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Capital vs Recurrent: The Challenge of Nigerian of Economic
Growth
Abarigu Prekebina Claudius Ph.D
University of Port-Harcourt, Yenagoa, Bayelsa Sate, NigeriaYenagoa, Bayelsa Sate, Nigeria
DOI: https://dx.doi.org/10.47772/IJRISS.2025.914MG00190
Received: 01 October 2025; Accepted: 07 October 2025; Published: 08 November 2025
ABSTRACT
This study compared the effect of capital and recurrent expenditure on Nigeria economic growth. The objective
was to compare the effect capital and recurrent expenditure on Nigeria economic growth. Time series data were
collected from Central Bank of Nigeria Statistical Bulletin from 1990-2021. Real gross domestic product was
modeled as the function of capital and recurrent expenditure on administration, social services, economic service
and transfer. Ordinary least square method, Augmented Dickey Fuller unit root test, cointegration, granger
causality test and vector error correction was used as data analysis methods. The study found adjusted R-Square
of the capital expenditure is 0.355303 while the recurrent expenditure is 0.341396. This indicates that capital
expenditure explained 35.5 percent while recurrent expenditure explained 34.1 percent variation in Nigeria
economic growth. The two models were statistically significant when judged by the value of F-statistic and
probability. Capital expenditure on administration added 0.73 on Nigeria economic growth while recurrent
expenditure on administration reduced economic growth by 6.3 percent. Capital expenditure on economic
service added 0.86 while recurrent added 8.94 percent on economic growth, capital expenditure on social
services added 0.98 while recurrent added 3.88 percent, capital expenditure on transfers added 0.93 while
recurrent reduced by 0.1 percent. From the findings, the study conclude that capital expenditure has greater effect
on economic growth than recurrent expenditure. The study recommends more budget allocations to capital
expenditure than recurrent expenditure for better economic growth.
INTRODUCTION
Public expenditure plays an important role in the aggregate economy in different ways. It is used to produce
various public goods and services such as infrastructural development which the market system cannot provide
due huge cost. It is also used by the government to adopt various fiscal measures such as capital investment to
stimulate economic activities particularly in the developing economy where there is abundant idle resources and
during recession. Public expenditure is a kind of government intervention on economic activities to bridge the
market imperfection as advocated by the Keynesian economists.
Public expenditure was justified due to the inefficiencies of the private sector to bridge gap between private and
social goods (Okpara, 2002). The limitation in the price system or market mechanism gave impetus to the need
for government intervention in the economic system through spending. The limitations revealed the failure of
self-adjusting principle of the classical era and provide support to the Keynesian thesis that government is the
best guidance of a nation’s economy (Ezirim, 2005).The importance of public expenditure was widened by
interest of economists in the problems of economic growth, planning regional disparities and income distribution.
Public expenditure is an injection into the income stream, it is a mechanism to stimulate demand and widen the
output of the economy as advocated by Keynes. Jhingan (2006) stated that the role of the public expenditure in
economic development lies in increasing the growth rate of the economy, providing more employment
opportunities, raising income and standard of living, reducing inequalities of income and wealth, encouraging
private initiative and enterprise, bringing about regional balance, and stabilizing the economic activities.
Government capital expenditure refers to government spending on investment goods. It is government long-term
expenditure plans that can affect the industrial sector of the economy. It means spending in things that last for a
period of time which may include investment in roads, industries, equipment, agriculture CBN (2011) noted that
capital expenditure is fiscal expenditure on goods classified as investment goods. As a component of fiscal
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policy, capital expenditure if well managed has the capacity of increasing the productive capacity of the industrial
sector, create employment and improve capacity utilization Aregenyen (2007). In Nigerian, capital expenditure
is classified as economic services, social and community services, transfer and administration. The role of
government capital expenditure on the growth of industrial sector has been a growing concern despite the fact
that various policies have been formulated to improve the performance of the sector. Government capital
expenditure has increase over the years without corresponding increase on the growth of the industrial sector.
Empirical evidence and theories have shown that well plan government capital expenditure have the capacity of
increasing the productive capacity of the industrial sector and the economy.
In Nigeria, government recurrent expenditure has continued to rise especially since the inception of the
democratic era which began in 1999. Available data by the Central Bank of Nigeria (2016) revealed that
government recurrent expenditure recorded an upward movement in all the years under study except in 2013.
From a total sum of N449.66bn in 1999 up to N3,325.16bn in 2012 and it declined a bit to N3,214.95bn in 2013.
In 2014, it commenced an upward movement form N3, 426.94bn to N4, 177.59bn in 2016, N5, 675.20bn in
2017, N6, 997.20bn in 2018, N8,188.81bn in 2020 and N9,1145.16bn in 2021. On the overall, the trend
revealed a consistent increase in recurrent expenditure of government. This ever-increasing government
recurrent expenditure has attracted lots of criticisms and complaints from a good number of citizens who argue
that the government was wasteful and that the much spent on servicing recurrent component of the government
should have been channeled to capital projects (Ijaiya, Sanni & Olanrewaju, 2017, Nurudeen & Usman, 2010).
