Keywords

Taxation, Non-Oil, Economic, Growth, Taraba, Victor, Falack.

Introduction

After oil was discover in Nigeria, so many state Governments across board in Nigeria (including Taraba state) shifted attention from the non-oil-based revenue to oil-based revenue. Most States in Nigeria have been adjudged not to be viable, because they depend largely on the allocation received from the federation account. Depending on oil revenue alone has different disadvantages, ranging from the fact that oil is a wasting asset, and also the price of oil is largely determined and controlled by the international oil market.

Any economy depends on the ability to mobilize enough resource that can support such growth; however, the amount of tax revenue generated depends largely on the aggregate from various sources from different sectors of the economy. All economic entities, including Taraba State, revenue generation through taxation, amongst other things is directed towards meeting the basic social and infrastructural needs of its citizenry and to maintain a sustained economic growth. (Osuala, 2010) Thus, the quest to determine the extent to which non-oil sector tax revenue influences Taraba State economy necessitated this study.

Statement of Problem

Taraba State is over-dependent on oil-revenue accruing from the federation account. The burden of any revenue shock from the federation account directly affects the revenue base of Taraba state because of her over-dependence on oil-revenue. Taraba State is endowed with vast taxable population. These non-oil revenue from taxation has not been optimally harnessed to bring economic development to the state.

Literature Review

Taraba State Government Sources of Non-Oil Revenue: Taxes and Fees

One of the sources of non-oil revenue in Taraba State is tax. The approved taxes and fees in the state are contained in the TARABA STATE OF NIGERIA INTERNAL REVENUE SERVICE LAW NUMBER 3 OF 2020. These taxes, levies and fees collectible by Taraba State Board of Internal Revenue are:

1. Pay As You Earn (PAYE).
2. Direct Assessment.
3. Entertainment Tax.
4. Withholding Tax.
5. Pool Betting / Casino Stamp Duties.
6. Property Tax (state share).
7. Capital Gains Tax (Regulated by Federal Law).
8. Stamp Duties Fees (Regulated by Federal Law).
9. Development Levy.
10. Motor Vehicle Registration & Weighing Fees.
11. Contract Agreement Processing Fees.
12. Motor Vehicle Charges.
13. Registration Booklet.
14. Conductor & Drivers’ Badge.
15. Side Stickers.
16. SMS Alert.
17. Penalty for Offences.
18. Motor Vehicle License.
19. Driving License & Learners Permit.
20. Certificate of Road Worthiness.
21. Road worthiness Validity Tag.
22. Hackney Carriage Permit.
23. Riders Card.
24. Sales of Vehicle Number Plates.

Review of Empirical Literature

Likita & Nakah carried out an investigation on impact of non-oil revenue on economic growth in Nigeria. The study covered the period 1981 to 2016 and agricultural revenue, manufacturing revenue, solid minerals contributions, services revenue contribution, company income tax, and custom and excise duties tax were adopted as proxies for non-oil revenue and they were used as the independent variables. On the other hand, the study made use of Gross Domestic Product (GDP) as proxy for economic growth and it served as the dependent variable. Unit root test was carried out to determine the stationarity of the variables while the cointegration test was carried out to ascertain the existence of long run equilibrium relationship among the variables. Thereafter, the Ordinary Least Squares (OLS) and Error Correction Mechanism (ECM) techniques were used to analyse the data collected (Taraba State Government Official Website, 2021). Findings from the study showed that agricultural revenue, manufacturing revenue and services revenue exerted positive and significant impact on economic growth. On the other hand, the study showed that company income tax revenue exerted a negative and significant impact on economic growth in Nigeria. The study further revealed that solid minerals revenue exerted a negative and insignificant relationship with economic growth while custom and excise duties tax exerted a positive but insignificant impact on economic growth in Nigeria using the Ordinary Least Squares (OLS) estimation method.

