hausman Test: H0: RE vs H1: FE


In [76]:
skripsi.fe <- plm(TOBINQ ~ PDEBT + LogAssets + LEV + LIQ + INTCOV + PROF + DR + GROWTH + FIRMAGE, data = data_panel, model = "within")
skripsi.re <- plm(TOBINQ ~ PDEBT + LogAssets + LEV + LIQ + INTCOV + PROF + DR + GROWTH + FIRMAGE, data = data_panel, model = "random")


Error in eval(expr, envir, enclos): object 'TOBINQ' not found
Error in eval(expr, envir, enclos): object 'TOBINQ' not found

In [77]:
summary(skripsi.fe)


Error in summary(skripsi.fe): object 'skripsi.fe' not found

In [78]:
summary(skripsi.re)


Error in summary(skripsi.re): object 'skripsi.re' not found

In [79]:
phtest( skripsi.fe, skripsi.re)


Error in phtest(skripsi.fe, skripsi.re): object 'skripsi.fe' not found

Hausman menghasilkan penggunaan Fixed Effect







Poolability Test


In [80]:
pooltest.billy <- pooltest(TOBINQ ~ PDEBT + FIRMAGE + LIQ, data = data_panel, model="within")


Error in eval(expr, envir, enclos): object 'TOBINQ' not found

In [81]:
pooltest.billy


Error in eval(expr, envir, enclos): object 'pooltest.billy' not found

Bruesch Pagan Test


In [82]:
pool_rergression <- plm(TOBINQ ~ PDEBT + SIZE + LEV + LIQ + INTCOV + PROF + DR + GROWTH + FIRMAGE, data = data_panel, model="pooling")
bpagan_test <- plmtest(pool_rergression,effect="twoways",type="bp")


Error in eval(expr, envir, enclos): object 'TOBINQ' not found
Error in plmtest(pool_rergression, effect = "twoways", type = "bp"): object 'pool_rergression' not found

In [83]:
bpagan_test


Error in eval(expr, envir, enclos): object 'bpagan_test' not found

BP Test significant dan Hausman significant, sehinggga menggunakan Fixed effect


In [84]:
summary(skripsi.fe)


Error in summary(skripsi.fe): object 'skripsi.fe' not found

In [85]:
summary(data_panel)