The impression created by the above argument is that recurrent expenditure does not increase economic growth
in Nigeria. This study compared the effect of recurrent expenditure and capital expenditure on economic growth
in Nigeria.
REVIEW OF RELATED LITERATURE
Capital Expenditure
Capital expenditure refers to the amount spent in the acquisition of fixed (productive) assets (whose useful life
extends beyond the accounting or fiscal year), as well as expenditure incurred in the upgrade/ improvement of
existing fixed assets such as lands, building, roads, machines and equipment. including intangible assets. Federal
Government Expenditure in research also falls within these components of these expenditures. Capital
expenditure is usually seen as expenditure creating future benefits, as there could be some lags between when it
is incurred and when it takes effect on the economy.
Capital expenditure are budgeted expenses incurred by the government of any economy to ensure the certainty
of projects execution which are of economic benefit to the government, citizens and economy of the country.
The federal government capital expenditure over time has covered major infrastructures in the economic which
includes; construction and rehabilitation of federal roads, fixed assets for the administration of the federal
government running of its activities, agriculture equipment, power supply, industrialization for economic
services, building of hospitals, schools and social amenities for social community services, payment of debts
owed locally and internationally by the government to liquidate its debts obligations as transfers. All these
expenditures are categorized as major expenditure which only the federal governments will solely take
responsibility in ensuring that these facilities and services are being provided for the growth of its economy.
Osiegbu et al (2010) posited that the federal government capital expenditure is another means of stimulating the
economic growth of Nigeria by means of its fiscal policies consideration. When the federal government seems
to boost the economy activities, it executes projects through the approved budgeted funds meant for its capital
expenditure for that year. In other words, it is termed the federal government capital expenditure fiscal year
policy; since it is possesses the characteristics and role of fiscal policy towards the growth of an economy then
federal government capital expenditure should be a fundamental element of economic variables which could
characterize the well-being of productivity within the Nigerian economy.
Recurrent Expenditure
Recurrent expenditure on the other hand refers to expenditure on purchase of goods and services, wages and
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salaries, operations as well as current grants and subsidies (usually classified as transfer payments). Recurrent
expenditure, excluding transfer payments, is also referred to as government final consumption expenditure.
Recurrent expenditure in Nigeria can be disaggregated into four; administration, SCS, ES and transfers,
classified under economic functions/obligations of government, while Administration (Defense, internal security
and general administration) is classified as non-economic function/obligation of government.
Economic Growth
Economic Growth refers to the ability of an economy to improve its production of goods and services over a
period of time using the factors of production within the economy (Popkova, Shakhovkaya, & Mitrakhovich,
2008). Economic Growth is usually calculated in real terms thus inflation-adjusted terms to eliminate the
distorting effect of inflation on the price of goods produced. Several theories have been developed to explain the
economic growth of a country.
Rostow, an American economist developed the Rostow’s Stages of Growth model in which it explains the idea
about the transition of an economy from underdevelopment status to a developed status through various stages
a country must precede. Thus, a country must precede from a traditional stage (in which the foundations for
growth are based on subsistence production) to a “take off” stage (in which development starts to accelerates),
to a matured stage of development. Roy – F Harrod in 1939 and Evsey Domar in 1947 also developed the Harrod
- Domar Growth model from the Keynesian model. The model with specific assumptions such as a scarce capital
resource, constant capital and output with consumption and savings being a constant proportion of income, the
main thrust of the model was that the rate of savings was the principal determinant of the growth of the economy
under given levels of productivity of capital (incremental capital output ratio) and a state of technology.
The Keynesian Theory
In the Keynesian macroeconomics, an increase in government expenditure has an expansionary effect on income
and employment through the multiplier effects on aggregate demand. On the other side, government expenditure
crowds out private investment as a result of an increase in the rate of interest and this slows down economic
growth and reduces the rate of capital accumulation in the long run. Keynes (1936) regarded government
expenditure as an exogenous variable that contributes positively to economic growth. Hence, an increase in
government expenditure would likely lead to an increase in employment, profitability and output through the
multiplier effects on aggregate demand. With the introduction of government expenditure (G) by Keynes, the
national income determination model is expanded which becomes;
AD=C+I+G
Where, AD represents aggregate demand, which equals the sum of consumption (C), Investment (I), and
government expenditure. Government expenditure has a direct and positive impact on GDP. An increase in
government expenditure will boost aggregate demand, resulting in a higher level of national income. All things
being equal, an increase in government spending has an expansionary effect on output and income while a
decrease has a contractionary effect on output and income. The neoclassical growth models argued that
government fiscal policy does not have a positive effect on the growth of an economy. On the contrary, a
significant number of scholars have agreed that fiscal policy is a potent tool for promoting growth and improving
failures arising from the inefficiencies of the market. Hence, government fiscal policy could be a vital tool for
militating against failure arising from market inefficiencies (Abu, 2010).
Adolph Wagner’s Theory of Increasing State Activities
The earliest of all theories of government growth is Wagner’s Law of Increasing State Activity. This theory
posits a relationship linking industrialization, urbanization and education to the expansion of the public sector.
