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Journal of Economics and Allied Research Vol. 7, Issue 2 (June, 2022) ISSN: 2536-7447
i
JOURNAL OF
ECONOMICS AND
ALLIED RESEARCH
(JEAR)
ISSN: 2536-7447
VOLUME 7, ISSUE 2
JUNE, 2022
Journal of Economics and Allied Research Vol. 7, Issue 2 (June, 2022) ISSN: 2536-7447
ii
TABLE OF CONTENTS
ECONOMIC GROWTH, OIL RENT AND AGRICULTURAL VALUE-ADDED NEXUS IN NIGERIA:
AN EMPIRICAL EVIDENCE
Sunday O. Igbinedion, Hussain K. Ogunbadejo and Aisha A. --------------------------------------------------------(1-15)
PUBLIC EXPENDITURE AND INFRASTRUCTURAL DEVELOPMENT IN NIGERIA:
A COMPARATIVE ANALYSIS OF DEMOCRATIC AND MILITARY REGIMES
Temidayo O. Akinbobola, Kehinde H. Oderinu and Abiodun .S. Olayiwola -------------------------------------(16-32)
IMPLICATIONS OF COVID-19 FOR AGRICULTURE, FOOD SECURITY, AND
POVERTY IN NIGERIA
Osmond N. Okonkwo, Ogwuru H. O. Richard, Okezie A. Ihugba, Desmond O. Echeta and Charles O. Manasseh ------(33-41)
IMPACT OF INFRASTRUCTURE ON FOREIGN DIRECT INVESTMENT INFLOW TO NIGERIA
AbdulRahman B. Sani and Ajayi O. Ezekiel -----------------------------------------------------------------------------(42- 52)
DO EDUCATION OUTCOMES ENHANCE SUSTAINABLE DEVELOPMENT IN NIGERIA?
Richard O. Ojike, Nkechinyere R. Uwajumogu and Chizoba E. Didigu -------------------------------------------(53-66)
THE EFFECT OF FINANCIAL CRISIS ON PROFITABILITY OF NIGERIAN BANKS
Rufus A. Ajisafe, Akinwale Olasusi, Solomon O. Okunade and Abiodun S. Olayiwola -------------------------(67-80)
INVESTMENT IN ROAD TRANSPORT INFRASTRUCTURE AND ECONOMIC GROWTH
IN NIGERIA: A VECTOR ERROR CORRECTION MODEL APPROACH
Adebosin W. Gbadebo, Salami L. Abiodun and Saula D. Taiwo --------------------------------------------------------------(81-92)
WORK ETHICS AND SUSTAINABLE SERVICE DELIVERY IN NIGERIA PUBLIC SERVICE
Francisca N. Onah, Christopher O. Ugwuibe, David C. Nwogbo and Nnabuike O. Osadebe ----------------------------(93-110)
MODELLING THE EFFECT OF THE CENTRAL BANK BALANCE SHEET POLICY ON
DISAGGREGATED INFLATION IN NIGERIA: A NON-LINEAR ARDL APPROACH
Igoni Pedro and Ganiyat A. Adesina-Uthman -------------------------------------------------------------------------------(111-130)
MIGRATION AND REMITTANCE: IMPLICATION FOR ECONOMIC DEVELOPMENT
IN AFRICA
Timothy I. Aliu and Evelyn N. Ogbeide-Osaretin --------------------------------------------------------------------(131-145)
DOES OIL PRICE AND PRODUCTION INFLUENCE ECONOMIC GROWTH? EVIDENCE FROM
NIGERIA
Ahmed Adamu and Habiba H. Usman ----------------------------------------------------------------------------------(146-159)
TAX REVENUE AND WELFARE OF NIGERIANS
Olaleye, Adenike.O.,Tella, Sheriffdeen A., and Awolaja, Oladapo .G --------------------------------------------(160-174)
IMPACTS OF FUNDAMENTAL MACROECONOMIC SHOCKS AND ANTI – SHOCK POLICIES
IN NIGERIA: A DSGE ANALYSIS
Adebisi, Ademola A. --------------------------------------------------------------------------------------------------------(175-193)
Journal of Economics and Allied Research Vol. 7, Issue 2 (June, 2022) ISSN: 2536-7447
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INEQUALITY TRENDS IN MATERNAL HEALTH CARE SERVICE UTILIZATION:
EVIDENCE FROM NIGERIA
Chukwuedo S. Oburota -------------------------------------------------------------------------------------------------------(194-205)
GOVERNMENT EDUCATION EXPENDITURE AND HUMAN CAPITAL DEVELOPMENT
IN NIGERIA: AN EMPIRICAL INVESTIGATION
Andy Okwu, Moses Nissi, Owolabi T. Joy and Deborah Adejola --------------------------------------------------------(206-222)
SOCIO-ECONOMIC EFFECT OF COMMUNITY-BASED NATURAL RESOURCES
