An empirical review of factors affecting revenue collection in nairobi county, kenya

© Ngicuru, Muiru, Riungu & Shisia
influence on revenue collection as shown by the coefficient (B = 0.584, t = 7.686, p> 0.03). Tax administration also showed a significant influence on revenue collection with the coefficients (B= 0.695, t = 2.208, p> 0.008) indicating a positive effect on revenue collection. Tax structure as well showed a significant influence with a coefficient of (B = 0.659, t = 2.850, p> 0.019) showing a positive and significant relationship. Similarly, forms of revenue indicated a significant positive influence with coefficients (B = 0.687, t = 4.465, p> 0.000). The study used the following regression model:


Y = β₀ + β₁X₁ + β₂X₂ + β₃X₃ + β₄X₄+ ε

Where:

Y= Revenue collection

β₀=Constant

β_1……... β₄₌ Coefficient of the variables

X₁=Revenue diversification

X₂= Administration

X₃=Tax structure

X₄= forms of revenue

ε= Error term

Therefore;

Revenue collection= 6.885 + 0.584 Revenue diversification + 0.695 Tax administration + 0.659 Tax structure + 0.687 Forms of revenue + .589

Diagnostic Tests

The researcher conducted a multicollinearity test. The researcher made further attempt to minimize and/or avoid Common Method Variance (CMV) problem in the study. The precautions taken in designing the questionnaires (i.e. use of multi-item scales) as well as identifying different respondents for the independent and dependent variables, as already done, are preliminary mechanisms to minimize this problem. In addition to these precautions, the data is further tested or checked for CMV problem before commencing data analysis. The study therefore adopted collinearity analysis to test for collinearity issues, which might have arose during the study. According to the findings in table 16 below, the spread of the VIF values is very low (less than 2.5), indicating that there were no major problems in the study.

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