Bird (1971) the activities of the different tiers of government (federal, state and local) increase both intensively
and extensively arising from the increasing demand for public utilities. Wagner advanced the theory of rising
public expenditure by analyzing the trend in the growth of government expenditure and the size of government
expenditure. Wagner’s law postulates that: (i) the extension of the functions of the states leads to an increase in
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public expenditure on administration and regulation of the economy; (ii) the development of modern industrial
society would give rise to increasing political pressure for social progress and call for increased allowance for
social consideration in the conduct of industry (iii) the rise in public expenditure will be more than proportional
increase in the national income (income elastic wants) and will thus result in a relative expansion of the public
sector. So it is the economic growth that determines government size.
The theory explains that increases in public goods are a product of increased demands by organized industrial
workers, coming at the costs of growth in the private sector (Wagner, 1958). The government sector tends to
grow faster than the economy. Bureau Voting Theory rejected the role of industrialization and urbanization,
suggesting that the main driver of public sector expansion is an artificial demand for government services created
by self-interested government employees (Niskanen, 1971), fiscal illusion theory, which tries to explain
government growth by linking the intricacies of tax systems to the masking of the costs of public goods. Also,
tax systems can hide the costs of public goods and therefore stimulate their growth (Goetz, 1977). Empirical
support for these theories has varied, causing them to lose some of their impetus.
Musgrave’s Theory of Public Expenditure Growth
The Musgrave’s theory of public expenditure and growth explained that, at low level of per capita income, the
demand for public services tend to be very low, arguing that such income is devoted to satisfying primary needs
and it is only when the per capita income starts to rise above these level of low income that the demand for
services provided by the public sector such as education, health, and transports starts to rise, thereby forcing
government to increase expenditure on them. The theory observed that with high per capita income typical in
the developed nations, the rate of public spending falls as most basic wants are being satisfied. Therefore, the
theory suggested in connection to Wagner that as progressive nations become more industrialized, the share of
the public sector in the national economy grows continually (Musgrave, 1988). Iyoha (2002) stated five stages
of expenditure growth; Traditional society, preconditions for take-off, the take-off; the drive to maturity and the
eye of high mass consumption. What determines the accepted expenditure-growth depends critically on the
assumption of the type of economy, i.e. whether it is a free-market economy, a mixed economy or a command
economy.
Empirical Review
Ekpo, Daniel and Okon (2022) employed modified and extended aggregate production model to examine the
effects of government expenditure at its’ aggregate level on economic growth in Nigeria for the period (1981-
2018) using bound test (ARDL) approach. The co-integration result indicates the existence of long-run
relationship between total government expenditure (LTGE) and economic growth in Nigeria, ARDL results
show that total government expenditure (LTGE) impacted positively on economic growth in Nigeria in line with
Keynesian theory. The granger causality test result indicates the existence of uni-directional causal relationship
from LGDP to LTGE for the observed period, in line with Wagner’s theory. It is recommended that there should
be proper utilization of public fund in the provision of security and critical infrastructure especially electricity
supply and road infrastructure which are precursors to effective economic performance. Public fund should be
properly managed to ensure accountability, transparency and fiscal responsibility in carrying out public
assignment. It is believed that if corruption is tackled in the country, more public fund will be freed for
development and public expenditure would impact more on the economic performance, hence, the fight against
corruption in the country should be frontally confronted. Public institutions charged with the responsibility of
handling corruption matters in the country should be overhauled and strengthen to ensure timely and proper
handling of corruption matters.
Ogbuagu and Ekpenyong (2015) investigated the impact of the components of public expenditure on economic
growth in Nigeria from 1970 to 2014. Recurrent expenditure, capital expenditure, net exports, inflation rate and
gross national savings served as the independent variables while gross domestic product served as the dependent
variable. Unit root test, Toda-Yamamoto causality test and autoregression distributive lag (ARDL) technique
were used as analytical tools. Findings showed that recurrent expenditure had a positive and significant impact
on economic growth both in the short run and long run. However, the study showed that capital expenditure
had no short run effect on economic growth, but rather exhibited a negative significant effect on economic
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growth only in the long run. National savings had negative and significant impact on economic growth in the
short run but a positive and significant effect in the long run. Finally, the study revealed that net exports had a
negative impact on economic growth in Nigeria.
Ojonugwa, Esther and Hindatu (2016) examined the relationship between government expenditure and
economic growth in Nigeria for the period 1970 to 2010. Recurrent expenditure and capital expenditure were
adopted as proxies for government expenditure while real gross domestic product was proxy for economic
growth. Unit root test, cointegration test, Pair-wise cointegration test and Grangercausality test were empirical
tools. The study showed that both capital expenditure and recurrent expenditure had positive and significant
relationship with economic growth in the short run. Recurrent expenditure exhibited positive and significant
relationship with economic growth in the short run while capital expenditure had a negative but significant
relationship with economic growth in the short run. The Pair-wise Granger-causality test showed that there was
a unidirectional causality running from economic growth to both capital and recurrent expenditures showing
that economic growth determined both capital and recurrent expenditures in Nigeria.
