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Dr. Shuchi Gupta Dept. of Accounting, College of Business Administration Dept. of Accounting, College of Business Administration |
Dr. Shuchi Gupta Assistant Professor Dept. of Management & Information Systems College of Business Administration, University of Hail, Kingdom of Saudi Arabia. |
Every government requires funds for the performance of its various functions. The main sources of financing government expenditure are taxations. Especially developing countries like Ethiopia are used to raise revenue collection from tax for their economic development. One of the major aim of the tax system in Ethiopia is to maximize domestic revenue by collecting sufficient taxes. To achieve this, the Ethiopian government creates different tax reform programs and the reform improved the application of business income tax with more simplified standard assessment methods of presumptive taxes. This study is an attempt to identify the efforts done by govt. for collecting the tax with the help of Statistical tool- Multiple regression analysis which reveals that tax assessment affects the tax collection performance. Thus, it can be concluded that the tax law enforcement has its own contribution to tax collection performance and the revenue authority of the town should consider as of the other predictors.
Keyword: Ethiopian Federal Income tax, Taxpayers, Tax assessment, Service Delivery.
Taxes are significant sources of public revenue. The existence of collective consumption of goods and services necessitates putting some of the income into government hands. Moreover, there are many purposes of collecting revenue through taxes. It enables government to allocate resources; to provide or support social development. It stabilizes the economy and encourages optimal economic growth (ECC & EBDSN, 2005).Especially developing countries like Ethiopia are used to raise revenue collection from tax for their economic development. One of the major purpose of the tax system in Ethiopia is to maximize domestic revenue by collecting sufficient taxes. In order to achieve this, the Ethiopian government creates different tax reform programs and the reform improved the application of business income tax with more simplified standard assessment methods of presumptive taxes (Misrak, 2011).
Category “A”: tax payers include any company incorporated under the laws of Ethiopia or in a foreign country and any other business having an annual turnover of Birr 1,000,000 or more. (Federal Income Tax Proclamation No, 979/2016). Category “B”: taxpayers unless already classified in category “A”, any business having an annual turnover of over Birr 500, 000 would be classified under Category “B” taxpayers. (ibid) Category “C”:Businesses having annual turnover is estimated less than Birr 500,000 are classified under this category.
Specifically, in Ethiopia category “C” taxpayers have higher compliance cost burden than category “A” and “B” taxpayers (Hagos, 2011) and Lemessa, 2007). Evidently the conformity cost burden rises with business size while the relative cost burden is remarkably higher for small businesses. Therefore, the compliance costs of taxation are mainly a problem for small businesses. Ethiopian business income taxpayers, as in other developing countries, tax noncompliance is a serious challenge facing income tax administration and hindering tax revenue performance.
1. To identify taxpayers’ problems related to the overall taxation system, tax assessment, collection and service delivery of tax authorities. 2. To examine the significance effect of tax assessment problems on tax collection process.
H1: Good service delivery of the tax authority affects positively the tax collection performance. H2: The law enforcement of the tax authority in Debre Markos city negatively affects the tax collection performance. H3: Effective awareness creation on tax payers by the tax authority positively affects the tax collection performance. H4: The taxpayers trust on the tax system affects positively the tax collection performance. H5: Tax collection performance positively affected by the fair tax assessment.
Sample of the study was category 'C' taxpayers of the Debre Markos city administration. Depending on the nature of the respondents, the study used two sampling techniques: the stratified simple random sampling and the purposive sampling technique. Based on this formula of sample size determination the researcher has
n=N/(1+N(e)^2 )=3860/(1+3860×(〖0.05)〗^2 )=363 That is, the sample size of the tax payers in category “C” was 363.
Tax collection performance which represents the effectiveness and efficiency of the tax collection by the tax collectors (authority) is considered as a dependent variable for this study. The dependent variable was expected to be influenced by many factors of the tax assessment such as, service delivery, the tax assessment awareness creation, the trust of taxpayers on the tax system, the tax assessment fairness, and law enforcement of tax assessment.
refers to the act of providing service by the tax authorities, assessors and collectors to taxpayers so as to make the process efficient and effective. Their support can initiate the taxpayers to reduce the tax evasion and then improve the tax collection performance.
refers the implementation of transparent, simple and practical tax law of the tax authority in order to be fair and reduces disputes with the taxpayers on the amount due.
refers to honesty, trust or loyalty of the tax collectors and assessors. Besides it shows the taxpayers’ trust on assessment and collection procedures of the tax authority.
is the process of conducting different types of training related to tax assessment procedures, rules & regulations, principles and soon. Creating awareness will help tax authorities to minimize tax evasion and frauds.
