Post on 27-Apr-2023
Public Expenditure, Corruption and Economic
Growth: Evidence from Nigeria using ARDL
Modelling Approach
MAJEKODUNMI, OwolabiEconomics Department, Faculty of Social and Management
Sciences, Olabisi Onabanjo University, Ago-Iwoye, Ogunstate
Abstract
In this paper, the growth differential effect of public
investment, public consumption and corruption control was
analysed between 1970 and 2011 using the autoregressive
distributed lag (ARDL) framework for cointegration, long-run,
and shot-run models. The bounds testing analysis indicated
existence of cointegration between considered set of variables
in the ARDL model. The long-run and short-run estimates
indicated that public investment was economic growth enhancing
but reversal evidence with interaction with corruption was
reported. This indicates that corruption is a menace in
Nigeria and hindering the effectiveness of public investment
in Nigeria. Also, further evidence indicated that equilibrium
is fully restored within 2years for any distortion in the
short-run. Emanating from the above, proper policy
recommendations were proffered.
1
Keywords: Public Expenditure, Corruption, Bureaucracy,Economic Growth, ARDL Modelling, Nigeria
JEL Code: C22, E02, F43, H50
I. INTRODUCTION
Corruption has become the lead topic of debate among all
major international development agencies. The World Bank, for
example, has identified corruption as the single greatest
obstacle to economic and social development, and has given
priority to anti-corruption initiatives in its strategies for
improving the quality of governance, Bardhan (1997), Jain
(2001), Rose-Ackerman (1999) and Tanzi (1998) of most concern
is corruption within society’s state institutions. Public
officials, politicians, bureaucrats and legislators, hold
unique positions of power and responsibility, the abuse of
which can cause significant and long-lasting damage to many
aspects of socioeconomic development. Such abuse can manifest
in a variety of ways, including bribery, embezzlement,
extortion and fraud that may offer substantial personal gains
at little risk of prosecution. Dishonest behavior at one level
in public office is often contagious and often supported by
dishonest behavior at other levels (Blackburn, Bose and Haque,
2011). Based on the above reasons public sector corruption is
perceived to be especially harmful, especially pervasive and
especially difficult to fight and to eliminate or reduced to
the bearest minimum in developing economy and Nigeria as well.
2
There are different ways corruption can reduce economic
growth. Corruption can act as a tax and can lower incentive to
invest. Corruption can increase the ability of agents to get
resources from central and local governments. Therefore,
public resources reward the more able people, not the best
entrepreneurs. Corruption can distort the composition of
government expenditure as corrupt politicians may be expected
to invest in large, non-productive projects from which it is
easier than in productive activities to exact large bribes
(Mauro, 1998b.)
Recent years have seen a large number of papers on the
causes and consequences of corruption. Most of these papers
are theoretical or qualitative analyses. The first
comprehensive econometric research to assess the impact of
corruption on economic growth is by Mauro (1995). On the basis
of cross-country data, Paolo Mauro finds a significant
negative relation between a corruption index, built using
information assembled from the correspondents of Business
International in 70 countries in the early 1980s, and the rate
of growth. According to the findings of Mauro, policies to
fight corruption could be very beneficial to growth. A country
that improves its standing on the corruption index, say, 6 to
8, 0 being the most corrupt, 10 the least, will experience a 4
percentage point increase in its investment rate and a 0.5
percentage point increase in its annual GDP growth rate.
(Mauro, 1998a).
3
Most of the existing literature on the long-run economic
consequences of corruption (Shleifer and Vishny, 1993;
Ehrlich, 2000). Focuses on rent seeking in the provision of
public services. A government official controls the offer of a
service against private demand. He or she has some
discretionary power on the offer and can restrict it in
several ways e.g. denying permission or delaying its release.
Bribes are the extra-price charged by bureaucrats to private
customers, and arise like rents. The economic consequences of
this phenomenon concern distortions in resources allocation
mainly in terms of less private investment, and a reduced rate
of human capital formation. In Ehrlich (2000), corruption is
an economic activity that requires some political capital.
Effort devoted to the accumulation of this kind of knowledge
has an alternative use in human capital production. Corruption
reduces economic growth through a negative influence on
investments in human capital.
Nigeria is one of the most populated countries in the
World and endowed with vast human and natural resources.