MANAGEMENT PROGRAMME ON POVERTY STATUS AMONG FISHING
HOUSEHOLDS IN THE RIVERINE AREAS OF ONDO STATE, NIGERIA
Oduntan Oluwakemi ---------------------------------------------------------------------------------------------------------(223-234)
AGRICULTURE FINANCING AND FOOD SECURITY IN NIGERIA
Abdul M. Yusuf, Saheed Zakari., Abraham Alexander, Bernard O. Anthony and Yakubu Alfa --------(235-249)
ECONOMIC SIZE, UNCERTAINTY, AND INCOME INEQUALITY IN NIGERIA
Obiakor R. Tochukwu, Akpa E. Okoro and Okwu A. Titus-------------------------------------------------------(250-264)
FREE TRADE DYNAMICS AND EXPORT-IMPORT COMPETITIVENESS
IN ENGLISH SPEAKING WEST AFRICAN COUNTRIES (ESWACS)
Uzomba, Peter Chika ------------------------------------------------------------------------------------------------------(265-283)
BENCHMARKING ICT IN TEACHING AND LEARNING WORD PROCESSING
FOR ENTREPRENEURIAL AND ECONOMIC SUSTAINABILITY
Gaddafi Shehu, Mgbeonyejume Hilary and Abubakar Aliyu ---------------------------------------------------(284-295)
GOVERNMENT CAPITAL EXPENDITURE IN ECONOMIC SERVICES’ SECTOR
AND ECONOMIC GROWTH IN NIGERIA
Ikubor O. Jude, Oladipo. A. Oluwaseun, Zakaree. S. Saheed and Abraham.A. Alexander ----------------(296-308)
Journal of Economics and Allied Research (JEAR)
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Journal of Economics and Allied Research (JEAR) is a peer-reviewed open access journal
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Journal of Economics and Allied Research Vol. 7, Issue 2 (June, 2022) ISSN: 2536-7447
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Journal of Economics and Allied Research Vol. 7, Issue 2 (June, 2022) ISSN: 2536-7447
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BaoXiaojia, PhD (Columbia University,
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Wang Yanan Institute for Studies in
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Economics (Wise),
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Journal of Economics and Allied Research Vol. 7, Issue 1 (March, 2022) ISSN: 2536-7447
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Journal of Economics and Allied Research Vol. 7, Issue 2 (June, 2022) ISSN: 2536-7447
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ECONOMIC GROWTH, OIL RENT AND AGRICULTURAL VALUE-ADDED
NEXUS IN NIGERIA: AN EMPIRICAL EVIDENCE
SUNDAY OSAHON IGBINEDION
Department of Economics, Faculty of Social Sciences University of Benin, Edo State
Sunday.igbinedion@uniben.edu Phone +234 (0)8065432491
HUSSAINKEHINDE OGUNBADEJO
Nigerian Institute for Oceanography & Marine Research, Victoria Island Lagos
Email: ogunbadejohk@yahoo.com, Phone +234 (0)8023911896
AISHA ARAMA ZUBAIR
Department of Economics, Kogi State University, Anyigba, Kogi State, Nigeria
Aramaaisha@gmail.com, +234 (0)8038419066
ABSTRACT
Agriculture is known as the engine and panacea for economic growth in most developing
nations of the world. The objective of this study is to investigate the direction of causality
among economic growth, oil rent and agriculture value-added in Nigeria. In addition,
analyzing the interrelationship between economic growth and agriculture added value. The
data used is time-series data in the period 1970-2020 obtained from world development
indicators from the World Bank database. The analytical approach used is causality with the
vector error correction model (VECM) and Granger Causality test. The finding of this study,
in the agricultural added value equation indicates the validity of the long and short-term
equilibrium relationship between variables, there is long and short-term causality in the
direction of economic growth, oil rent on agriculture added value.
