TAX REVENUE AND AGRICULTURAL PERFORMANCE: EVIDENCE FROM NIGERIA [629326]

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TAX REVENUE AND AGRICULTURAL PERFORMANCE: EVIDENCE FROM NIGERIA

ABSTRACT
The responsibility of the government of any economy cannot be overemphasized . Likewise, the
resources generated and infrastructural development helps to boost the economic growth of any
nation. There have been over dependency of Nigeria economy on the Oil sector the major source
of revenue. However, this sector has experienced sev eral challenges ranging from devaluation in
naira and fall in prices of crude oil in the international market . This serve s as a revelation for the
Nigerian government to seek an additional source of income. To this end, the main aim of this
paper is to examine the im pact of total tax revenue on agricultural performance in Nigeria. the
study uses Engel and Granger approach to cointegration to establish the long and short run
behaviour , we found that a positive and signific ant relationship exists between revenue obtained
in the agricultural sector, capital in agricultural sector proxy by loan and agricultural output, while
employment and total tax generated are not significant in the short -run. In the long-run,
employment, capital and total revenue are statistically significant with agricultural output while
tax is insignificant. The implication of the result showed that tax has not yielded des irable result
in promoting the agricultural sector in Nigeria. To promote pro -poor growth, long -run employment
and improve overall welfare, there is a need to incorporate benefit from tax into agricultural
performance . The study recommends among others the need for a systemic approach of given a
significant percentage of the total tax generated to boost the development of the agricultural sector.
Keywords: Agriculture Output , Taxation, Employment
JEL Classification: E62, O4

1. Introduction
The government of any economy is saddled with th e responsibility of increasing the welfare and
standard of living of its citizens, protection of lives and properties, provision of social welfare
service, maintenance of law and order and the promotion of econom ic development amongst
others. To carry out these functions, there is a need for various sources of revenue generation.
Guerra & Harr ington, (2018) noted that the revenue of a country could be generated via the
external and internal structured tax system. The amount of revenue generated also has impacted
the economic growth of such nation. Generally, taxation is a sustainable and authentic source of

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government income and an instrument for ma cro-economic policy and fiscal management. Saad,
(2014) described taxation as an instrument for social and economic reforms that perme ates every
facet in the economy including individuals, corporation s, citizens and foreigners. As an economic
tool, (Bayer & Cowell, 2016 ; Uwuigbe, Uwuigbe, Jafaru, Iginoba, & Oladipo, 2016 ) equates its
efficiency to power to destroy.
Mittone & Saredi, (2016) see taxation as a tool employed in order to ensure the redistribution of
economic wealth and to ensure socio -economic growth . Developed counties have a well-
structured tax system and thus enable them to generate a significant amount of their annual
revenue from the tax. Examples of such countries are the United States of America (USA),
United Kingdom (UK), Canada and the Netherlands. As a result of this, economic growt h has
been boosted. Taxation is also one of the major sources of revenue in the country but due to
mismanagement, leakages and corruption in the system, the revenue generated annually is
affected (Eluyela et al., 2019 ; Asaleye et al, 2018 ). Although taxati on contributes a significant
amount to the country's GDP, Nigeria's tax contribution is seen as the lowest compared to that of
other countries. PricewaterhouseCoopers (PwC) stated that Nigeria’s tax contribution to GDP is
the lowest in the world when compa red to other nations. The highest value of tax to GDP is 5.46%
in 2008 w hile the lowest value is 0.91% (Onwe, 2015) .
On the other hand, a griculture is seen as the bedrock of any economy especially in Africa
(Adama, Asaleye, Oye & Ogunjobi, 2018) . Solid rock economies are built on its ability to explore
its potentials and opportunities using Natural resources, except in technologically developed
countries like Japan. Agriculture plays a vital role in the nati onal development of the most
developed economy. They see agriculture as a means of reducing over dependency on some
particular sector or activities of the economy like oil sector. Some benefits that will accrue to
such countries are an increase in the rate of exportation, enhancement of foreign exchange ,
provision of employment opportunities, reduction in poverty levels and contribu tion to economic
growth (Ojeka, 2016 ; Asaleye at al., 2018 ). In 1960, the agriculture s ector contri butes to about
70 per cent of Nigerian exports. This later reduced to 40 per cent in late 1970 and gradually
decreases to 2 per cent in the late 1990s. In recent times , agriculture has been neglected by the
majority in Nigeria . Agriculture is only practised on a small scale in rural societies of the country.
Although Nigeria has been described as one of the top countries endowed with natural resources

