Effect of I-tax Implementation on Revenue Collection in Kenya

Abstract

In an era characterized by rapid technological advancements and digital transformations, tax collection systems worldwide have undergone significant evolutions. Kenya's introduction of the I-tax system serves as a prime example, aiming to modernize and optimize revenue collection. Given the pivotal role of taxation in a nation's economic health, understanding the implications of such systemic changes is crucial. This study sought to ascertain the impact of the I-tax implementation on revenue collection in Kenya. Anchored within the frameworks of the theory of optimal taxation, tax incidence theory, and economic deterrence theory, the research aimed to decipher the relationship between digital tax initiatives and economic indicators. A descriptive research design was employed, harnessing secondary data from the Kenya Revenue Authority (KRA), Kenyan Central Bank, and the Kenya National Bureau of Statistics (KNBS). The study's temporal scope spanned 14 years, divided into two distinct phases: seven years before the I-tax implementation (2009-2015) and seven years’ post-implementation (2016-2022). Data on quarterly tax revenue, interest rates, inflation rates, and unemployment rates were meticulously gathered and analyzed. The research employed descriptive statistics, correlation analysis, and regression analysis to derive meaningful insights. The analysis yielded notable outcomes. Correlation results revealed a significant positive relationship between I-tax implementation and revenue collection. Meanwhile, economic indicators like unemployment rates were found to have a negative correlation with revenue. The regression model demonstrated that approximately 47.7% of the variation in revenue collection was attributable to the predictors. Specifically, the I-tax system had a positive effect, and a higher unemployment rate was inversely related to revenue collection. However, interest and inflation rates did not manifest statistically significant impacts within the regression framework. The study concludes that the I-tax system has made a positive stride in enhancing revenue collection in Kenya. Yet, it doesn't operate in a vacuum. Broader economic conditions, particularly unemployment rates, have considerable bearings on revenue collection dynamics. Policymakers should prioritize the integration of technology in tax systems, buttressed by robust taxpayer education campaigns. Continuous refinement and iterative improvements of digital platforms, paired with feedback mechanisms, can ensure the long-term success of such initiatives. Future research endeavors should consider extending the timeline to capture the prolonged implications of the I-tax system. Adopting a broader set of economic indicators can also offer a more holistic view of the revenue collection landscape.