Table 5

Propensity score matching

Panel A – Logistic Regressions
(1)(2)(3)(4)(5)(6)(7)(8)
REGIN_REGREGIN_RESPREGIN_TIMEREGIN_DOLLAR
VariablesPre-matchPost-matchPre-matchPost-matchPre-matchPost-matchPre-matchPost-match
Without controlling for corporate governance
SIZE−0.071*0.019−0.0170.0020.0250.0280.136***−0.008
(−1.86)(0.52)(−0.53)(0.07)(0.75)(0.85)(4.28)(−0.26)
AGE0.097***−0.020−0.058*−0.037−0.007−0.002−0.080***0.007
(2.65)(−0.59)(−1.83)(−1.21)(−0.22)(−0.05)(−2.69)(0.24)
ROA0.131***0.0040.0350.001−0.0180.016−0.013−0.032
(3.20)(0.12)(1.11)(0.04)(−0.58)(0.50)(−0.39)(−1.01)
RETURN−0.051**−0.0130.0010.001−0.049**0.023−0.044*0.003
(−2.41)(−0.62)(0.03)(0.06)(−2.37)(1.05)(−1.91)(0.12)
INDCONC0.143***−0.0030.278***−0.0150.316***−0.040*0.128***−0.013
(6.53)(−0.11)(12.22)(−0.67)(13.81)(−1.72)(5.41)(−0.53)
Constant−0.953***0.168−1.430***0.088−1.681***−0.041−0.975***0.194
(−4.12)(0.64)(−7.25)(0.37)(−8.05)(−0.16)(−6.00)(0.90)
Observations78,44138,45278,42238,63578,41038,90464,30331,721
Pseudo R20.08880.002800.04870.003770.05230.004570.04710.00415
Year fixed effectYesYesYesYesYesYesYesYes
Firm fixed effectYesYesYesYesYesYesYesYes
Clustered std err by firmYesYesYesYesYesYesYesYes
Controlling for corporate governance
SIZE−0.175***−0.022−0.0390.0210.0030.0020.139***−0.012
(−4.01)(−0.55)(−1.01)(0.55)(0.08)(0.06)(4.01)(−0.36)
AGE0.129***−0.015−0.066*−0.0040.007−0.016−0.098***−0.005
(3.17)(−0.38)(−1.83)(−0.13)(0.19)(−0.44)(−3.17)(−0.15)
ROA0.198***−0.0130.0470.0050.0210.020−0.0070.005
(4.10)(−0.35)(1.34)(0.14)(0.62)(0.57)(−0.21)(0.14)
RETURN−0.041*0.002−0.004−0.006−0.096***−0.000−0.0360.005
(−1.71)(0.07)(−0.16)(−0.24)(−3.87)(−0.01)(−1.52)(0.19)
INDCONC0.079***−0.0360.176***−0.0190.182***−0.0410.126***−0.002
(3.20)(−1.46)(6.82)(−0.75)(7.31)(−1.60)(5.13)(−0.07)
CEOTURN0.032−0.011−0.0100.0130.038−0.0010.0250.008
(1.03)(−0.37)(−0.36)(0.44)(1.38)(−0.03)(0.96)(0.32)
CEODUALITY0.0110.004−0.0260.0040.0080.0000.0360.010
(0.31)(0.11)(−0.79)(0.12)(0.25)(0.00)(1.21)(0.33)
BOARDSIZE−0.025−0.0220.0310.004−0.136**0.0240.0280.015
(−0.35)(−0.32)(0.49)(0.06)(−2.12)(0.38)(0.58)(0.27)
Constant−1.840**−0.731−2.642***−0.169−4.354***0.500−1.148***−0.113
(−2.41)(−1.01)(−3.68)(−0.21)(−3.70)(0.39)(−5.86)(−0.52)
Observations61,00029,71860,71929,21960,95530,19659,95529,552
Pseudo R20.1050.004420.08940.006730.07030.004780.04910.00453
Year fixed effectYesYesYesYesYesYesYesYes
Firm fixed effectYesYesYesYesYesYesYesYes
Clustered std err by firmYesYesYesYesYesYesYesYes
Panel B – Stage 2 – Regressions of STRG
Variables(1)(2)(3)(4)(5)(6)(7)(8)
REGIN_REG−0.092***   −0.085***   
 (−8.615)   (−7.408)   
REGIN_RESP −0.057***   −0.067***  
  (−6.468)   (−5.958)  
REGIN_TIME  −0.059***   −0.062*** 
   (−7.264)   (−6.267) 
REGIN_DOLLAR   −0.022***   −0.022***
    (−3.104)   (−3.054)
SIZE−0.036**0.0010.000−0.012−0.046**−0.009−0.009−0.026
 (−2.275)(0.084)(0.014)(−0.667)(−2.357)(−0.465)(−0.491)(−1.406)
AGE−0.103***−0.117***−0.121***−0.147***−0.126***−0.144***−0.141***−0.161***
 (−5.976)(−6.372)(−6.643)(−6.181)(−5.683)(−5.738)(−5.809)(−6.611)
ROA−0.279***−0.328***−0.322***−0.309***−0.267***−0.321***−0.316***−0.297***
 (−18.661)(−20.918)(−20.544)(−17.047)(−14.774)(−17.237)(−16.820)(−16.524)
RETURN0.021***0.025***0.023***0.014**0.012**0.018***0.017***0.012**
 (4.062)(4.691)(4.343)(2.345)(2.134)(2.933)(2.797)(2.086)
INDCONC0.009**0.006*0.008**0.014***0.014***0.011***0.012***0.012***
 (2.361)(1.887)(2.307)(3.473)(3.525)(3.065)(3.642)(3.283)
CEOTURN    0.0050.0010.0030.003
     (1.149)(0.294)(0.591)(0.595)
CEODUALITY    −0.003−0.004−0.003−0.001
     (−0.398)(−0.461)(−0.359)(−0.133)
BOARDSIZE    0.026**0.036***0.035***0.031***
     (2.560)(3.176)(3.340)(2.791)
Constant0.522***0.352***0.369***0.327***0.359**0.307**0.257*0.347***
 (11.961)(10.220)(10.773)(7.481)(2.486)(2.278)(1.856)(7.916)
         
Observations38,45238,63538,90431,72129,71829,21930,19629,552
Adj. R-squared0.4920.5390.5390.5460.5150.5670.5680.547
Year fixed effectYesYesYesYesYesYesYesYes
Firm fixed effectYesYesYesYesYesYesYesYes
Clustered std err by firmYesYesYesYesYesYesYesYes

Note(s): This table presents the results of the propensity score matching approach. We create an indicator variable equal to one for firms with higher levels of regulatory intensity (treated firms) if they belong to the 4th quartile of the sample distribution of REGIN_REG/REGIN_RESP/REGIN_TIME/REGIN_DOLLAR and zero otherwise (control firms). In the first stage, we employ logistic regression to predict the propensity score using the same set of control variables with and without the control for corporate governance. Panel A displays the results. We revisit our baseline regressions using the matched sample in the second stage. Panel B displays the results. Refer to Appendix A for detailed variable definitions. We winsorize all continuous variables at the upper and lower 1% of the sample distribution. ***, ** and * indicate significance at the 1%, 5% and 10% levels, respectively

or Create an Account

Close Modal
Close Modal