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and massive land area, only 40% of its land area is cultivated and used for agricultural purposes.
There is a lack of motivation amongst the farmers due to lack/poor financing, poor transportation
due to bad roads and also lack of market (people rather import foods).
Strands of literature exist between Taxation and Agriculture as tools for Economic Grow th
(Omorogiwa, Zivkovic and Ademoh, 2006; Simeon and Marinos, 2009; Worlu and Emeka, 2012;
Afuberoh and Okoye, 2014 ; Guerra & Harringt on, 2018) but most of these studies ignored the
relationship between taxation and agricultural performance. In addition , vast literature has
provided different revelations, opinions and explanations of taxes, a griculture, and its
relationship with the economic growth of the country. Worlu and Emeka (2012) examined the
relationship between tax revenue and economic development in Nigeria usi ng a macro -economic
approach. The study by the authors show s that tax revenue influences economic growth via
infrastructural development. Similarly, Afuberoh and Okoye (2014) assessed the impact of
taxation on revenue generation in Niger ia. The sample size used was the federal capital city and
some selected states. Findings from the regression analysis showed that a significant relationship
exists amidst taxation and revenue generation. Also, the study shows that taxation has a
significant contribution to t he Gross Domestic Product (GDP). More so, u sing the ordinary least
square (OLS) regression technique, Onwucheka and Aruwa (2014) examined the impact of value –
added tax on economic growth in Nigeria. Findings from the study reveal that Value -added Tax
(V AT ) contributes greatly to the total tax revenue of the government and ultimately have a
significant effect on economic growth in Nigeria.
Consequently, Adegbie and Fakile (2011) further examined the impact of company income tax
on economic growth in Nigeri a. The study used chi -square and multiple regression analysis.
Results from the scholars’ study show that a significant consonance exists between company
income tax and economic growth of Nigeria. The study highlighted tax evasion and avoidance as
major hi ndrances to revenue generation. Nwadialor and Ekezie (2016) observed the effect of tax
policy on economic growth in Nigeria. The study observed 19 years of data from 1994 -2013.
Ordinary least squares regression analysis was used to analyse the study data. The findings
revealed that tax has a significant effect on Economic growth in Nigeria . Tolulope and Chinonso
(2013) used Granger causality test to observed the contribution of Agriculture to economic
growth in Nigeria. They discovered that the agricu ltural sector has contributed positively and

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consistently to economic growth in Nigeria, reaffirming the sector's importance in the economy.
Simeon and Marinos (2009) used the simulations model to examine the role of Agriculture in
Nigeria’s economic growt h. The result shows that some subsectors in the agricultural sectors
outperform some of the oil and manufacturing sectors in terms to return in investments.
Omorogiwa, Zivkovic and Ademoh (2006) assessed the role of Agriculture in the economic
development of Nigeria. The study used trend analysis. Results from the findings revealed that it
is plausible for Nigeria to diversify into the agriculture market in their effort to become more
self-sustainable and a world economic power. However, despite different s tudies established a
strong connection between tax and economic growth in Nigeria, the implication on agricultural
performance have not been looked into. Likewise, mismanagement of resources, inconsistency
of policies, low capital and investment rate have been pointed by scholars as main issues affecting
the development of the Nigerian economy (Asaleye, Adama & Ogunjobi, 2017; Ogundipe,
Ogunniyi, Olagunju & Asaleye, 2019).
Tax can be seen as a compulsory obligation imposed by the public authority on taxpa yers. This
is irrespective of the amount of service rendered to the taxpayer (Perez -truglia & Troiano, 2018) .
In simple terms, tax can be seen as a contribution from taxpayer to revenue generation of an
economy. This source of government revenue assists the government in providing and meeting
public needs. Tax may be imposed on income, properties, land and goods or services (Modan,
2016). Against this backdrop, the main aim of this study is investigate the implication of tax
revenue on agricultural performance in Nigeria.
2. Model Specification and Technique of Estimation
Following the study by Popoola, Asaleye and Eluyela (2018) that examines the relationship
between domesti c revenue mobilization and agricultural productivity, the empirical model for this
study is slightly adjusted and given as:
( , , , ) AGDP f EAGR CAGR TAGR TAX=
2.1
Equation 2.1 is the implicit form of the model, where AGDP is the output in the agricultural sector.
EAGR is employment in agricultural sector, CAGR is capital in agricultural sector, TAGR is
agricultural revenue while TAX is the total revenue. The model can be explicitly given as:
0 1 2 3 4 t t t t t t AGDP EAGR CAGR TAGR TAX     = + + + + +
2.2

