Table VIII.

Logistic regression model

Variables in the model*HypothesisPredicted signBWaldSignificance**ToleranceVIF
SIZEH1+0.00018.7230.0000.7151.400
SEGMENTSH2+0.0300.0760.7830.9201.086
RECINVH3+0.0215.7060.0170.9001.111
OCFH4+0.0294.1520.0420.8621.160
RISKCH5+1.68010.6030.0010.9221.085
LEVH6+−0.0060.5070.4760.7841.276
DSHH7−0.0274.8910.0270.8331.200
MSHH8?0.0000.0000.9830.8511.175
INDCHH9+−0.2740.7090.4000.8751.143
INDDSH10+−0.0070.1270.7220.4692.132
ACSIZEH11a+0.5874.0440.0440.5491.820
ACINDH11b+−0.0050.1710.6790.5531.807
ACEXPH11c+0.0143.9860.0460.9171.091
ACMEETH11d+0.3745.7350.0170.7511.332
BIG4?0.9683.2190.0730.8031.246
AUDITFEES?−0.5060.3650.5460.8241.214
Constant  −5.04012.3580.000  
N332Pseudo R Square:  
Model Chi-square172.980Cox & Snell0.406
Significance0.000Nagelkerke0.553
Overall Percentage Correct80.7     

Notes:

*

Dependent variable (IAF existence) = 1 if the company has an IAF, 0 if the company does not;

SIZE = Total Assets; SEGMENTS = number of operating segments; RECINV = receivables and inventories divided by total assets; OCF = operating cash flows divided by total assets; RISKC = 1 if the company has a risk management committee, 0 otherwise; LEV = long-term debts divided by total assets; DSH = percentage of outstanding shares owned by directors; MSH = percentage of outstanding shares owned by the major (institutional) shareholders; NDCH = 1 if the chairman is independent, 0 otherwise; INDDS = percentage of independent directors on the board; ACSIZE = number of audit committee members; ACIND = percentage of independent directors on the audit committee; ACEXP = percentage of directors with financial expertise on the audit committee; ACMEET = number of audit committee meetings during the year; BIG4 = 1 when a Big 4 external auditor is used and 0 otherwise; AUDITFEES = total external audit fees divided by total assets;

**

p-Value (two-tailed)

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