Nwoha, Onwuka and Ejem (2017) examined the effect of aggregated and disaggregated government expenditure
on economic growth in Nigeria for the period 1980 to 2015. The study adopted aggregated government
expenditure (proxied by total federal government expenditure). Disaggregated expenditure was proxied by
recurrent expenditure and capital expenditure while real gross domestic product served as proxy for economic
growth. All of total government expenditure, recurrent expenditure and capital expenditure served as the
independent variables while real GDP served as the dependent variable. The study employed the error correction
mechanism (ECM) as the empirical tool for its tests and analysis. Findings showed that total federal government
expenditure and capital expenditure had positive and significant effect on economic growth in Nigeria. On the
other hand, the study revealed that recurrent expenditure had a positive and insignificant effect on economic
growth in Nigeria.
Ditimi, Nwosa, and Ajisafe (2019) examined relationship between the components of government expenditure
with focus on education, agriculture, health and transport and telecommunication variables on economic growth
in Nigeria for the period between 1970 and 2018. The results of the long run and short run regression estimates
indicated that expenditure on agriculture was the most significant of the components of government expenditure
that impacted on economic growth.
Nworji, Okwu, Obiwuru and Nworji (2018) studied the effect of public government spending on economic
growth in Nigeria based on variables considered relevant indicators of economic growth and government
expenditure for the period 1970 – 2017. The Ordinary Least Square (OLS) multiple regression models specified
on perceived causal relationship between government expenditure and economic growth was used. Results of
the analysis showed that capital and recurrent expenditure on economic services had insignificant negative effect
on economic growth. Capital expenditure on transfers had insignificant positive effect on growth. Capital and
recurrent expenditures on social and community services and recurrent expenditure on transfers had significant
positive effect on economic growth.
Oziengbe (2016) explored the relative impacts of federal capital and recurrent expenditures on Nigeria’s
economy from 1980 to 2015. The study investigated the effect of total government expenditure (GOVEXP) on
gross domestic product (GDP) using multiple linear regression analysis. The result showed evidence that
strongly supported Ram’s growth accounting model. The Error Correction Model (ECM) model revealed that
the short-run impact of each explanatory variable on GDP was statistically insignificant contemporaneously, but
significant with a lag, with RECEXP exerting greater impact than CAPEXP, though the impact of the former
was negative while that of the latter was positive.
Akanbi (2018) investigated Government expenditure in Nigeria: Determinants and trends. The study used time
series data from 1974 to 2016. It was discovered that capital and recurrent expenditure were resilient to shocks
in total government spending and, also, total government expenditure was confirmed to be resilient to shocks in
capital and recurrent spending.
Aremu, Babalola, Aninkan, and Salako (2020) investigated the impact of government expenditures on critical
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sectors on economic growth in Nigeria (1984-2019). The study employed Autoregressive Distributed Lag model
(Bound Test Co-integration Approach) to estimate both short and long run impact of Government expenditures
on economic growth. The result revealed that government expenditure on defence impacts negatively on
economic growth while government expenditure on agriculture enhances economic growth. Government
expenditure on education, transport and communication did not impact on economic growth in the long-run.
Kanayo, Akujinma and Francis (2016) examined the long run relationship between government expenditure and
economic growth Nigeria. Johansen co-integration was the tool of analysis employed in testing the long run
relationship while Vector Error Correction Model (VECM) was used to test the short and long run adjustments.
Granger causality effect test was adopted to analyse the effect of government expenditure on economic growth.
The long run test revealed the evidence of a long run relationship between government expenditure and economic
growth in Nigeria. The vector error correction model analysis suggested the possibility of Nigeria achieving a
steady level of growth if preference is given to capital expenditure more than recurrent expenditure. The granger
causality effect result obtained showed that recurrent and capital expenditure which have significant effect on
economic growth in Nigeria.
Bashir, Hamza and Rafiat (2017) studied the impact of government expenditure on economic growth in Nigeria.
The study covered the period of 1981-2016 using Ordinary Least Square (OLS) technique and granger causality
test were employed. The result obtained indicated that there was negative and insignificant relationship between
human capital and GDP, the relationship between physical capital and GDP as well as between government
capital expenditure (GCE) and GDP were positive but insignificant. The granger causality test showed that
government expenditure granger caused GDP but GDP did not granger cause government expenditure.
Idris and Bakar (2017) examined the relationship between government expenditure and economic growth with
the aim of establishing a stable relationship. To estimate the existence or otherwise of the equilibrium
relationship among the examined variables the study employed an ARDL model. The data covered a period of
thirty-five (35) years from 1980 to 2015.The result from the ARDL estimation indicated an existence of positive
and long-run equilibrium relationship between economic growth and government expenditure in Nigeria.
Ifarajimi and Ola (2017) studied the relationship between government expenditure and economic growth. Time
series data on government expenditure on administration, economic services, social and community services,
transfers, government total revenue, nominal exchange rate and real per capital GDP for the period of 1981 to
2015 were employed. The study used ECM computed through Dynamic OLS and found that long run
government expenditure on administration and nominal exchange rate were significant and therefore impact
significantly on economic growth in Nigeria.