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In equation 2.2,
0 is the intercept where
1 ,
2,
3 and
4 are the parameters on the independent
variables EAGR, CAGR, TAGR and TAX respectively. ‘t’ is the period of observation.
Theoretically, it is assumed that EAGR and CAGR have a positive relationship with AGDP. This
is directly from the output model, capita l and employment are essential to increase the aggregate
output. Likewise, increase in revenue is presumed to have a positive response on output. This is as
a result of increase in economics of scale ini tiating a positive response on productivity, sales an d
income. Th e implication of tax can be neutral, positive or negative depending on the objectives
and implementation to the tax system.
Equation 2.2 is estimated using Engel -Granger approach to cointegration. This approach is chosen
based on its strength and suitability. Firstly, the stochastic properties of the time series are tested
using the Augmented Dickey -Fuller (ADF) approach. Estimate non -stationary series with ordinary
least square may result in spurious regression. The ADF on the other hand has b een popular in the
literature to investigate stationarity in time series. After the ADF test and if the outcome shows
that all series are integrated of the same order, that is order 1. The Engel and Granger give a suitable
one equation, which can be used to investigate the long -run behaviour and short -run dynamics.
The cointegration among the non -stationary data involves matching the degree of the series and
ensure that the error term and the residual of the estimated equation became stationar y; this helps
to overcome the spurious regression. Assuming the series
tM and
tN are both non -stationary, that
is
()Id , then the linear combination
t t tJ M aN− , will also be
()Id . Hence, if
tM and
tN are
(1)I
with dominant long -run components. Therefore,
tJ is
(0)I . The long -run equation and short –
run dynamics can be estimated.
Output (AGDP) in equation 2.2 is proxy by agriculture contribution to GDP, Capital (CAGR) is
proxy by loan credit given to agriculture sector, Agriculture employment (EAGR) is proxy by
employment in agricul tural sector, Revenue from agriculture (TAGR) is proxy by total income in
agricultural sector and Amount of Tax (TAX) is proxy by total tax generated. AGDP and CAGR
are sourced from Nigerian Central Bank Statistical Bulletin (Various issues), EAGR is obt ained
from Nigerian National Bureau of Statistics, TAX and TAGR are obtained from Federal Inland
Services, Nigerian Budgetary of Federation and Nigerian Institute of Social and Economic
Research . Finally, the study carried out diagnostics' checks to determine if the model is correctly

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specified. For a model to be correctly specified, the residual must be normally distributed, the
variance of the residual must be equal over time, and the residuals must not be serially correlated
(Asaleye, Lawal, Popool a, Alege & Oyetade, 2019; Fashina, Asaleye, Ogunjobi & Lawal, 2018) .
3. Presentation of Result
In this section, we provided the unit root test (using Augmented Dickey -Fuller test) to know which
variable is stationary at either first or second difference. Following the unit root test, we presented
the least square results that show the relationship b etween the dependent and independent
variables.
3.1 Result of Stationary Test (Unit Root Test)
Table 3.1 Unit Root Test
Variables ADF Statistics Prob. Critical Values Order
AGDP -4.164263
0.0075
1% -4.004425
5% -3.098896
10% -2.690439 I(1)
EAGR -5.885864 0.0001 1% -3.632900
5% -2.948404
10% -2.612874 I(1)
CAGR -5.073177 0.0002 1% -3.632900
5% -2.948404
10% -2.61287 4 I(1)
TAGR -4.318265 0.0073 1% -4.121990
5% -3.144920
10% -2.713751 I(1)
TAX -4.953909
0.0019 1% -4.004425
5% -3.098896
10% -2.690439 I(1)
Source: Authors Compilation (2019 )
Table 3.1 presents the unit root result using Augmented Dickey -Fuller (ADF). The null hypothesis
that the series are not stationary is tested at level and first differenced forms. All the series are not
stationary at the level form. However, the series became stationary at the first -differenced forms
at 5 per cent significance level since the probability values are less than 5 per cent. Also, using 5
per significa nce level, the ADF statistics in table 1 in absolute terms is greater the critical values
at 5 per cent for all the series, this indicates that null hypothesis is rejected and all series are
integrated of order one. The ADF statistics for AGDP, EAGR, CAGR , TAGR and TAX are –
4.164263, -5.885864, -5.073177, -4.318265 and -4.953909 respectively , in absolute term are