Fairness of the tax assessment and collection (FT): refers to the perception of taxpayers and tax authorities in which the tax levied by the tax assessors and collectors are acceptable, proportional to their income, equitable and correct to different category “C” taxpayers. Therefore, based on the above information the researcher of this study formulates the following linear regression model
Y= β0 + β1X1 + β2X2 + β3 X3 + β4 X4+ β5 X5+ e
Where: Yi = Tax collection performance; β0 = Constant; β i = Vector of unknown parameters; X1= Service delivery by the tax authority; X2= law enforcement of tax assessment; X3= trust on tax system; X4= Tax assessment awareness creation; X5= fairness of the tax assessment and collection; and e = error term.
Taking the regression equation demonstrated above into account, one can make the following analysis by considering coefficient of the linear regression, model summary of the regression and one-way ANOVA of the regression
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Table1 : Model Summary |
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Model |
R |
R2 |
Adjusted R2 |
Std. Error of the Estimate |
Change Statistics |
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R2 Change |
F Change |
df1 |
df2 |
Sig. F Change |
DW |
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1 |
.825a |
.681 |
.676 |
.31476 |
.681 |
148.416 |
5 |
348 |
.000 |
1.909 |
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a. Predictors: (Constant), TLE, SD, AC, FT, TTS |
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The output shown in the multiple linear regression model summary that the unadjusted multiple R2 for these data is 0.681, and the adjusted multiple R2 is 0.676.Here, one can see that there is no significant difference between the unadjusted R square value and the adjusted R square values. The five predictor variables together accounted about 0.681 (68.1%) of the variance on the value of the dependent variable (tax collection performance). The standard error of the estimate is also a measure how much R is predicted to vary from one sample to the next. In this case, the standard error of the estimate is about 0.31476, which mean the multiple correlation R between all the predictor variables(X1, X2, X3,X4 and X5) and tax collection performance will vary by 0.31476 (31.476%). A multiple regression analysis was conducted to see if service delivery (SD), tax law enforcement (TLE), trust on tax system (TTS), awareness creation (AC) and fairness of the tax assessment and collection (FT) could predict the tax collection performance. As the ANOVA summary in Table 2 below indicates, the model is fit to predict tax collection performance from service delivery, tax law enforcement, trust on tax system, awareness creation and fairness of the tax assessment and collection as it was found statistically significant (df=5, 348; F=148.416, is greater than its table value and significant at p<0.01)
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ANOVAa |
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Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
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1 |
Regression |
73.520 |
5 |
14.704 |
148.416 |
.000b |
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Residual |
34.477 |
348 |
.099 |
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Total |
107.997 |
353 |
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a. Dependent Variable: TCP |
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b. Predictors: (Constant), TLE, SD, AC, FT, TTS |
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On the same way table 3 below portrayed that the coefficients of the five predictor variables obtained in the multiple linear regression.
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Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
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B |
Std. Error |
Beta |
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(Constant) |
-.233 |
.169 |
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-1.376 |
.170 |
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FT (X1) |
.152 |
.034 |
.151 |
4.461 |
.000 |
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AC (X2) |
.362 |
.038 |
.333 |
9.438 |
.000 |
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TTS (X3) |
.343 |
.038 |
.332 |
9.128 |
.000 |
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SD (X4) |
.268 |
.037 |
.265 |
7.307 |
.000 |
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TLE (X5) |
-.058 |
.030 |
-.060 |
-1.914 |
.056 |
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The first number in the regression equation is -0.233 is the intercept or the constant. This means that if the values of all the five selected predictor variables become zero, the value of the dependent variable (tax collection performance) will be -0.233. Similarly, the regression coefficient of FT is 0.152 (i.e. the slop of the line).This implies that holding other variables being constant, a unit increase in fairness and equity on the tax system increases the value of the dependent variable (tax collection performance) by 0.152. On the other hand, if the tax assessors and collectors do their task perfectly in an equitable and fairly (100%) holding other variables constant, then the performance of the tax collection or the efficiency will be increased by 15.2%. One can make the same interpretation for the rest of four predictor variables by taking each regression coefficient as a slop of the regression equation. It is important to analyze the cumulative contribution of each potential predictor variable, whether they are statistically significant or not, if so, the direction of the relationship. For doing such analysis, the regression coefficients, and the partial t-test were used with degree of freedom (df= 348) and level of significance (p<0.01). Fairness of tax assessment and collection (X1, β= 0.152) is statistically significant (p=0.000), and the regression coefficient is positive which would indicate that high level of fairness on tax assessment and collection is related to best tax collection performance. In the same way, other four predictor variables (X2,X3,X4 and X5)have statistically significant relationship with the criterion variable (tax collection performance =Y) though their direction of relationship is not the same. When we see the coefficient and level of significance of the independent variable tax law enforcement it has β = -0.058 and p< 0.05. Based on these result, the following model was developed to examine the determinants of tax collection performance (TCP) in this study.
