Factors Affecting Tax Collection: the Case of Bale Robe Revenue Office
Year: 2025
Type: article
Abstract: The main objective of this study was to analyze the factors that affect tax collection in Bale Robe town/zone for the period 2014/15 to 2020/21. Descriptive statistics, Chi square analysis, Binary logistic regression method of data analysis were employed to analyze the data. The total number of sample size taken was 371.Data analyzed with discriptive statistics such as frequencies, percentages, mean and standard deviation through statistical tool of SPSS version 20.Based on the results, there is a significant association between determinants such as Age, sex, education qualification, work experience, awareness, tax compliance, evasion, unemployment, revenue office capacity and instability and dependent variable tax revenue collection in Bale Robe town, Ethiopia. The data presented in tablesfrom the result of logistic regression, the variables gender, age, awareness, evasion, unemployment, revenue office capacity and instability more significantly affected tax revenue collection in the Bale Robe town. Whereas,education qualification, work experience, and tax compliance are not significantly affected the tax revenue collection in Bale robe town.Since the findings of this study provedthat many factors that determine the tax collection like awareness, evasion, unemployment and instability, the Robe town administration might consider seeing all factors which determine tax collection. To enhance tax awareness the Robe town must exert it’s at most efforts in increasing tax awareness of tax payers. Since evasion, instability and unemployment affect the income of the Robe town administration, it could strongly work on mitigation measures like increasing awareness,incentive mechanism to those meet their obligations effectively, increasing security and decreasing unemployment by developing projects that enhance job opportunities.7
DOI: 10.20372/nadre:12537
Author: Adafre Wederyelesh
Institution: Madda Walabu University
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6926070160
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