Keywords: Agriculture, Economic growth, Granger Causality, Vector error correction
model (VECM).
JEL Classification: J43, Q1
1. INTRODUCTION
Agriculture is the bedrock for economic growth, development and poverty eradication in
developing countries. Agriculture has also been regarded as the engine and panacea to
economic prosperity. In the words of Gunner Myrdal (1984), “The battle for long-term
economic growth will be won or lost in the agricultural sector”. However, how this path
leads to economic prosperity is still subject to debate among development specialists and
economists. In the 1950s and 1960s in Nigeria, agriculture was the leading sector in terms
of contribution to the gross domestic product, accounting for approximately 64% of output
as well as employing over 73% of the total labour force. It was the major foreign exchange
earner used to pay for imported capital manufactured goods (Ighodaro, 2010). However, the
discovery of crude oil in commercial quantity brought about a reduction in the agricultural
share of gross domestic product from almost 64% in 1960 to about 49% in 1969. Between
1980 and 1989 it fell to an average of 33.4%. Agriculture’s contribution to the gross
domestic product between 1990 and 1997 averaged 29.34% (Iyoha, 2003). Agriculture share
later increased to 40% in 1998 and declined to 27% in 2000. Between 2000 and 2009 the
percentage contribution of the agricultural sector to GDP declined to an average of 28.5%
with a persistent reduction of 21.6% from 2010 to 2016. Agriculture contributed to almost
22.03 percent of the total GDP between 2017 and 2020, with an increase of about four
percentage points compared to the previous period (Central Bank of Nigeria, 2020).
Journal of Economics and Allied Research Vol. 7, Issue 2 (June, 2022) ISSN: 2536-7447
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Agriculture is still the main source of livelihood for most Nigerian and remains the
foundation of the Nigerian economy, despite the presence of oil in the country. The
agricultural sector is made up of four sub-sectors: Crop Production, Livestock, Forestry and
Fishing.
Before 2015, real GDP growth in Nigeria compared favourably with the emerging Asian
countries, notably, Thailand, Malaysia, China, India and Indonesia which were far behind
Nigeria in terms of GDP per capita in 1970, these countries have transformed their
economies and are not only miles ahead of Nigeria, but are also major players on the global
economic arena. Indeed, Nigeria’s poor economic performance, particularly in the last forty
years, is better illustrated when compared with China which now occupies an enviable
position as the second-largest economy in the world. Between 2013 and 2014, growth in
Nigeria averaged 6 per cent but fell to 2.7 per cent in 2015 and -1.6 per cent in 2016 when
Nigeria experienced its first full year of recession in 25 years (World Bank, 2017). Even
with the recovery in 2017, Nigeria’s growth is yet to meet up with its peers as the impact of
direct government interventions in the sector could not robustly counteract the
accompanying effects which have led to the destruction of agricultural farmlands,
insecurity, disrupted economic activity, and poor food security.
Nigeria is facing an imminent food security crisis, increasing poverty levels, and high
unemployment with a growing population, which depends mainly on imported food (Ikenwa
et al., 2017; Olomola &Nwafor, 2018). The dominance of subsistence farming over large-
scale farming in Nigeria may be traced to problems such as high lending rates, inadequate
access to fertilizers, poor storage facilities, poor farmers’ education and or extension
services, and weak institutional framework. (Anumudu Ugwuanyi, Asogwa & Ogbuakanne,
2018). Despite Nigeria’s significant resource endowments, there is a negative economic
growth rate; poverty and insurgency remain widespread.
The GDP in 2017 stood at 0.8% which later rose to 2.2 % in 2019 and further declined to
1.92% in 2020 as a result of the downward trend in global economic activities as a result of
the COVID-19 pandemic. The second quarter of 2021 recorded a slight recovery, but the
country’s economic growth is yet to match up with its peers as the impact of direct
government intervention in the agricultural sector failed to significantly counteract the
effects that led to insecurity, poor infrastructure, and destruction of road networks, disrupted
economic activities, and poor economic performance through economic growth (Central
Bank of Nigeria, 2021).
