Table4. Descriptive statistics of efficiency indicators
Variables Sign N Min. Max. Mean Std. Dev. Kolmogorov-Smirnov Z
Efficiency (Small Banks) SIZ_S 30 .84 1.00 .9534 .03450 0.934
Efficiency (Big Banks) SIZ_R 30 .79 1.00 .8983 .04807 0.499
Efficiency (Young Banks) AGE_Y 30 .77 1.00 .8918 .05368 0.498
Efficiency (Old Banks) AGE_O 30 .86 1.00 .9488 .03296 0.666
Efficiency (Public Banks) OWN_P 30 .71 1.00 .8648 .06710 0.496
Efficiency (Private Banks) OWN_V 30 .88 1.00 .9574 .02747 0.664
Source: collected and processed by the researcher.
Efficiency score of using DEA according to CCR method is 95.34% for small banks, while it’s 89.83% for big ones. Efficiency scores are 89.18% and94.88% for young and old banks respectively. Besides, they are 86.48% and 95.74% for public and private banks respectively. However, these differences don’t indicate significance. Kolmogorov-Smirnov test shows that variables are not normally distributed. So, Wilcoxon signed rank test (as a non-parametric test) is conducted to check the significance of these differences, as follow:
5. Summary and Concluded Remarks
This paper aims at analyzing the effects of bank size. age and ownership on efficiency of Egyptian banks, as measured by Data Envelopment Analysis (DEA) according to CCR method. This has been conducted using Wilcoxon signed rank test, as applied on a sample of 10 banks during the period from 1984 to 2013
Result indicate that, efficiency scores differ significantly, according to “size”, “age” and “ownership” of the Egyptian banks, where small, old and private banks seem to more efficient than big, young and public ones. Also, robustness check assures the “age” and “ownership” effects, using panel data analysis.
Bank ownership explains 21.1% of efficiency scores and this could be more elaborated by analyzing private banks characteristics that may enhance efficiency. Further research may investigate their competitive advantages in areas of risk management, systemic risk and financial stability.