Testing performance of an interest rate commission agent banking system (AIRCABS)

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This paper sought to analyze data and interpret statistical results in testing the performance of an interest rate commission agent banking system. Primary and secondary data were collected from banking industry in Ethiopia to test the research hypotheses, credit risk and liquidity crunch have no impact on AIRCABS, investor loan funding has a positive impact on profitability and sustainability of AIRCABS and discrete market deposit interest rate incentive has a positive impact on stable deposit mobilization in a bank. To test the hypothesis, statistical tools such as Cronbach’s alpha, Kuder-Richardson (KR-20), canonical correlation and multinomial logistic regression were used. The result showed that credit risk and liquidity crunch have no effect on an interest rate commission agent banking system, investor loan funding has a significant strong relationship with profitability and sustainability of AIRCABS and discrete market deposit interest rate incentive has also a significant strong relationship with stable deposit mobilization. This led to a conclusion that an interest rate commission agent banking system (AIRCABS) model is viable and reliable.

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    • Figure 1. AIRCABS risk transfer mechanism
    • Table 1. Indicators of credit risk and liquidity crunch measures
    • Table 2. Indicators of investor loan funding measures
    • Table 3. Indicators of discrete market deposit interest incentive measures
    • Table 4. Indicators of AIRCABS measures
    • Table 5. Measures of liquidity crunch ratio
    • Table 6. Measures of credit risk ratio
    • Table 7. Measures of investor loan funding ratio
    • Table 8. Measures of discrete market deposit interest incentive ratio
    • Table 9. Measure of AICABS ratio
    • Table 10. Descriptive statistics for credit risk and liquidity crunch
    • Table 11. Descriptive statistics for AIRCABS
    • Table 12. KMO and Bartlett’s test
    • Table 13. Model summary rotationa
    • Table 14. Variance accounted for investor loan funding survey instruments
    • Table 15. Variance accounted for discrete market deposit survey instruments
    • Table 16. Descriptive statistics for credit risk and liquidity crunch and AIRCABS
    • Table 17. Linear combination for canonical correlation
    • Table 18. Multivariate tests of significance
    • Table 19. Dimension reduction analysis
    • Table 20. KMO and Bartlett’s test
    • Table 21. Redundancy index and effect of shared variance
    • Table 22. Model fitting information of profitability and sustainability of AIRCABS
    • Table 23. Model fitting information of stable deposit
    • Table 24. Goodness-of-fit
    • Table 25. Pseudo R-square
    • Table 26. Likelihood ratio tests of profitability and sustainability of AIRCABS
    • Table 27. Likelihood ratio tests of stable deposit
    • Table 28. Parameter estimates of profitability and sustainability of AIRCABS
    • Table 29. Parameter estimates of stable deposit
    • Table 30. Classification
    • Table 31. Percentage classification of stable deposit
    • Table 32. Case processing summary (profitability and sustainability of AIRCABS)
    • Table 33. Case processing summary (stable deposit)