Though, the country lacks adequate capital resources to foster
growth and depend mainly on natural resources (such as crude
oil) revenue that persistently fluctuates with crude oil price
volatility. The resource wealth and high external fiscal
financing have resulted to high government spending and
persistent fiscal spending with little or no significant
trickle-down effect on productivity and human welfare. Over
the years from 1999 till date Nigerian governments (federal,
state and local ) had spend and are still spending huge amount4
of money on infrastructural developments like building of
roads, hospitals, schools, generation of electricity etc.
despite all these huge amount pumped into these sectors our
roads are still death traps, our hospitals are still not in
good shape, schools are in a dilapidated states, our energy
sector is still providing epileptic power supply, youth
unemployment is at increase day in day out. The security level
in the country is still very low. huge resources will continue
to be used and wasted in addressing all these problems and no
significant change will be witness if a critical and swift
action/ measure is not taken to tackle the menace of
corruption in our society especially in the government and
the political circles.
It hampers budget equilibrium, diminishes expenditure
efficiency and distorts its allocation between different
budgetary functions. The state budget equilibrium is
undermined in a corrupt political context. Corruption reduces
state revenue (Tanzi, 1998). The impact of corruption on the
amount of public spending is controversial. Mauro (1997)
emphasized that corruption had no significant impact on the
level of public spending. If corruption increases the official
level of expenditure, it reduces the part of it which is
really laid out on the community since the other part is
captured by corrupt agents. A study carried out in Ugandan
primary schools shows notably that only 30 % of the expense
per pupil had actually reached schools between 1991 and 1995
(Ablo and Reinikka, 1998). Corruption raises the cost of
expenditure and reduces the quantity of output provided by the5
state (Shleifer and Vishny, 1993). But does corruption only
reduce the portion of allocated expenditure in total
expenditure or does it also have a net impact on allocated
expenditure level as a share of GDP? The same level of
spending and for a given budgetary function, public spending
is less efficient in countries with high levels of corruption:
corrupt public agents tend to favour investment projects which
generate highest bribes and not necessarily the most efficient
(Shleifer and Vishny, 1993).
Corruption diminishes the impact of public spending on
social outcomes and alters the quality of public services.
Reducing corruption would enable to improve human development
through the reduction of infant mortality and the improvement
of primary school rates (Gupta, Davoodi and Tiongson, 2000).
Corruption, on the other hand, is a multi-dimensional
variable and can be perceived and approached from various
angles. However, for the purpose of this paper, the subject
matter of corruption shall be streamlined and defined to be
illegal profiteering(mismanagement of public funds) by a
government official using his or her position as a
representative of the government, corruption, Barreto(2000)
asserts, can therefore take place in any economic transaction
involving the public sector.
In Nigeria corruption is viewed, as a means of survival
in the face of combination of economic decline, undemocratic
policies, rampant right violations, clamp down, massive
unemployment and wide poverty (Ahmed, 2006). Evidence from
corruption perception index (CPI) by transparency6
international for different years also highlighted the poorest
countries as the most corrupt countries. Oluwatayo I. B.
(2006) and Ikpeze et al, (2005) discovered politicization to
be another main constraint placed on the performances of
public spending. According to them individuals in appointive
positions in government or bureaucracy see themselves as a
representative of their group with the mission to get them
their fair share of the ‘national, state or local cake’ by
whatever means.
According to International Transparency report (2012),
Nigeria is ranked 35th (139th out of 176 countries) the most
corrupt nation in the world. As Nigeria continue to be ranked
high as one of the most corrupt nations in the world, fiscal
spending accelerates with its attendant no return on economic
growth, has yielded empirical question; what is the nexus
among public expenditure, corruption and economic growth in
Nigeria? The foregoing empirical question forms the focus of
this study in examining the effect of corruption and
bureaucracy on public expenditure and on economic growth; and
as well examines the interactive effect of corruption and
public expenditure on economic growth in Nigeria between 1970
and 2011.
This article is made up of five sections. In section 2,
literature reviews. Section 3 describes the data and
econometric method. In section 4, we present empirical
results. Then, section 5 conclusion and policy recommendation
7
in combating corruption in developing countries Nigeria
inclusive.
II LITERATURE REVIEWS
There are a lot of empirical write-ups and journals
addressing the issue of corruption, public spending and
economic development. Below are reviews of such journals.