METHODOLOGY
This study employed Ex-post facto research design. The study used time series data obtained from the Central
bank of Nigeria Statistical bulletins and the World Development indicators covering the period from 1990-2021.
This study employed the use of ordinary Least Square methods to compare the impact of government recurrent
and capital expenditure on economic growth in Nigeria. The study used the Augmented Dickey Fuller test to
ensure that all variables are stationary; this is to avoid the spurious regression problem associated with unit roots.
The Johansen cointegration test was conducted and it showed that there is no long run relationship among the
variables.
Model Specifications
Thus, we express the model as follows;
RGDP =f(CAPEXA,CAPES, CAPSS, CAPEXTR) (1)
RGDP =f(RECEXA, RECXES, REXSS, REXTR) (2)
Transforming equation 1 above to econometric method, we have:
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(3)
(4)
Where
RGDP = Real Gross domestic products
CAPEXA = Capital expenditure on administration as percentage of total capital expenditure
CAPES = Capital expenditure on economic service as percentage of total capital expenditure
CAPSS = Capital expenditure on social services as percentage of total capital expenditure
CAPEXTR = Capital expenditure on transfer as percentage of total capital expenditure
RECEXA = Recurrent expenditure on administration as percentage of gross domestic product
RECXES = Recurrent expenditure on economic services as percentage of gross domestic product
REXSS = Recurrent expenditure on social services as percentage of gross domestic product
REXTR = Recurrent expenditure on transfer as percentage of gross domestic product
µ = Error Term
β
1
– β
4
= Coefficient of Independent Variables to the Dependent Variable
β
0
= Regression Intercept
Methods of Data Analysis
In order to estimate the regression model, E-views econometrics and statistical package will be used. The
procedure involves specifying the dependent and independent variables; in this case, stock market return is the
dependent variable while capital assets pricing models is the independent variables. The main tool of analysis
is the Ordinary Least Squares (OLS) using the multiple regression method for a period of 33 years, annual data
covering 1990-2021. Statistical evaluation of the global utility of the analytical model, so as to determine the
reliability of the results obtained were carried out using the coefficient of correlation (r) of the regression, the
coefficient of determination (r
2
), the student T-test and F-test.
Unit Root Test
It is suggested that when dealing with time series data, a number of econometric issues can influence the
estimation of parameter using Ordinary Least Square (OLS). Regressing a time series variable on another time
series variable using Ordinary Least Square (OLS) estimation can obtain a very high R
2
, although there is no
meaningful relationship between the variables. This situation reflects the problem of spurious regression between
totally unrelated variables generated by a non-stationary process. Therefore, it is recommended that a stationarity
(unit root) test be carried out to test for the order of integration. The Augmented Dickey-Fuller (ADF) test is
used. The ADF test simply runs a regression of the first-difference of the series against a first-lagged value,
constant, and a time trend as the following:
Without Intercept and Trend DYt = d Yt-1 + Ut (5)
With Intercept DYt = a + d Yt-1 + Ut (6)
With Intercept and Trend DYt = a + bT + d Yt-1 + Ut (7)
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The hypothesis is
Ho: d = 0 (Unit Root)
H1: d ¹ 0
Decision rule:
Decision rule:
If t* > ADF critical value, ==> do not reject null hypothesis, i.e., unit root exists.
If t* < ADF critical value, ==> reject null hypothesis, i.e., unit root does notexist.
Cointegration Test
Testing for Cointegration Using Johansen’s Test
Johansen’s methodology takes its starting point in the vector auto regression (VAR) of order p given by
(8)
Whereyt is an nx1 vector of variables that are integrated of order one – commonly denoted I(1) – and at is an
nx1 vector of innovations. This VAR can be re-written as
(9)
Where
If the coefficient matrix II has reduced rank r<n, then there exist nxr matrices a and β each with rank r such that
II = αβ’ and β’yt is stationary. R is the number of cointegrating relationships, the elements of a are known as the
adjustment parameters in the error correction model and each column of β is a cointegrating victor. It can be
shown that for a given r, the maximum likelihood estimator of β defines the combination of yt-1 that yields the
r largest canonical correlations of with yt-1 after correcting for lagged difference and deterministic
variables when present. Johansen proposes two different likelihood ratio tests of the significance of these
canonical correlations and thereby the reduced rank of the II matric: the trace test and maximum eigen value
test, shown in equations (8) and (9) respectively.
Here T is the sample size and 𝛌i is the largest canonical correlation. The trace test tests the null hypothesis of r
cointegrating vectors against the alternative hypothesis of n cointegrating vectors. The maximum Eigen value
test, on the other hand, test the null hypothesis of r cointegrating vectors against the alternative hypothesis of
r+1 cointegrating vectors. Neither of these test statistics follows a chi square distribution in general; asymptotic
critical values can be found in (Johnsen and Juselius, 1990) and are also given by most econometric software
packages. Since the critical values used for the maximum Eigen value and trace test statistics are based on a pure
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unit-root assumption, they will no longer be correct when the variables in the system are near unit-root processes.