Research Methodology

Research Design

In this study ex-post facto design was adopted in obtaining, analysing and interpretation of data required for this study. The ex-post facto research design is used to foist a link between the dependent and independent variables, relying on already an existing secondary data.

Model Specification and Variable Measurement

Ugochukwu & Azubike (2016), specified a model which captured an evaluation of the contributions of nonoil revenue to economic growth of Nigeria.

GDP = ƒ(OILREV, NOILREV)…………………Eqn. (1)

GDP = β_o + β₁OILREV + β₂NOILREV + μ……Eqn. (2)

Where:
GDP = Gross domestic product
OILREV = Oil revenue
NOILREV = Non-oil revenue

This model was adopted and modified to suit the objective of this study, thus, we have:

TRGDP = ƒ (TR)………………Eqn. (3)

Where:
TRGDP = Taraba Real gross domestic product
TR = Tax revenue
When transformed to its econometric model, it becomes:

TRGDP = β_o + β₁TR + μ Eqn……. (4)

Where:
β_o = Constant (Intercept) term
β₁ = Coefficient parameters of the explanatory variables.
μ = Stochastic or error term.
In order to bring the variables to the same base, the natural logarithm form was used as follows:

LnTRGDP = βo + β3lnTR + μ…………..Eqn. (5)

Data Presentation, Analysis And Discussion Of Findings

Data Presentation

Analysis of Data: In the following paragraphs, the study analysed the data as presented in Table 1.

Table 1 Non-oil revenue data for taraba state nigeria. 1997 to 2021
YEAR	Taraba Real Gross Domestic Product (TRGDP)=N=’billion	Tax Revenue (TR) =N=’billion
1997	19979.12	5.03
1998	20353.2	6.26
1999	21177.92	11.29
2000	21789.1	13.91
2001	22332.87	16.21
2002	22449.41	23.75
2003	23688.28	30.64
2004	25267.54	44.91
2005	28957.71	52.63
2006	31709.45	65.89
2007	35020.55	96.2
2008	37474.97	87.45
2009	39995.5	110.57
2010	42922.41	144.37
2011	46012.52	198.07
2012	49856.1	229.32
2013	54612.26	275.57
2014	57511.04	318
2015	59929.89	347.69
2016	63218.72	389.53
2017	67152.79	388.85
2018	69023.93	381.27
2019	67931.24	397.06
2020	68490.98	473.77
2021	69326.89	483.56

Source:  CBN Statistical Bulletin, 2012 (Various) and Taraba State Board of Internal Revenue 1997 – 2021.

Descriptive Statistics

This is a summary of statistic that quantitatively (i.e. numerical description like standard deviation, chart or graphic description that) describes features from a collection of information. For example, mean is a descriptive statistic that summarizes the figure that describes the average of the data collected.

From Table 2 above, the descriptive statistics was made using the data captured for 25 years (1997 to 2021). The Mean captured the average for each variable for the 25 years. This refers to the average of the numbers. Mean measures the centre point unlike standard deviation which measures dispersion away from the centre point. The Median represents the middle number for each variable.

Table 2 Descriptive Statistics
	TRGDP	TR
Mean	42647.36	183.6720
Median	39995.50	110.5700
Maximum	69326.89	483.5600
Minimum	19979.12	5.030000
Std. Dev.	18543.37	167.3177
Skewness	0.199388	0.468914
Kurtosis	1.494050	1.672809
Jarque-Bera	2.528029	2.750999
Probability	0.282518	0.252713
Sum	1066184.	4591.800
Sum Sq. Dev.	8.25E+09	671884.9
Observations	25	25

Maximum represents the maximum value for each variable reported in the 25 years statistics. On the other hand, Minimum represents the minimum value for each variable reported in the 25 years statistics. Standard deviation measure of the amount of variation or dispersion of a set of values. Basically, it measures dispersion away from the mean. A low standard deviation indicates that the values tend to be close to the mean while a high standard deviation indicates that the values are spread out over a wider range.