Fiorino and Galli, (2012), in their study corruption and
growth: evidence from the Italian religions, estimated a
dynamic growth model for the period of 1980-2004 addressing
both the potential bias of the measures of corruption and the
endogeneity between corruption and economic development, finds
strong evidence of a negative correlation between corruption
and growth. Moreover, since government intervention has been
traditionally used to reduce income differentials between the
northern and the southern regions, they also analyse the
interaction between corruption and government expenditure.
Their results indicate that corruption undermines the positive
impact that public expenditures have on economic growth.
Blackburn and Haque, (2011) presented a dynamic general
equilibrium analysis of public sector corruption and economic
growth. Corruption arises because of an opportunity for
bureaucrats to appropriate public funds by misinforming the
government about the cost and quality of public goods
provision. They establish the existence of multiple
development regimes, together with the possibility of
multiple, frequency-dependent equilibria. The predictions of
our analysis accord strongly with recent empirical evidence.
8
Blackburn and Forgues-Puccio (2007) who also show how
corruption can foster inequality by compromising the
effectiveness of redistributive policy, and in Blackburn and
Sarmah (2008) who show how corruption can influence
demographic outcomes (life expectancy in particular) through
its impact on the provision of public health expenditures. The
present paper goes further than these, providing an account of
the corruption–development feedback nexus for the purpose of
explaining why the incidence of corruption is not only higher
in poor countries than in rich countries, but also more
variable among middle-income countries.
Rose-Ackerman (1999) tells of the millions of dollars of
non-existent stationary that was ‘purchased’ by the Government
Press Fund in Malawi, and describes how telephone
specifications in another African country contained the
useless requirement that the equipment must be robust to
freezing temperatures (a requirement that could be satisfied
by only one telephone manufacturer from Scandinavia). These,
and countless other, examples bear testimony to the problems
that face many developing countries. The scale of the offences
involved and the ingenuity of those behind them are often
quite astonishing, and there is little doubt that the
misappropriation of public resources has contributed
significantly to the plight of deprived of nations
Tanzi and Davoodi (1997) find that corruption leads to a
diversion of public funds to where bribes are easiest to
collect, implying a bias in the composition of public spending
towards low-productivity projects at the expense of value9
enhancing investments. The same authors conclude that, as a
result of corruption, the amount of public investment tends to
rise, while the quality of this investment tends to fall
Abbott (1988) reports the instance in Haiti when a prominent
member of the Duvalier regime had 150 km of rail track pulled
up and sold for scrap metal, pocketing the proceeds for
himself. Hardin (1993) recounts the case of the Turkwell Gorge
Dam project in Kenya, the final cost of which was more than
double the amount of initial estimates due to the recoupment
of bribe payments by the French contractor.
III. Theoretical Framework and Model Specification
3.1 Theoretical Framework
Models of endogenous growth have pursued theoretical
framework where persistent economic growth is conditioned on
public investment spending such as human capital accumulation,
as in Lucas (1988), Romer (1990), and Romer (1994). The
proponents opined that growth rate of output is endogenously
determined within the economic environment. The implication of
these models is that public capital investment is the driving
force in the growth process of an economy. The theoretical
consideration which this study is anchored on stems from the
generalization of the capital accumulation of growth and the
accessible channels of capital investment in developing
countries in which associated consensus is still controversial
in literature.
The proponents of endogenous growth model indicate that a
society with higher incentives for capital investments would
10
generate higher growth; it is not clear how the social
incentives for capital investment should be structured across
the real sectors to foster growth. This is an important issue
since different structures will lead to different compositions
of government capital investments (e.g. economic, social,
security and community components) which may or may not have
differential impact on the productivity growth.
From the above, we consider an economy where final output
is dependent two distinct factors of production, physical
capital and labour. For a Cobb-Douglass production function
with constant return to scale technology:
Yt=AtKtβLt
1−β, (0<β<1 ) (3.1)
Where Yt , Kt , and Lt denote gross domestic product, physical
capital stock, and total labour force at time t. Time-variant
technological level ( At ) is influenced by factors contributing
to the enhancement of efficiency and knowledge environment.
In this paper, we argued that the government has growth
or productivity incentives on investment and consumption
spending. Our proposed argument indicates that physical
capital is conceptualized as public investment and consumption
spending driving economic growth over time. This also supports
earlier argument of Josephat et. al. (2000), Nitoy et. al.