Out[85]:
       X               CEI           BRIB_CORR         BUSS_ETH     
 Min.   :  0.00   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.: 35.75   1st Qu.:0.3051   1st Qu.:0.0000   1st Qu.:0.0000  
 Median : 71.50   Median :0.4702   Median :0.0000   Median :0.5000  
 Mean   : 71.50   Mean   :0.4814   Mean   :0.2542   Mean   :0.4462  
 3rd Qu.:107.25   3rd Qu.:0.6958   3rd Qu.:0.6000   3rd Qu.:0.7500  
 Max.   :143.00   Max.   :0.9524   Max.   :1.0000   Max.   :1.0000  
   FAIR_COMP        POL_CONTR        INDIG_PPL        IND_EC_IMP    
 Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.6667   1st Qu.:1.0000  
 Median :0.0000   Median :0.0000   Median :1.0000   Median :1.0000  
 Mean   :0.2708   Mean   :0.3316   Mean   :0.7865   Mean   :0.8681  
 3rd Qu.:0.5000   3rd Qu.:0.7500   3rd Qu.:1.0000   3rd Qu.:1.0000  
 Max.   :1.0000   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
    X0TH_ENG         ALT_CEI          BRD_EFFC        BRD_INDP    
 Min.   :0.0000   Min.   :0.0000   Min.   :1.458   Min.   :1.167  
 1st Qu.:0.3332   1st Qu.:0.3000   1st Qu.:2.059   1st Qu.:1.833  
 Median :0.5000   Median :0.5000   Median :2.235   Median :1.833  
 Mean   :0.5060   Mean   :0.4361   Mean   :2.231   Mean   :1.960  
 3rd Qu.:0.6667   3rd Qu.:0.6000   3rd Qu.:2.412   3rd Qu.:2.167  
 Max.   :1.0000   Max.   :0.8000   Max.   :2.882   Max.   :3.000  
    BRD_MEET        BRD_SIZE      BRD_COMPT        DIVIDEND      
 Min.   :1.000   Min.   :1.00   Min.   :1.750   Min.   :   0.00  
 1st Qu.:2.000   1st Qu.:1.00   1st Qu.:2.500   1st Qu.:   0.00  
 Median :2.333   Median :3.00   Median :2.500   Median :   0.00  
 Mean   :2.333   Mean   :2.09   Mean   :2.525   Mean   :  70.24  
 3rd Qu.:2.667   3rd Qu.:3.00   3rd Qu.:2.500   3rd Qu.:  50.00  
 Max.   :3.000   Max.   :3.00   Max.   :3.000   Max.   :1666.00  
      LOSS          TOT_ASSETS            SLACK                ROE           
 Min.   :0.0000   Min.   :9.957e+07   Min.   :2.649e+06   Min.   :-2.030000  
 1st Qu.:0.0000   1st Qu.:7.557e+11   1st Qu.:4.009e+10   1st Qu.:-0.001275  
 Median :0.0000   Median :3.332e+12   Median :3.073e+11   Median : 0.045330  
 Mean   :0.3125   Mean   :2.508e+24   Mean   :2.794e+24   Mean   : 0.036846  
 3rd Qu.:1.0000   3rd Qu.:1.348e+13   3rd Qu.:1.597e+12   3rd Qu.: 0.172300  
 Max.   :1.0000   Max.   :3.611e+26   Max.   :4.023e+26   Max.   : 0.741000  
  BRD_INDP_DIV      BRD_MEET_DIV     BRD_SIZE_DIV    BRD_COMPT_DIV 
 Min.   :   0.00   Min.   :   0.0   Min.   :   0.0   Min.   :   0  
 1st Qu.:   0.00   1st Qu.:   0.0   1st Qu.:   0.0   1st Qu.:   0  
 Median :   0.00   Median :   0.0   Median :   0.0   Median :   0  
 Mean   : 147.22   Mean   : 180.4   Mean   : 203.5   Mean   : 182  
 3rd Qu.:  92.01   3rd Qu.: 125.0   3rd Qu.: 100.0   3rd Qu.: 125  
 Max.   :4442.67   Max.   :4998.0   Max.   :4998.0   Max.   :4165  
  BRD_EFFC_DIV   
 Min.   :   0.0  
 1st Qu.:   0.0  
 Median :   0.0  
 Mean   : 172.0  
 3rd Qu.: 110.6  
 Max.   :4606.0  
















In [86]:
qplot(y = data$LogTobinsQ, x = data$LIQ, geom = c("point", "smooth"), method = lm)


Error in exists(name, envir = env, mode = mode): argument "env" is missing, with no default

In [87]:
var(data$LIQ)


Error in var(data$LIQ): 'x' is NULL

In [88]:
var(data$TOBINQ)


Error in var(data$TOBINQ): 'x' is NULL

In [89]:
qplot(data$TOBINQ)


Error in exists(name, envir = env, mode = mode): argument "env" is missing, with no default

In [90]:
skripsi.try1 <- plm(log(TOBINQ) ~ PDEBT + log(SIZE) + log(LEV) + log(LIQ) + log(INTCOV) + log(PROF) + DR + log(GROWTH) + FIRMAGE + y1 + y2 + y3 , data = data_panel, model = "within")


Error in eval(expr, envir, enclos): object 'TOBINQ' not found

In [91]:
summary(skripsi.try1)


Error in summary(skripsi.try1): object 'skripsi.try1' not found

In [92]:
install.packages("R2wd")


Installing package into ‘/home/qbits7/R/x86_64-pc-linux-gnu-library/3.2’
(as ‘lib’ is unspecified)
Error in contrib.url(repos, type): trying to use CRAN without setting a mirror

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