Table 5. Linear and nonlinear...

Table 5.

Linear and nonlinear estimations of the corruption model with the employee characteristics

Dependent variable: Transparency (TRANS)
Independent variables	Linear probability model (OLS)^a	Probit model (ML)	Logit model (ML)
PREV	0.043(0.628))	0.155(0.5986)	0.2910(0.5532)
AACOR	0.1190*(0.0885)	0.3688(0.1028)	0.6298*(0.0974)
TE	0.0694(0.1998)	0.2348(0.2361)	0.4308(0.2125)
GEND	0.0487(0.3366)	0.1810(0.3352)	0.335(0.3092)
AGE	0.0369(0.4128)	0.1603(0.3878)	0.2406(0.4467)
EXP	−0.1142***(0.0037)	−0.4124***(0.0068)	−0.6764***(0.0084)
Intercept	0.8316***(0.0000)	1.0274**(0.0252)	1.6487**(0.0367)
R²/pseudo R²	0.0838	0.0787	0.078

Dependent variable: Transparency (TRANS)
Independent variables	Linear probability model (OLS)^a	Probit model (ML)	Logit model (ML)
PREV	0.043(0.628))	0.155(0.5986)	0.2910(0.5532)
AACOR	0.1190*(0.0885)	0.3688(0.1028)	0.6298*(0.0974)
TE	0.0694(0.1998)	0.2348(0.2361)	0.4308(0.2125)
GEND	0.0487(0.3366)	0.1810(0.3352)	0.335(0.3092)
AGE	0.0369(0.4128)	0.1603(0.3878)	0.2406(0.4467)
EXP	−0.1142***(0.0037)	−0.4124***(0.0068)	−0.6764***(0.0084)
Intercept	0.8316***(0.0000)	1.0274**(0.0252)	1.6487**(0.0367)
R²/pseudo R²	0.0838	0.0787	0.078

Note(s):

*** represents significance at the 1% level; ** represents significance at the 5% level; *represents significance at the 10% levell; ^aEstimated using heteroscedasticity-robust standard errors; p-values are given in parentheses. TRANS is the presence of transparency, PREV is the preventive measures, AACOR is the actions against corruption, TE is the training and ethics, GEND is gender, AGE is age group and EXP is experience

Source(s): Authors’ own work

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