(2003), Adesoye et. al. (2010) and Atanda et al. (2012). This
indicates that:
Kt=f (PIt,PCt) (3.2)11
Also, following the conventional growth models, the growth of
labour force (L) is proportion to population level (POP) i.e.
Lt=POPt (3.3)
Similarly, technological progress (A) is taken to grow at a
constant rate over-time and the baseline theoretical model is
augmented with an institutional factor, corruption control
(COR). Then, we have:
Yt=AtKtβLt
1−βCORtη (3.4)
Yt=AtPItβ1PCt
β2Lt1−βCOR
tη (3.5)
Yt=AtPItβ1PCt
β2POPt1−βCOR
tη (3.6)
3.2 Model Specification and Estimation Procedure
Therefore, taking log of both sides, gives:
lnYt=θ0+β1lnPIt+β1lnPCt+(1−β )lnPOPt+ηCORt+u (3.7)
Then, the equ. (3.7) represents the main theoretical baseline
model for this study that expresses the relationship among
public spending, corruption and economic growth in Nigeria.
In line with the objective of this study, the long-run and
short-run effect of public spending and corruption on economic
growth is examined using the autoregressive distributed lag
(ARDL) framework Pesaran & Shin (1995, 1999), Pesaran et. al
(1996), Pesaran (1997), and Pesaran (2001). This framework is
distinct from traditional approach to determine the long-run
and short-run relationships among variables using the standard12
Johansen cointegration (Johansen, 1988; Johansen and Juselius,
1990) and vector error correction (VEC) procedures. In spite
of its innovative properties and popularity, the Johansen
procedure has been under scrutiny in terms of sample size
(Jeon, 2006).
There are advantages of using ARDL framework instead of the
conventional Johansen procedures as noted by Duasa (2007). The
conventional cointegration method estimates the long run
relationships within a context of a system of equations, the
ARDL method employs only a single reduced form equation
(Pesaran & Shin, 1995). The ARDL method yields consistent and
robust results both for the long-run and short-run
relationship among economic growth, public spending and
corruption. The ARDL approach does not involve pre-testing
variables, which means that the test for the existence of
relationship between variables in levels is applicable
irrespective of whether the underlying regressors are purely
I(0), purely I(1) or mixture of both. This feature alone,
given the characteristics of th cyclical components of the
data, makes the standard of cointegration technique unsuitable
and even the existing unit root tests to identify the order of
integration are still highly questionable. But, Adom (2011) as
quoted in Adom, Bekoe and Akoena (2012) indicated that there
is the need for series within an ARDL framework to satisfy two
conditions necessitate that we test for the presence of unit
root in series.
13
Duasa (2007) earlier established that with the ARDL, it is
possible that different variables have different optimal lags,
which is impossible with the standard cointegration test. Most
importantly, the model could be used with limited sample data
(30 observations to 80 observations) in which the set of
critical values were developed originally by Narayan (2004).
From equation (3.7), we basically adopt the ARDL approach to
cointegration following Pesaran et. al (2001) involves estimating
the Unrestricted Error Correction (UEC) version of the ARDL
model to describe the existence of an equilibrium in terms of
long-run and short-run dynamics without losing long-run
information. The test involves estimating the following
equation:
Δln(RYt)=c+∑i=1
aαiΔln(RYt−i)+∑
i=0
bϕiΔln(PIt−i)+∑
i=0
cλiΔln (PCt−i)+∑
i=0
dνiΔln(POPt−i )+
∑i=0
eρiΔ (CORt−i )+η1ln (RYt−1 )+η2ln (PIt−1)+η3ln(PCt−1)+η4ln (POPt−1)+η5CORt−1+εt
(3.
8)
Where Δ is first-difference operator and a,b,c,d and e are the
optimal lag lengths for each incorporated series. Note that
there is no reason that the lag-length terms are equivalent to
each other. The first part of the equation with αi,ϕi,λi,νi, and ρi
represents the short-run dynamics of the model whereas the
parameters η1−5 represents the long-run relationship.
14
The equation (3.8) is estimated using classical ordinary least
square (OLS) method. To test the existence of a long-run level
relationship the F test is used. When long-run relationship
exists, F test indicates which variable should be normalized.