Thus, the real question is how sensitive Johansen’s procedures are to deviations from the pure unit root
assumption.
Granger Causality Test
One of the objectives of this study is to investigate the causality between the independent and the dependent
variables. Granger causality test according to Granger (1969) is used to examine direction of causality between
two variables. Therefore, in this study, carried out a granger causality between an independent variables
monetary policy and the dependent variables private sector funding in Nigeria from 1990-2021.The pair-wise
granger causality test is mathematically expressed as:
(13)
(14)
(15)
(16)
(17)
(18)
(19)
(20)
(21)
(22)
Where x
t
and y
t
are the variables to be tested white u
t
and v
t
are the white noise disturbance terms. The null
hypothesis , for all I’s is tested against the alternative hypothesis and if the co-efficient
of are statistically significant but that of are not, then x causes y. If the reverse is true then y causes x.
however, where both co-efficient of and are significant then causality is bi – directional.
Vector Error Correction (VEC) Technique
Co-integration analysis provides a test for spurious correlation. Finding co integration between apparently
correlated I(1) series validate the regression but failure to find co integration is an indication that spurious
correlation maybe present thus invalidating the inferences drawn from such correlation. Co-integration is a
prerequisite for the error correction mechanism. Since co-integration has been established, it is pertinent to
proceed to the error correction model. The VECM is of this form
(23)
Where Y
t
is a vector of indigenous variables in the model, α is the parameter which measures the speed of
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adjustment through which the variables adjust to the long run values and the β is the vectors which estimates
the long run cointegrating relationship among the variables in the model. is the draft parameter and is the
matrix of the parameters associated with the exogenous variables and the stochastic error term.
ANALYSIS AND DISCUSSION OF FINDINGS
Table 2: ADF Unit Root Test for Stationarity at Level
Variable
ADF
Statistic
MacKinnon
@ 1%
MacKinnon
@ 5%
Prob.
Order of
Int
Conclusion
Capital expenditure and economic growth
ADF @ Level
RGDP
-2.971604
-3.661661
-2.960411
0.0488
1(0)
Not stationary
CAPSS
-1.956123
-3.670170
-2.963972
0.3036
1(0)
Not stationary
CAPEXTR
-2.334537
-3.661661
-2.960411
0.1681
1(0)
Not stationary
CAPEXA
-2.118941
-3.661661
-2.960411
0.2390
1(0)
Not stationary
CAPES
-2.765171
-3.661661
-2.960411
0.0750
1(0)
Not stationary
ADF @ Difference
RGDP
-8.093635
-3.670170
-2.963972
0.0000
1(1)
Stationary
CAPSS
-10.21366
-3.670170
-2.963972
0.0000
1(1)
Stationary
CAPEXTR
-5.279315
-3.711457
-2.981038
0.0002
1(1)
Stationary
CAPEXA
-7.042656
-3.670170
-2.963972
0.0000
1(1)
Stationary
CAPES
-12.01791
-3.689194
-2.971853
0.0000
1(1)
Stationary
Recurrent expenditure and economic growth
ADF @ Level
RGDP
-2.971604
-3.661661
-2.960411
0.0488
1(0)
Not stationary
REXTR
-1.505364
-3.661661
-2.963972
0.2146
1(0)
Not stationary
REXSS
-1.182132
-3.661661
-2.960411
0.2627
1(0)
Not stationary
RECXES
-2.684361
-3.699871
-2.976263
0.0897
1(0)
Not stationary
RECEXA
-1.919700
-3.661661
-2.960411
0.1153
1(0)
Not stationary
ADF @ Difference
RGDP
-8.093635
-3.670170
-2.963972
0.0000
1(1)
Stationary
REXTR
-8.781259
-3.670170
-2.963972
0.0000
1(1)
Stationary
REXSS
-8.329543
-3.670170
-2.963972
0.0002
1(1)
Stationary
RECXES
-5.924880
-3.769597
-3.004861
0.0000
1(1)
Stationary
RECEXA
-8.849636
-3.670170
-2.963972
0.0000
1(1)
Stationary
Source: Extract from E-view 9.0
The time series properties of the variables used in the analysis was investigated using Augmented Dickey-Fuller
test. The test was run with specification of trend and intercept in the model. The ADF statistics for the test are
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presented in the table above. It can be seen from the table 1 above that the unit root test results, using the ADF
unit root test suggest that all series are stationary at order I (1). Therefore, the Engle and Granger (1987) can be
employed.