TCP = -0.233 + 0.268 (SD) -0.058 (TLE) + 0.343 (TTS) + 0.362 (AC) + 0.152 (FT) + Є
The variable good service delivery by tax authority is significant with P-value of 0.000 at 1% and the coefficient is positive (0.268) then the hypothesis is accepted. This supports the hypotheses that states good service delivery influences tax collection efficiency positively. In other words, the result implies that good service delivery by the tax authority on category ‘C’ taxpayers positively affects tax collection performance. The finding of this study is in line with others researchers work. For instance, Hagos (2011) and Lemessa (2007) explained that the service delivery by the authority was below enough and poor when evaluated by the category “C” tax payers.
The result of regression shows that strong law enforcement by the tax authority found insignificant with p-value 0.056 at 5% and the coefficient is negative (-0.058), therefore the hypothesis rejected. This result supports the hypothesis which states strong law enforcement can minimize the likelihood of efficient tax collection. As can be seen in the descriptive analysis, a very great number of respondents believed that law enforcement is strong and the authority is demanded improvement. Hagos (2011) findings explained that strong law enforcement can maximize the possibility of efficient tax collection.
The significant value of the variable awareness creation by tax authority is accepted at p< 0.01. This implies that the awareness creation on tax payers by the tax authority significantly affects tax collection efficiency. As the regression result showed if the tax authority creates awareness to the tax payers fully holding other variables constant, then it will increase the tax collection performance by 36.2%. Therefore, the hypothesis “effective awareness creation on tax payers by the tax authority is positively affects the tax collection performance” is accepted. The result obtained in this study is supported by different researchers like Getaneh (2011), Hagos (2011), Suresh (2012) and Lemessa (2007).
The study found the regression coefficient of the independent variable trust on the tax system (β = 0.343) has positive and significant (P-value = 0.000 which is less than α = 0.01) relationship with tax collection performance. This shows that if taxpayers trust on the tax system is increased by 100%, tax collection performance will be increased by 34.3% by controlling other factors constant. This means that there is positive significant relation between trust on the tax system and tax collection performance. Therefore, the Ho is rejected and the H1 is accepted. Hagos (2011) in his study stated honesty of the tax collectors and indicated that the tax payers of category “C” responded negatively and many of them believed that there was high corruption at the time of the registering, assessments and payments of taxes. On the other hand, Lemessa (2007) and Asamenew (2012) found that the majority of the taxpayers don’t have believe in tax estimation, assessment and collection procedures.
The sig-value column shows that 0.000 is accepted at 1% in the dimension of tax assessment fairness to category ‘C’ tax payers and the coefficient of the multiple linear regressions is positive 0.152; thus, the hypothesis is accepted. This result supports the hypothesis that states ‘tax collection efficiency is positively affected by the faired tax assessment.’ This implies that if tax assessment is perceived to be fair by tax payers, it would have a positive impact on tax collection performance, otherwise negative. That is, if the tax assessors and collectors do their task perfectly in an equitable and fairly (100%) way, then the performance of the tax collection or the efficiency will be increased by 15.2%. Wubshet’s (2011) also found that the low income earners receive more benefit from the government but a significant ratio opposed this and this needs more work to be fair and equitable for the citizens. Wollela (2009) also found that the tax being levied is not equitable and fair; it may nearly negate the principles of fairness and ability to pay.
On the basis of the results from data analysis with the help of Multiple Regression it is concluded that Tax assessment affects the tax collection performance. The most significant variables affecting tax collection were awareness creation, tax assessment and collection fairness, and service delivery, while tax law enforcement affect tax collection performance negatively and in an insignificant statistic. Moreover, Tax authority is not doing to the maximum of their capacity to create awareness (educate) to the category “C” taxpayers. The revenue office is not pertaining adequate education and awareness training on tax issue for majority of category “C” taxpayers. It is also identified that the quality of service delivery to category “C” taxpayers Debre Markos town is poor. Based on the majority of the taxpayers’ perception the response rate of taxpayers complains and queries were not given quickly. The higher proportions of the category “C” taxpayers in Debre Markos town were dissatisfied and not yet sufficient enough. On the basis of data analysis and conclusion it would be suggested that one of the most important points is mobilizing tax payers towards government agendas. This is because tax payers are the foundation for the government existence and should have a strong bondage between the government and the tax payers. Therefore, to strengthen the relationship between the government and the tax payers through persuasion and continuous communication is a matter of awareness creation. For creating awareness tax authority should use its own tools such as regular educational sessions through politicians, professionals, role models of the tax payers, through visiting and experience sharing on the results of paid tax and using electronic and printing medias. Tax assessment is done with no enough data of transaction of the tax payers and this is not convenient for both the government as well as the tax payers. Therefore, participation of the tax payers at the tax assessment is essential. This could be through the legal representative associations or representatives can be directly elected from the tax payers in the town.Even though many factors affect efficient tax collection, one of the essential factors is service delivery.
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