The null hypothesis for no cointegration (i.e. no long-run
relationship) among variables in equation (3.8) is:
H0: η1=η2=η3=η4=η5=0
H1: η1≠η2≠η3≠η4≠η5≠0
We proceed by conducting a bounds test for the null
hypothesis. The calculated (Wald) F-statistic is compared with
the critical value tabulated by Pesaran (1997), Pesaran et al.
(2001) and Narayan (2004). If the test statistics exceeds the
upper critical value, the null hypothesis of a no long-run
relationship can be rejected regardless of whether the under
lying order of integration of the variables is 0 or 1 or a
mixture of both. Similarly, if the test statistic falls below
a lower critical value, the null hypothesis is not rejected.
However, if the test statistic falls between these two bounds,
the result is inconclusive. When the order of integration of
the variables is known and all the variables are I(1), the
decision is made based on the upper bound. Similarly, if all
the variables are I(0), then the decision is made based on the
lower bound.
In the second step, if there is evidence of long-run
relationship (cointegration) among the policy variables, the
following long-run model (3.9) is estimated:15
ln(RYt)=c+∑i=1
kϖiln(RYt−i)+∑
i=0
lϑiln (PIt−i )+∑
i=0
mχiln (PCt−i)+
∑i=0
pμiln (POPt−i)+∑
i=0
qοiCORt−1+εt
( (3.9)
The ARDL method estimates (p+1)k number of regressions in order
to obtain the optimal lag length for each variable, where p is
the maximum number of lags to be used and k is the number of
variables in the equation. The orders of the lags ( k,l,m,p,q ) in
the ARDL model (3.9) are selected by the Akaike Information
criterion (AIC), the Schwarz Information criterion (SIC), and
Hannan-Quinn Information criterion (HIC) before the selected
model is estimated by OLS. For annual data, Pesaran & Shin
(1999) recommended choosing a maximum of 2 lags. From this,
the lag length that minimizes the criteria are selected.
The ARDL specification of the short-run dynamics can be
derived by constructing an error correction model (ECM) of the
following form:
Δln (RYt)=c+∑i=1
aμiΔln(RYt−i)+∑
i=0
bνiΔln(PIt−i)+∑
i=0
cοiΔln (PCt−i)
+∑i=0
dπiΔln(POPt−i )+∑
i=0
eθiΔCORt−i+ψECMt−1+ωt
(3.10)
Where ECMt−1 is the error correction term, defined as:
16
ECMt−1=ln(RYt)−¿(c+∑i=1
kϖiln (RYt−i)+∑
i=0
lϑiln(PIt−i)+∑
i=0
mχiln (PCt−i )¿)¿
¿
¿¿
(3.11)
All coefficients of short-run equation are coefficients
relating to the short-run dynamics of the model’s convergence
to equilibrium, and ψ represents the speed of adjustment. The
ECM indicates the speed of adjustment back to long-run
equilibrium after a short-run disturbance.
However, public investment spending are expected to be growth
enhancing, while public consumption spending can either be
positive or negative related economic growth depending on
inherent institutional framework in Nigeria. Also, corruption
control as an institutional quality indicator is expected to
further enhance public spending effectiveness to enhance
economic growth in Nigeria. Likewise, we expect the speed of
growth adjustment to long-run path to be fast, which further
inform policy simulations from the findings.
3.3 Pre and Post Estimation Diagnostic Tests
3.3.1 Pre Estimation Diagnostic Test
The time series properties of the variables incorporated in
the ARDL model (3.7) is examined using the Augmented Dickey-
Fuller unit root test in order to determine the long-run
convergence of each series to its true mean. The test involves
17
the estimation of equations with drift and trends as proposed
Dickey and Fuller (1988). The test equations are expressed as:
ΔZt=η0+η1Zt−1+∑i=1
nπiΔZt−i+νt (3.12)
ΔZt=η0+η1Zt−1+η1t+∑i=1
nπiΔZt−i+νt (3.13)
H0: η1=0
H1: η1<0
The time series variable is represented by Z, t and νt as time
and residual respectively. The equ. (3.12) and (3.13) are the
test models with intercept only, and linear trend
respectively.