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greater than their corresponding critical values of -3.098896, -2.948404, 2.948404 , -3.144920 and
-3.098896 .
Table 3.2: Presentation of Short -run Dynamics
Dependent Variable: AGDP
Variables Coefficient Standard Error T – Statistics Prob.
Constant -9.584773 6.125410 -1.564756 0.1269
EAGR 0.000336 0.000181 1.856782 0.1441
CAGR 0.002111 0.000378 5.586672 0.0000
TAGR 0.001596 0.000731 2.183 310 0.0440
TAX 0.007476 0.006164 0.824563 0.5453
ECM -0.045013 0.002482 18.13844 0.0000
Source: Authors Compilation (2019 )
Table 3. 2 presents the short -run dynamics result since the series is not stationary; hence, the Error
Correction Model (ECM) or Engel and Granger approach is most suitable. The ECM shows the
short -run behaviour and the long -run behaviour. The significance of the error correction term,
indicated by ECM in table 3 .2 validate that there is long -run behaviour among the series. The ECM
must be negative, less than one and significant to capture the speed of adjustment and confirm the
long-run implication. It is depicted from the table 3 .2 that the system will adjust at the rate of 4 per
cent yearly give n the value of the ECM is -0.045013 , whic h is statistically significant at the level
of 5 per cent since the probability value is 0.0000 which is less than 5 per cent. The independent
variables are EAGR, CAGR, TAGR and TAX, while AGDP is used as the depend ent variable.
The constant term, EAGR and TAX are not statistically significant at the level of 5 per cent since
the corresponding probability values of 0.1269 , 0.1441 and 0.5453 are greater than the value of
0.05. The variables CAGR and TAGR are statistic ally significant. Hence, the short effect is as
follows; h olding all the variables constant, one unit change in CAGR will cause approximately 0.2
per cent increment in agricultural output. Also, holding all the variables constant, one unit change
in TAGR w ill cause approximately 0.7 per cent increment in the output.
Table 3.3: Presentation of Long -run R elationship
Dependent Variable: AGDP

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Variables Coefficient Standard Error T – Statistics Prob.
Constant -0.991340 0.008962 -11.06102 0.0000
EAGR 0.002111 0.000378 5.586672 0.0000
CAGR -0.000586 0.001223 -2.10856 0.0417
TAGR 0.000079 0.000037 2.135135 0.0412
TAX -0.0131918 0.155839 -0.08465 0.3524
R-Squared: 0.776763 F- Statistics: 27.83635 Prob. (F -Statistics): 0.0000
Durbin -Watson Statistics: 2.275916 Adjusted R -Squared: 0.748858
Source: Authors Compilation (2019 )
Table 3 .3 presents the long -run effects. The Durbin –Watson statistics value is 2.275916, which is
close to two, within the region of no autocorrelation. The R -squared and the adjusted R -squared
is the coefficient of determination, which measure the goodness of fit. A value more than 50 per
cent shows that more of the variation in the dependent variable is been explained by the
independent variables. The R -squared and the adjusted R -squared values are 0.776763 and
0.748858 respectively; this shows that there is a good fit since more than 70 per cent variations in
the dependent variable is been explained by the independent variables. The F -statistics measure
the joint significance of the variable. The value of the F -statistics is 27.83635, with the probability
value of 0.0000, which is less than 5 per cent. Hence, the independent variables jointly explained
the dependent variable at the level of 5 per cent. T he variable TAX has probability value of 0.3524 ,
which is not statistically significant at the level of five per cent. The variables EAGR , CAGR and
TAGR have the probability values of 0.0000 , 0.0417 and 0.0412 respectively, which are
statistically signific ant at the level of five per cent. EAGR and TAGR have positive relationship
with AGDP while CAGR has a negative relationship with AGDP. Holding all other variables
constant, one unit change in EAGR will increase AGDP about 0.2 per cent while; holding all other
variables constant, one unit change in TAGR will increase AGDP with about 0.0079 per cent. For
CAGR, one unit change in the variable will cause about 0.0586 per cent reduction in AGDP.
Table 3.4: ECM Unit Root Test and Diagnostic Checks
Residual Unit Root Test
ECM ADF Statistics Prob. Critical Values Order
-11.06102 0.0000 1% -3.626784 I(0)