Skewness is the measure of lack of symmetry. A distribution or data set is symmetric if it looks the same to the left and right of the centre point but if it is not symmetric, it is said to be skewed. Skewness is the degree of distortion from the symmetrical bell curve or normal distribution. A distribution is negatively skewed when the long tail is on the negative side of the peak and positively skewed when the long tail is on the positive side of the peak. Generally, when mean is greater than mode, skewness is positive and when mean is less than mode, skewness is negative.

Kurtosis is a statistical measure that defines how heavily the tails of a distribution differ from the tails of a normal distribution i.e. it identifies whether the tails of a given distribution contain extreme values.

Jarque-Bera is a goodness-of-fit test; to test whether sample data have the skewness and kurtosis matching a normal distribution; usually employed to test the normality of the data set. The test statistics is always nonnegative. It is always positive and if it is not close to zero, it shows that the sample data do not have a normal distribution. The Probability measures the likelihood that an event will occur; usually measured between 0 and 1. The Sum is the addition of all the occurrences for the variable for the 25 years in view. The Sum Square Deviation is a measure of deviation from the mean. This was also reported for each variable. The sum of squares or sum of squared deviation scores, is a key measure of the variability of a set of data.

Unit Root Pre-Diagnostic Test

Unit Root Test is a pre-analysis test carried out before subjecting the data to any form of analysis. If the data has a unit root, the analysis on that data will be discontinued and vice versa. This study adopted the Augmented Dickey-Fully (ADF) Unit Root Test.

From the result in Table 3, it was evident that at level, TR was stationary as its ADF value (3.468590) in absolute terms was greater than the critical value (2.998064) at five percent level of significance. The ADF values for TRGDP in absolute terms was less than their critical value. Based on this outcome, there was a need to difference the nonstationary time series one more time to see whether the study would attain an overall stationarity. At first difference, TRGDP became stationary as its ADF value 3.964631 became greater than their critical values 3.004861 in absolute terms. Overall, it was evident that the Order of Integration was a mixture of I(0) and I(1). Based on this, the researcher employed the Autoregressive Distributed Lag (ARDL) technique in carrying out the empirical analysis (Taraba State Properties and Investment Ltd, 2021).

Table 3 Unit Root Test Result. Adf Unit Root Test
	ADF	ADF	0.05 Critical Values		Order of Integration
Variable	Level	1st Diff	Level	1st Diff
lnTRGDP	-1.328283	-3.964631	-3.004861	-3.004861	I(1)
lnTR	-3.468590	-	-2.998064	-	I(0)

Short Run Co-integration

This analysis will test the relationship between the dependent and independent variable in the short run. Short Run is a period considered on a short timescale. The Auto Regressive Distributed Lag (ARDL) was used and the result for short run co-integration is summarised in the Table 4 below.

From Table 4 above, the result showed that there was a positive relationship between tax revenue and real gross domestic product in Taraba State. From the result, 1 unit increase in tax revenue led to 0.1142 percent increase in real gross domestic product in Taraba State. The probability value of tax revenue (0.0079) was less than the test significant level (i.e. P < 0.05). Thus, the researcher concluded that tax revenue had positive and significant effect on real gross domestic product in Taraba State in the short run.

Table 4 Cointegrating Short Run Coefficients
Variable	Coefficients	Std. Error	t-Statistic	Prob.
D(lnTR)	0.114213	0.034532	3.307474	0.0079*
CointEq(-1)	-0.365829	0.135801	-2.693860	0.0225**

Secondly, the cointegrating equation error correction term (CointEq(-1)) had the correct sign and significant at 5 percent significant level. The value of the coefficient was 0.365829 and this meant about 36.58 percent of the disequilibrium in real gross domestic product of previous year’s shock had adjusted back to the long run equilibrium in the current year. It also implies that deviated real gross domestic product adjust to equilibrium with lags and only about 36.58 percent of the.