Table 2 : Unrestricted Cointegration Rank Test (Trace)
Hypothesized
Trace
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
Prob.**
Capital expenditure and economic growth
None *
0.712914
61.41127
47.85613
0.0016
At most 1*
0.346101
73.97206
59.79707
0.0016
At most 2
0.233748
11.22800
15.49471
0.1979
At most 3
0.102393
3.240690
3.841466
0.0718
Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized
Max-Eigen
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
Prob.**
None *
0.712914
37.43921
27.58434
0.0020
At most 1
0.346101
42.74406
21.13162
0.0361
At most 2
0.233748
7.987311
14.26460
0.3800
At most 3
0.102393
3.240690
3.841466
0.0718
Recurrent expenditure and economic growth
Unrestricted Cointegration Rank Test (Trace)
None *
0.700627
81.42359
69.81889
0.0045
At most 1*
0.536452
55.24163
47.85613
0.042
At most 2
0.364256
22.17628
29.79707
0.2888
At most 3
0.202258
8.587484
15.49471
0.4049
At most 4
0.058499
1.808398
3.841466
0.1787
Unrestricted Cointegration Rank Test (Maximum Eigenvalue)
Hypothesized
Max-Eigen
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
Prob.**
None *
0.700627
36.18196
33.87687
0.0261
At most 1*
0.536452
43.06535
27.58434
0.0407
At most 2
0.364256
13.58880
21.13162
0.3997
At most 3
0.202258
6.779086
14.26460
0.5156
At most 4
0.058499
1.808398
3.841466
0.1787
Source: Extract from E-view 9.0
From table 2, the results of the Johansen co-integration test show that we reject the null hypotheses of one co-
integrating equation at the 5% level of significance. This implies that, there is linear combination of the variables
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that are stationary in the long run and also confirms the non-existence of a long-run relationship between capital
and recurrent expenditure and economic growth.
Table 3: Pairwise Granger Causality Tests
Null Hypothesis:
Obs
F-Statistic
Prob.
Capital expenditure and economic growth
CAPSS does not Granger Cause RGDP
30
2.35233
0.1159
RGDP does not Granger Cause CAPSS
1.05879
0.3619
CAPEXTR does not Granger Cause RGDP
30
10.1814
0.0006
RGDP does not Granger Cause CAPEXTR
2.20583
0.1311
CAPEXA does not Granger Cause RGDP
30
2.75549
0.0829
RGDP does not Granger Cause CAPEXA
0.69425
0.5088
CAPES does not Granger Cause RGDP
30
4.64975
0.0192
RGDP does not Granger Cause CAPES
2.10696
0.1427
Recurrent expenditure and economic growth
REXTR does not Granger Cause RGDP
30
0.70063
0.5058
RGDP does not Granger Cause REXTR
3.90042
0.0335
REXSS does not Granger Cause RGDP
30
2.05263
0.1495
RGDP does not Granger Cause REXSS
0.51283
0.6050
RECXES does not Granger Cause RGDP
30
1.78384
0.1887
RGDP does not Granger Cause RECXES
1.58633
0.2246
RECEXA does not Granger Cause RGDP
30
3.67018
0.0400
RGDP does not Granger Cause RECEXA
1.16139
0.3294
Source: Extract from E-view 9.0
Pair wise causality tests were run with an optimal lag of 2. The results are presented in table 3. The researcher’s
interest here is to establish the direction of causality between the dependent variables and the independent
variables from 1990-2021. The study found a uni-directional causality from capital expenditure on transfer and
economic service on gross domestic product. The study also found a uni-directional causality from real gross
domestic product to recurrent expenditure on transfers and from administration to gross domestic products.
Table 4: Presentation of the Vector Error Correction Results
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(CAPSS(-1))
0.977149
0.017662
-0.487075
0.6306
D(CAPEXA(-1))
0.731633
0.997849
-0.484598
0.6324
D(CAPES(-1))
0.857440
0.022457
-0.485920
0.6314
D(CAPEXTR(-1))
0.935801
0.012504
-0.486960
0.6307
C
0.470958
0.557817
-0.844287
0.4068
ECM(-1)
0.627059
0.168806
-3.714660
0.0011
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R-squared
0.466458
Mean dependent var
-0.274333
Adjusted R-squared
0.355303
S.D. dependent var
3.759195
S.E. of regression
3.018372
Akaike info criterion
5.224169
Sum squared resid
218.6536
Schwarz criterion
5.504408
Log likelihood
-72.36253
Hannan-Quinn criter.
5.313820
F-statistic
4.196474
Durbin-Watson stat
1.451692
Prob(F-statistic)
0.006992
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(REXTR(-1))
-0.109835
0.598008
-0.183668
0.8558
D(REXSS(-1))
3.884301
3.469885
1.119432
0.2740
D(RECXES(-1))
8.964507
3.992305
2.245446
0.0342
D(RECEXA(-1))
-6.732596
3.106698
-2.167122
0.0404
C
-0.379303
0.560232
-0.677047
0.5049
ECM(-1)
-0.474914
0.166821
-2.846850
0.0089
R-squared
0.454949
Mean dependent var
-0.274333
Adjusted R-squared
0.341396
S.D. dependent var
3.759195
S.E. of regression
3.050752
Akaike info criterion
5.245510
Sum squared resid
223.3702
Schwarz criterion
5.525749
Log likelihood
-72.68265
Hannan-Quinn criter.
5.335161
F-statistic
4.006510
Durbin-Watson stat
1.490353
Prob(F-statistic)
0.008752
Source: Extract from E-view 9.0
From the results, the adjusted R-Square of the capital expenditure is 0.355303 while the recurrent expenditure is
0.341396. This indicates that capital expenditure explained 35.5 percent while recurrent expenditure explained
34.1 percent variation in Nigeria economic growth. The two models were statistically significant when judged
by the value of F-statistic and probability.