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5% -2.945842
10% -2.611531
Diagnostic Checks
Chi-Square Value Jarque -Bera Stat Prob.
Serial Correlation 3.671540 – 0.1595
Heteroskedasticity Test 1.594381 – 0.2067
Normality Test – 0.847748 0.6545
Source: Authors Compilation (2019)
Table 3 .4 presents the ECM unit root result and the diagnostic checks. The ADF statistics of the
ECM is -11.06102 with a probability value of 0.0000. Also, the absolute term of the ECM
(11.06102) is greater than absolute value of the critical value at 5 per cent (2.945842). Hence, the
ECM is stationary at the level. Based on the outcome of the unit root test of the residual (ECM),
the study pro ceed with Engel Granger approach to cointegration to establish the long and short
behaviour exp lained in table 3.2 and 3 .3. The diagnostic checks using the LM serial correlation,
ARCH and Histogram normality test was used to determine if the model is corre ctly specified.
Since all the probability is greater than 0.05; it means the null hypotheses of model without serial
correlation, ARCH effect and errors not normally distributed cannot be accepted. Therefore, in the
model, the errors are not serially corre lated, the variance of the errors is constant over time and
there is normal distribution of the errors.

3.5 Implications of Result
This study investigates the relationship b etween agricultural output and taxation in Nigeria. The
agricultural sector in recent times have been identified by Nigerian government has one on the
sector under -utilized to generate employment and potential increase in income. In order to promote
sustainable growth through this sector by enhancing employment generation, increase income per
capita and reduce poverty rate, this study follows Enger -Granger approach to cointegration to
establish the short and long -run behaviour. Agricultural output is used as dependent variable and
the independent variables considered are employment in agricultural sector, capital in agricultural
sector proxy by loan to the sector, total revenue of agricultural sector and amount of tax generated.
After considered the stochastic properties of the time series used in this study, it was observed that

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all the series and not stationary at the level form. However, there were integrated of order one.
Based on this outcome, the study proceeds to estimate the Error Correction Model (ECM) also
known as Engel and Granger approach to cointegration. The model showed the short and long -run
behaviour. Evidence from the short run relationship showed that employment and amount of tax
generated is not statistically significant with agricultural output. This outcome contr adicts the
study by Guerra and Harrington (2018) that stressed that tax has positive influence on the economy.
The implication of this findings displayed that despite all the efforts geared by Nigerian
government towards promoting immediate employment, to increase income per capita, low the
poverty rate, improve overall welfare, among others have not achieved desirable result. Many
reasons might be responsible for this , among others include mismanagement of resource,
inconsistent in the policies or resource targeting long -run goals in agricultural sector . More so, it
was evident that revenue obtained from tax have not been utilized to develop the agricultural
sector. However, capital in agricultural sector proxy by loan to the sector and total revenue
genera ted are statistically significant in the short -run.
In the long -run, evidence from the result showed that employment, capital and revenue from
agricultural sector are statistically significant with agricultural output. However, amount of tax
generated is not significant. The finding refutes the findings of Worlu and Emeka (2012), Afuberoh
and Okoye (2014) in Nigeria. The disparity in the findings are based on the scope and objectives
of the studies. For example, Worlu and Emeka (2012) focused on aggregate growth while the study
by Afuberoh and Okoye (2014) limited the scope to the Nigerian Federal capital city and some
selected states. The general conclusion from this study is that the amount obtained from tax or tax
revenue have not promoted growth in the agricultural sector. Despite the importance of the
agricultural sector to promote lon g-run employment. Financing agriculture sector for long -run
benefit may not be suitable to promote sustainable growth a nd development. Such outcome could
be achieved through promoting the sector with less liability. Hence, it is important to ensure there
is linkage between tax generated and agricultural performance in Nigeria.
4 CONCLUSION AND RECOMMENDATIONS
The conclusion drawn from this study is that Nigeria still faces administrative challenges as
regards taxation and societal challenges as regards agriculture. Before the fall of the Nigerian
Naira, the Nigerian economy was heavily dependent on crude oil export receipts. Therefore, the