Long Run Co-integration

This analysis will test the relationship between the dependent and independent variable in the Long Run. Long Run is a period considered on a long timescale. In several instances, the results of relationship between the variables in the Short Run will change or vary in the Long Run. The most important result for decision making is the Long Run result. Therefore, irrespective of the Short Run result, some of which may not be favourable, the Long Run test is required for better decision making. The Auto Regressive Distributed Lag (ARDL) was used and result for Long Run co-integration is summarised in the Table 5.

From Table 5 above, the result showed that there was a positive relationship between tax revenue and real gross domestic product in Taraba State. From the results, 1 unit increase in tax revenue led to 0.506 units increase in real gross domestic product in Taraba State. The probability value of tax revenue (0.0311) was less than the test significant level (i.e. P < 0.05). Thus, the researcher concluded that value-added tax revenue had positive and significant effect on real gross domestic product in Taraba State in the long run. This finding corroborates Onwuchekwa & Aruwa (2014) who argued in favour of a positive and significant effect of value-added tax on economic growth in Nigeria.

Table 5 Long Run Coefficients
Variable	Coefficients	Std. Error	t-Statistic	Prob.
lnTR	0.505976	0.201901	2.506064	0.0311**
C	4.526759	1.182180	3.829163	0.0033

The tax revenue is then plunged into the provision of basic amenities to the populace which increases the standard of living of the people. As the standard of living of the people is enhanced, productivity increases and economic growth in Taraba State increases.

Summary of Findings

Tax revenue had a positive and significant effect on economic growth of Taraba State, both in the short run and long run.

Conclusion

The study investigated impact of non-oil sector revenue on economic growth in Taraba State Nigeria. In order to achieve this broad objective, the study specifically investigated effect of tax revenue. Tax revenue served as the explanatory variables while real gross domestic product served as the dependent variable. From empirical results, the study revealed that tax revenue had a positive and significant impact on economic growth of Nigeria in both the short run and long run.

Recommendations

An improvement in tax revenue will lead to economic growth. Tax revenue in Taraba can be improved through the following recommendations.

1. Instead of increasing tax rate as being suggested by many, the government should increase tax awareness, and improve tax collection using technology to bring a lot of people under the tax net.
2. The government should exercise the political will to implement the tax laws in respect to collections, enforcement and penalties for defaulters.
3. The government should create new avenues for generating taxes e.g. creation of toll gates for motorists.
4. Taraba State Board of Internal Revenue should be managed by technocrats (one technically skilled) not by a politician. Taraba state has the lowest IGR in Nigeria as at April 2022; not because she has the lowest economy but because (among other reasons) there are no technocrats managing that department.

References

Onwuchekwa, J. C., & Aruwa, S. A. (2014). Value added tax and economic growth in Nigeria. European Journal of Accounting Auditing and Finance Research, 2(8), 62-69.

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Osuala, A.E. (2010).  Econometrics: Theory and Problems. Umuahia: Toniprints Services.

Google Scholar

Taraba State Government Official Website (2021). Website: tarabastate.gov.ng

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Taraba State Properties and Investment Ltd. (2021). Taraba State Investment and Properties.

Google Scholar

Ugochukwu, O.S., & Azubike, J.U.B. (2016). Evaluation of the Contribution of Non-Oil Revenue to Government Revenue and Economic Growth:  Evidence from Nigeria. Journal of Accounting and Financial Management, 2(5), 41-51.

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Received: 30-Sep-2022, Manuscript No. AAFSJ-22-12632; Editor assigned: 01-Oct -2022, PreQC No. AAFSJ-22-12632(PQ); Reviewed: 14-Oct-2022, QC No. AAFSJ-22-12632; Revised: 18-Oct-2022, Manuscript No. AAFSJ-22-12632(R); Published: 25-Oct-2022