3.3.2 Post Estimation Diagnostic Test
The specified long-run and short-run ARDL models (3.9 and
3.10) are estimated through the use of Classical Least Square
Estimator and other time series diagnostic tests are employed
such as Ramsey RESET test for the entire structural stability
of the model in line with underlining classical assumptions;
residual diagnostic tests like Histogram normality test,
Breusch Godfrey serial correlation LM test, Breusch-Pagan-
Godfrey (BPG) and ARCH Heteroskedasticity tests.
3.4 Data Requirements and Sources
The time series data required for this paper are real gross
domestic product, government recurrent expenditure, and
18
capital expenditure. These data were sourced from the Central
Bank of Nigeria (CBN) Statistical Bulletin, December 2012 and
control of corruption was sourced from the Worldwide
Governance Indicator (WGI) July, 2013. This study employed
annual data that spans from 1970 to 2011.
IV. EMPIRICAL FINDINGS
The empirical results and discussion on the growth
differential effect of public investment and consumption
spending and corruption control index in Nigeria between a
decade after independence (1970) and 2011 are presented under
this section. The summary statistics of the incorporated time
series are presented in section 4.1, while the estimated
regression models were presented in subsequent sub-sections.
4.1 Summary Statistics
Table 4.1: Descriptive Statistics for Growth, Public Spending and Corruption
COC PC PI RY POPGPOP_N
G
Mean -1.109479909.
5219782.
8281644
.82.535 102.2
Standard Error 0.028
130820.9 50328.4
35264.3
0.029 4.8
Median -1.122 37231.6 26194.8266464
.62.492 98.8
Standard Deviation 0.183
847816.0
326165.1
228538.7
0.187 31.1
Kurtosis -0.467 3.9 1.8 -0.11.691 -1.0
Skewness -0.106 2.1 1.6 0.81.492 0.3
Range 0.7713309627
.31152622
.9829942
.80.726 105.1
Minimum -1.510 716.1 173.6 4219.0 2.32 57.4
19
6Year (Minimum) 1978 1970 1971 1970 1997 1970
Maximum -0.7393310343
.41152796
.5834161
.83.052 162.5
Year (Maximum) 1990 2010 2009 2011 1978 2011Count 42 42 42 42 42 42
Source: Authors’ Computation
Figure 4.1:
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
0.00
50,000.00
100,000.00
150,000.00
200,000.00
250,000.00
300,000.00Real Growth, Public Consumption and
Investment Spending (Pre-SAP and SAP era)
PC PI RY
Figure 4.2:
20
1994
1996
1998
2000
2002
2004
2006
2008
2010
0.00
500,000.00
1,000,000.00
1,500,000.00
2,000,000.00
2,500,000.00
3,000,000.00
3,500,000.00 Real Growth, Public Consumption and Investment Spending (Post-SAP era)
PC PI RY
Table 4.2: Average Values of Growth, Public Spending and Corruption Indicators across Structural Periods
Structural Eras Period
PC(N’mill)
PI(N’mill)
RY(N’mil
l) COR
POPGrowth (%)
POP(mill)
2nd NDP1970-1974
1006.52 520.38 7011.4
-1.166
8 2.46 60.3
3rd NDP1975-1980
3526.983
5306.067
29757.66
-1.251
2 2.93 70.3
4th NDP1981-1985
5701.48
5486.94
195020.9
-1.166
8 2.55 81.7
SAP Era1986-1993
41621.38
23116.01
243313.9
-0.888
8 2.51 96.4
Post-SAP era
1994-1998
135751.5 196730
292703.2
-1.133
4 2.34 112.7
Democratic Era
1999-2002
546840.6
374388.3 357890
-1.215
7 2.39 125.3
21
NEEDS Era2003-2007
1224034
484839.4
559422.6
-1.163
7 2.48 139.9Global Economic & Debt Crises
2008-2011
2695558
1019669
750418.5
-0.986
9 2.51 156.5
Overall Eras
1970-2011
479909.5
219782.8
281644.8
-1.109
1 2.54 102.2Source: Authors’ Computation
Figure 4.3: Output Growth and Public Spending across structural erasin Nigeria
1970-1974
1975-1980
1981-1985
1986-1993
1994-1998
1999-2002
2003-2007
2008-2011
1970-2011
0
500000
1000000
1500000
2000000
2500000
3000000
PCPIRY
4.2 Unit Root Test Results
The result of the time series properties of the incorporated
variables in the multiple regression model in the previous
section is not reported in this sub-section. This serves as a
pre-test before the estimation of the long-run regression
model in the next sub-section that captures the effect of
public spending and corruption on economic growth in Nigeria
between 1970 and 2011.