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potentials of t axes and agriculture as a major source of revenue for the economy has not been
exploited. The need to expand the tax revenue by improving tax system and administration has
become a major economic issue. Furthermore, the various bottlenecks of tax and agric ultural
development in Nigeria such as lack of personnel, lack of facilities, multiple taxes, cumbersome
process of payment and lack of government participation, mismanagement of resources, high
transportation cost, lack of technical knowledge respectively . The study recommends the
following: systemic approach of given significant percentage of the total tax generated to boost
the development of the agricultural sector. There should be proper staff training annually, t his is
to ensure they are up to date with the latest technology and issues in taxation. This will help to
reduce the level of mismanagement of resources. The government should provide special grants
and soft loans with little or no interest to farmers in order to encourage the agricultur al activities.
Likewise, in order to enhance the agricultural knowledge of the farmers, agricultural programs can
be held in order. This would enable the farmers to adopt new methods of agriculture and improve
their outputs. More so, in order to improve yo uth interest and participation, agriculture can be
included into to the course outlines and taught in Nigerian institutions.
A research of this nature cannot effectively cover every area or issue of concern considering the
scope and goal of the study . The following are the researchers suggested area for further studies:
to examine the effect of rural and urban migration on agricultural sector. Also, investigate the
implications of tax on agricultural employment and output in general equilibrium framewor k.
References
Adegbie, F. & Faklie, S. (2011). Petroleum Profit Tax and Nigeria Economic Development.
International Journal of Research in Computer Application & Management , 11-18.
Adama, I.J., Asaleye, A.J., O ye, A.J., Ogunjobi, O.J. (2018). Agricultural Production in Rural
Communities: Evidence from Nigeria. Journal of Environmental Management and
Tourism , (Volume IX, Summer), 3(27): 428 -438. DOI:10.14505/jemt.v9.3(27).04

Afuberoh, D., & Okoye, E. (2014). The Impact of Revenue Generation in Nigeria: A Study of
Federal Capital Territory and Selected States. International Journal of Public
Administration and Management Research , 22-47.
Asaleye A.J, Isoha L.A, Asamu F., Inegb edion H., Arisukwu O., & Popoola O. (2018). Financial
Development, Manufacturing Sector and Sustainability: Evidence from Nigeria, The
Journal of Social Sciences Research, 4 (12), 539 -546,
https://d oi.org/10.32861/jssr.412.539.546

12

Asaleye A.J, Adama J.I. and Ogunjobi J.O. (2018). Financial sector and manufacturing sector
performance: evidence from Nigeria. Investment Management and Financial Innovations,
15(3), 35 -48. http://dx.doi.org/10.21511/imfi.15(3).2018.03

Asaleye A.J, Lawal A.I, Popoola O., Alege P.O & Oyetade O.O. (2019). Financial Integration,
Employment and Wages Nexus: Evidence from Nigeria, Montenegrin Journal of
Economics, 15 (1): 141 – 154 , doi.10.14254/1800 -5845/2019.15 -1.11

Asaleye A.J, Popoola O., Lawal A.I, Ogundipe A.and Ezenwoke O. (2018). The c redit channels
of monetary policy transmission: implications on output and employment in Nigeria. Banks
and Bank Systems, 13(4), 103 -118. http://dx.doi.org/10.21511/bbs.13(4).2018.10