DISCUSSION OF FINDINGS
From the results capital expenditure on administration added 0.73 on Nigeria economic growth while recurrent
expenditure on administration reduced economic growth by 6.3 percent. Capital expenditure on economic
service added 0.86 while recurrent added 8.94 percent on economic growth, capital expenditure on social
services added 0.98 while recurrent added 3.88 percent, capital expenditure on transfers added 0.93 while
recurrent reduced by 0.1 percent. Empirically, the positive effect of the variables confirm the expectations of the
study and the findings of Ekpo, Daniel and Okon (2022) that total government expenditure (LTGE) impacted
positively on economic growth in Nigeria in line with Keynesian theory. The granger causality test result
indicates the existence of uni-directional causal relationship from LGDP to LTGE for the observed period, in
line with Wagner’s theory, the findings of Ogbuagu and Ekpenyong (2015) that capital expenditure had no short
run effect on economic growth, but rather exhibited a negative significant effect on economic growth only in the
long run, Ojonugwa, Esther and Hindatu (2016) that both capital expenditure and recurrent expenditure had
positive and significant relationship with economic growth in the short run, Nwoha, Onwuka and Ejem (2017)
that total federal government expenditure and capital expenditure had positive and significant effect on economic
growth in Nigeria.
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The findings of Ditimi, Nwosa, and Ajisafe (2019) the long run and short run regression estimates indicated
that expenditure on agriculture was the most significant of the components of government expenditure that
impacted on economic growth, Nworji, Okwu, Obiwuru and Nworji (2018) that capital and recurrent
expenditure on economic services had insignificant negative effect on economic growth. Capital expenditure on
transfers had insignificant positive effect on growth, Oziengbe (2016) that strongly supported Ram’s growth
accounting model, Akanbi (2018) that capital and recurrent expenditure were resilient to shocks in total
government spending and, also, total government expenditure was confirmed to be resilient to shocks in capital
and recurrent spending, Aremu, Babalola, Aninkan, and Salako (2020) that government expenditure on defence
impacts negatively on economic growth while government expenditure on agriculture enhances economic
growth.
The findings of Kanayo, Akujinma and Francis (2016) Johansen co-integration was the tool of analysis
employed in testing the long run relationship while Vector Error Correction Model (VECM) was used to test the
short and long run adjustments. Granger causality effect test was adopted to analyse the effect of government
expenditure on economic growth, Bashir, Hamza and Rafiat (2017) that there was negative and insignificant
relationship between human capital and GDP, the relationship between physical capital and GDP as well as
between government capital expenditure (GCE) and GDP were positive but insignificant, Idris and Bakar (2017)
indicated an existence of positive and long-run equilibrium relationship between economic growth and
government expenditure in Nigeria and Ifarajimi and Ola (2017) that long run government expenditure on
administration and nominal exchange rate were significant and therefore impact significantly on economic
growth in Nigeria.
CONCLUSION AND RECOMMENDATIONS
Conclusion
This study compared the effect of capital and recurrent expenditure on Nigeria economic growth. The study
used time series data sourced from Central Bank of Nigeria Statistical Bulletin 1990-2021. The study conclude
that capital expenditure have greater explained variation on Nigeria economic growth over the periods covered
in the study. from the findings, the study conclude that capital expenditure on administration added 0.73 on
Nigeria economic growth while recurrent expenditure on administration reduced economic growth by 6.3
percent. Capital expenditure on economic service added 0.86 while recurrent added 8.94 percent on economic
growth, capital expenditure on social services added 0.98 while recurrent added 3.88 percent, capital expenditure
on transfers added 0.93 while recurrent reduced by 0.1 percent.
Recommendations
1. There should be proper utilization of public fund in the provision of security and critical infrastructure
especially electricity supply and road infrastructure which are precursors to effective economic
performance.
2. Public fund should be properly managed to ensure accountability, transparency and fiscal
responsibility in carrying out public assignment. It is believed that if corruption is tackled in the
country, more public fund will be freed for development and public expenditure would impact more
on the economic performance, hence, the fight against corruption in the country should be frontally
confronted.
3. Public institutions charged with the responsibility of handling corruption matters in the country should
be overhauled and strengthen to ensure timely and proper handling of corruption matters.
4. The fiscal responsibility Act 2004 should be implemented to guide the public expenditure to achieve
the macroeconomic objectives. The macroeconomic frame work and the business environment should
be overhaul for positive impact of public capital expenditure and the growth of Nigerian economy.
5. Poor policies on government expenditures impact negatively to the growth of Nigerian industrial
sector. The study recommend for better policies to manage the expenditure of the government.
Economic theories have it that unproductive expenditures do not impact on the growth of Nigerian
economy. The study recommends that government should spend on productive ventures.
6. The study recommend for overhaul in policies of revenue and expenditures to enhance the growth of
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Nigerian industrial sector. Most of the government revenue and expenditures are stolen by public
office holders. The study recommend for enforceable laws to back the anti-corruption agencies.
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