22
The Augmented Dickey Fuller (ADF) unit-root test results
indicated that among the considered time series variables, log
of real GDP, public investment spending, public consumption
spending, population level and corruption control index were
found not to reject the null hypotheses “no stationary” at
levels. This indicates that the series does not revert to
their long-run mean at level based on the random walk with
drift and without drift models. However, after the first
difference of these series do not reject the null hypothesis
“unit root”. This implies that the first difference
transformed series of the incorporated variables in the ARDL
models are stationary. This further suggests that the first
differenced series are mean reverting at levels and do converge to their
long-run equilibrium.
4.3 ARDL Bound Testing
Prior before the estimation of the Unrestricted Error
Correction (UEC) version of the ARDL model to describe the
existence of a long-run equilibrium among the incorporated
series in model (3.8), the optimal lag was selected using
several criteria as indicated in Table 4.3. Although, for
annual data, Pesaran & Shin (1999) recommended choosing a
maximum of 2 lags but the 3rd lag was found more optimal and
was selected for the ARDL estimation.
Table 4.3: Optimal Lag Selection Criteria for the ARDL Unrestricted Error Correction (UEC) Model [3.8]
Lag Adj. R2 S.E AIC SIC HQC1 0.2066 0.3025 0.6750 1.1394 0.84292 0.3385 0.2796 0.5812 1.2637 0.8261
23
3 0.7100 0.1875 -0.2089 0.6961 0.11314 0.6618 0.1821 -0.3758 0.7562 0.0233
Note: S.E is Standard error of regression; AIC is Akaike Information criterion; SIC is Schwarz criterion; and HQC is Hannan-Quinn criterion
Table 4.4: Bounds test for the existence of a level relationship
Wald F-Statistic
10% 5% 1%
Upper
bound
I(1)
LowerboundI(0)
UpperboundI(1)
Lower
bound
I(0)
Upper
bound
I(1)
LowerboundI(0)
FRY (RY|PI,PC,COR,POP)¿10.3877
3.345
2.402
3.905
2.850
5.173
3.892
Source: Narayan, 2004 and Authors’ Computation
The calculated Wald F-statistic value (10.39) as shown on
Table 4.4 was found greater than the tabulated upper and lower
bounds statistics reported in Narayan (2004) for 43
observations for each of the significance levels. This
indicates that there is existence of long-run relationship or
cointegration among economic growth, public investment, public
consumption and corruption in Nigeria between 1970 and 2011.
4.5 Long-Run and Short-Run Estimates
The dynamic and static versions of the long-run estimates of
the relationship among economic growth, public investment,
public consumption and corruption in Nigeria between 1970 and
2011 were estimated as reported on Table 4.5 and 4.6
respectively.
24
The Hendry’s (1995) general-to-specific modelling iteration
approach was adopted to estimate the autoregressive
distributed lag (ARDL) model (3.9) and the results were
reported in Table 4.5. The estimated ARDL(1, 1, 3, 0, 0)
model was selected on the basis of the Akaike and Schwarz
Information criteria. The R-squared result indicated that 94%
of the total changes in output was dynamically explained by
simultaneous changes in public investment, public consumption,
population and corruption control level in Nigeria.
Table 4.5: Long-Run Estimates (ARDL Version)Dependent Variable: lnRYARDL (1, 1, 3, 0, 0) selected based on Schwarz criterionSample (adjusted): 1973 2011
Regressor Coeff.Std.Error t-Stat. Prob.