Bayer, R., & Cowell, F. (2016). Research in Economics Tax compliance by firms and audit policy.
Research in Economics , 70(1), 38 –52. https://doi.org/10.1016/j.rie.2015.07.003 \
Eluyela, D.F., Akintimehin, O.O., Okere, W., Ozordi, E., Osuma, G.O., Ilogho, S.O., Oladipo , O.A.
(2018). Datasets for board meeting frequency and financial performance of Nigerian
deposit money banks. Data in brief, 19, 1852 -1855.
https://doi.org/10.1016/j.dib.2018.06.044 .
Eluyela, D.F., Akintimehin, O.O., Okere, W., Ozordi, E., Osuma, O.G., Ilogho, S.O., Oladipo, O.A.
(2018). Board meeting frequency and firm performance: examining the nexus in
Nigerian deposit money banks. Heliyon, 4, https://doi.10.1016/j.heliyon.2018.e00850 .
Eluyela, D.F., Adetula, D.T., Oladipo, O.A. Nwanji. T.I., Adegbola, O. Ajayi, A., & Falaye, A.
(2019 ). Pre and post -adoption of IFRS based financial st atement of listed small -medium
scale enterprises in Nigeria . International journal of civil engineering and technology ,
10(1) , 1097 -1108.
Fashina, O. A., Asaleye, A.J., Ogunjobi, J.O., & Lawal, A.I. (2018). Foreign aid, human capital
and economic growth ne xus: Evidence from Nigeria. Journal of International Studies,
11(2), 104 -117. doi:10.14254/2071 -8330.2018/11 -2/8
Guerra, A., & Harrington, B. (2018). Journal of Economic Behavior and Organization Attitude –
behaviour consistency in tax compliance : A cross -national comparison. Journal of
Economic Behavior and Organization , 156, 184 –205.
https://doi.org/10.1016/j.jebo.2 018.10.013
Laffer curve. (n.d.). Retrieved from Investopedia:
http://www.investopedia.com/terms/l/laffercurve.asp
Laffer curve. (n.d.). Retrieved from Wikipedia: https://en.wikipedia.org/wiki/Laffer_curve
Laffer curve Definition & Example. (n.d.). Retrieve d from Investinganswers:
http://www.investinganswers.com/financial -dictionary/economics/laffer -curve -3533
Mittone, L., & Saredi , V. (2016). Commitment to tax compliance : Timing effect on willingness

13
to evade. JOURNAL OF ECONOMIC PSYCHOLOGY , 53, 99 –117.
https://doi.org/10.1016/j.joep.2016.01.001
Nwadialor E. & Ekezie C.A. (2016 ). Effect of Tax Policy on Economic Growth in Nigeria (1994 –
2013) , International Journal of Business Administration , Internationa l Journal of Business
Administration, 7(1), 50-58.
Ogundipe A.A., Ogunniyi A., Olagunju K.S. and Asaleye A.J. (2019). Poverty and Income
Inequality in Rural Agrarian Household of Southwestern Nigeria. The Gender Perspective,
The Open Agriculture Journal, 1 3 – 00 -00

Omorogiuwa, O., and Zivkovic, J., and Ademoh, F. (2014). The Role of Agriculture in the
Economic Development of Nigeria. European Scientific Journal , 133 -147. Retrieved from
133-147

Ojeka, E. C. (2016). Constraints To Agricultural Development In Nigeria. International Journal
of Development and Economic Sustainability , 1-15.
Onwe, G. (2015). The Impact Of Taxation Non -Economic Growth In Nigeria. Global Journal of
Applied, Management and Social Sciences (GOJAMSS) , 25-31.
Onwuchekwa, J.C & Aruwa S.A.S (2014) Value Added Tax and Economic Growth in Nigeria.
European Journal of Accounting, Auditing and Finance Research , 2(8), 62-69
Perez -truglia, R., & Troiano, U. (2018). Shaming tax delinquents ଝ. Journal of Public Economics ,
167, 120 –137. https://doi.org/10.1016/j.jpubeco.2018.09.008
Saad, N. (2014). Tax Knowledge, Tax Complexity and Tax Compliance : Taxpayers ' View.
Procedia – Social and Behavioral Sciences , 109(1), 1069 –1075.
https://doi.org/10.1016/j.sbspro.2013.12.590
Simeon E., & Marinos T. (2009). The Role of Agriculture in Nigeria's Economic Growth: A
General Equilibrium Analysis. Conference of the International Association of Agricultural
Economists (IAAE) , (pp. 0 -12). Beijing, China.
Uwuigbe, O.R., Uwuigbe, U., Jafaru, J ., Iginoba, E.E & Oladipo, O.A. (2016). Value relevance of
financial statements & share price: A study of listed banks in Nigeria, Banks and Banks
System, 11(4), 135 -142.
Worlu C.N., & Emeka N. (2012). Tax Revenue and Economic Development in Nigeria: A
Macroeconometric Approach. Academic Journal of Interdisciplinary Studies , 211 -2