Analysis of socio-economic factors affecting revenue collection in kenya: a case of Siaya county

Abstract

County Governments in Kenya have been depending largely on the National Treasury for financial support since their establishment in April, 2013. This is against the backdrop of their agitation to have more government functions including security to be devolved. After the senate passes the division of revenue Act and the national assembly passes the CARA, then counties are guaranteed of development expenditure. However, this isn’t the only source of revenue used by the counties as there’s the bit of own source of revenue that in turn determines how much of recurrent expenditure a county gets. The controller of budget evaluates a county’s level of revenue collection to release recurrent expenditure; so if revenue collection is low, then the county is likely to have pending bills relating to recurrent expenditure. Consequently, this study sought to analyze the socio-economic factors affecting revenue collection in Kenya: A case of Siaya County. The study was guided by the following specific objectives: to establish the effect of legislation on rate of revenue collection in Kenya, to determine the effect of enforcement on rate of revenue collection in Kenya, to investigate the effect of automation on rate of revenue collection in Kenya; and to evaluate the effect of political goodwill on rate of revenue collection in Kenya. The findings of the study provide useful insights on revenue collection as the county government officials can gain comprehension on the factors affecting rate of revenue collection in Kenya. The social influence theory and optimal taxation theory anchored this study. This study adopted a cross sectional descriptive survey design and a correlational research design. The main focus of the study were the 1474 employees working under the Siaya County government. The study generally adopted stratified sampling whereby each group was sampled separately. However, Krecjie and Morgan (1970) formulae and simple random sampling were adopted to sample each department giving a sample size of 312. The study utilized a data collection form and a semi-structured questionnaire. Both descriptive and inferential statistics were used to analyze the data. Mean and standard deviations were used as measures of central tendencies and dispersion respectively. The study adopted both correlation and regression to test the relationship between the variables. The results showed that Legislation, Enforcement, Automation and Political goodwill jointly caused a significant deviation associated to rate of revenue collection in Kenya. In summary, the study established that Legislation, Enforcement, Automation and Political goodwill are indeed socio-economic factors affecting revenue collection in Kenya. In conclusion, legislation, enforcement, automation and political goodwill had a significant effect on rate of revenue collection in Kenya. The study recommends the creation and strengthening of an independent revenue body to strategically create strategies that advocate, administer and promote best practices for fostering sustainable and efficient revenue collection in County governments of Kenya. The study also recommends creation, adoption and strengthening of full-fledged revenue collection legislation. The study further recommends auxiliary scrutiny and improvement on current automation models utilized by county governments