C-
17.098 8.374 -2.042 0.050lnRY(-1) 0.548 0.131 4.178 0.000lnPI 0.038 0.114 0.338 0.738lnPC -0.075 0.233 -0.322 0.750
lnPC(-1) 0.001 0.234 0.003 0.998lnPC(-2) -0.237 0.254 -0.934 0.358lnPC(-3) -0.237 0.226 -1.049 0.303
COR -0.176 0.383 -0.458 0.650lnPOP 6.029 2.608 2.311 0.028
R-squared 0.949 Akaike info criterion 0.6829
Adjusted R-squared 0.936
Schwarz criterion 1.0668
S.E. of regression 0.308
Hannan-Quinn criter. 0.8207
F-statistic 70.118 Durbin-Watson stat 1.8809
Prob(F-statistic) 0.000
Source: Authors’ Computation
The dynamic the long-run estimates as shown on Table 4.5
indicated that public investment and population level were
25
growth enhancing while corruption and public consumption were
growth retarding in Nigeria between 1973-2011. Similar
findings were reported for static long-run version estimates
that capture the growth effect of public investment, public
consumption and corruption in Nigeria as shown on Table 4.6
However, it was evident from Table 4.6 under model [2] and
[3], the growth effect of interaction between public spending
components and corruption control in Nigeria were negatives
and statistically significant.
Table 4.6: Long-Run Estimates (ARDL Version)Dependent variable: lnRY
1 2 3Coeff.
Std.Er
Coeff.
Std.Er
Coeff.
Std.Er
C
-31.743
* 5.863
-26.860
* 5.823
-26.762
* 5.689lnPI 0.326* 0.136 -0.095 0.211 0.396* 0.128
lnPC-
1.169* 0.204-
1.220* 0.192-
1.736* 0.278COR 0.895* 0.425 5.262* 1.790 5.543* 1.724
lnPI*COR-
0.421* 0.168
lnPC*COR-
0.433* 0.156
lnPOP11.740
* 1.71311.752
* 1.60311.830
* 1.578R-squared 0.913 0.926 0.928Adjusted R-squared 0.904 0.916 0.919S.E. of regression 0.472 0.441 0.434F-statistic 97.375 90.229 93.457Prob(F-statistic) 0.000 0.000 0.000Akaike info criterion 1.447 1.334 1.301Schwarz criterion 1.653 1.582 1.549* denotes 5% significanceSource: Authors’ Computation
26
The short-run estimates of the ARDL model (1, 1, 3, 0, 0) were
reported on Table 4.7 and indicated that in the short-run
public investment and consumption had negative but
insignificant effect on economic growth while corruption
control was slightly beneficial to economic growth in the
short-run. The error correction term (ECT) co-efficient that
explains the speed of adjustment from any distortion in the
short-run to its long-run equilibrium stood at -0.501. This
implies that 50.1% of any disequilibrium is restored in the
first year. This further suggests that the short-run
disequilibrium are fully restored to its long-run equilibrium
within 2years. This further establish true long-run
relationship among the series.
Table 4. 7: Log-linear short-run (ECM) estimatesECM for ARDL (1, 1, 3, 0, 0) selected based on Schwarz criterionDependent Variable: DlnRY
C DlnPI DlnPC DlnCOR DlnPOP ECT(-1)-0.574 -0.063 -0.089 0.768** 28.940 -0.501*0.731 0.150 0.219 0.445 28.400 0.197
Diagnostic tests
R-sqd. 0.237623Adj. R-sqd. 0.118502
S.E. of reg. 0.326957
F-stat. 1.994797Prob(F-st.) 0.106198 D. W stat 1.44195
AIC 0.745963 SIC 1.004529 HQC 0.837958Source: Authors’ Computation
27
V. CONCLUSION AND POLICY RECOMMENDATIONS
In this paper, the growth differential effect of public
investment, public consumption and corruption control have
been established and critically analyzed. The adopted
theoretical framework emanates from the endogenous growth
model. Considering our small size (1970-2011) the
28
autoregressive distributed lag (ARDL) framework of
cointegration, long-run, and shot-run models were adopted.
The bounds testing analysis indicated existence of
cointegration between considered set of variables in the ARDL
model. The long-run and short-run estimates indicated that
public investment was economic growth enhancing but reversal
evidence with interaction with corruption was reported. This
indicates that corruption is a menace in Nigeria and hindering
the effectiveness of public investment in Nigeria. Also,
further evidence indicated that equilibrium is fully restored
within 2years for any distortion in the short-run.
On this basis of the emanating findings, this study proffered
the need for government to build strong institutions in
combating corruption problem in order to strength the
governance framework and enhance the effectiveness of
government spending to promote economic growth in Nigeria.
Also, high monitoring and management priority should be
dedicated to oversee public consumption spending in order to
reduce wastage and enhance its growth potentials.
29
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