Gardner (2003) considers the sources and constraints on agricultural growth in his paper, he
investigates the relationship between the growth in agricultural value-added per worker and
GDP per capita for 52 developing countries. He provides evidence of a positive relationship
between these growth rates and poses the question: “What is the direction of causality?”
There is substantial literature that provides conflicting evidence in answering the question.
For example, some suggest that the export of surplus resources from agriculture leads to
agriculture driving economic growth. Others suggest that increases in the nonagricultural
wage lead to relocation and increases in agricultural productivity thereby implying that
causality runs from general economic growth to agriculture. Gardner (2003) also provides
limited information concerning the methods used to answer this question, however, it is
concluded that an “investigation of lags.does not show agriculture as leading.” In this article,
we aim to further investigate the question posed by Gardner using the data to analyze. Our
analysis employs the Vector Error Correction and the Granger causality test and as such
complements the work by Gemmell et al. (2000) by applying a similar approach to a
country-specific.
Journal of Economics and Allied Research Vol. 7, Issue 2 (June, 2022) ISSN: 2536-7447
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Nevertheless, some authors while accepting this argument conclude that, in an open
economy, the linkages between agriculture and nonagricultural are less important than in a
more closed economy (Dercon 2009, Gollin 2010). They argue that in an open economy,
importing food and focusing efforts on other sectors might be more beneficial to the
country‘s development if it is difficult to increase agricultural productivity. Schiff and
Valdez (1998) report that most of the early development strategies, advocated by
Rosenstein-Rodan, Nurkse, and Hirshman among others, emphasize industrial development
as the main source of economic growth. They were biased against the agricultural sector. In
addition, Moon (2011) writes about the ‘Washington Consensus’ as having preached to Sub-
Sahara African leaders to focus on industrialization along with privatization and
deregulation at the expense of agricultural development. This is a manifestation of
mainstream development thinking before the 2000s.
Imposed by the donor countries, the International Monetary Fund (IMF), and the World
Bank, this strategy left Sub-Sahara African agriculture to lag farther behind the rest of the
world.
However, Pingali (2012) reports that the canonical role of agriculture in economic
development is being re-discovered by the developing country policymakers as well as
managers of foreign assistance in the Organization for Economic Cooperation Development
(OECD) countries and multi-lateral agencies. He further coinsthe expression “agriculture
renaissance” and defines it as the renewed understanding and recommitment to the
fundamental role of agriculture in the development process.
Given the differing views in the literature, the role of agriculture in the development process
must be reevaluated based on the specific economic environment of a country.
Therefore, the research question that the study attempts to provide the answer to is: is
agriculture significantly impact Nigeria's economy? And, what is the direction of causality
among economic growth, oil rent and agriculture value-added?
This paper is structured into five sections. Section two reviews the empirical literature and
section three discusses the methodology, model specification, vector error correction and
Granger causality approach. Section four presents the analysis and interpretation of
empirical results. Section five summarizes and presents the concluding remarks.
2. LITERATURE REVIEW
2.1 Conceptual Literature
In the theories of economic development advocated by Lewis (1954), rapid industrial
growth is fueled by the agricultural sector. He saw agriculture as freeing disguised labour
for industrial production and hence the engine of growth and development of any society
must start with agricultural production. Schultz (1964) argued that many poor countries are
in a situation of “high food drain,” in which they have “a level of income so low that a
critically large proportion of the income is required for food.” In his view, agriculture is
important for economic growth in the sense that it guarantees subsistence for a society
without which growth is not possible in the first place. When countries can meet their
subsistence needs, economic growth will emerge.
As agricultural productivity increases, rural income increases thus creating demand for
domestically produced industrial products. As emphasized by Lewis (1954) in his report on
industrialization in the Gold Coast, increased rural purchasing power is a valuable stimulus
to industrial development. The lack of purchasing power of the rural poor, who comprised
the majority of the population, displayed low productivity in agriculture. Hence, with
lack of increased agricultural productivity, there would be no sufficient market for
agricultural goods (Nurkse, 1959).
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The value of production and consumption linkages is exemplified by Adelman (1984)
through his idea of agricultural demand led industrialization (ADLI). The author advocates
a development strategy driven by agriculture rather than exports because of these linkages.
Increased agricultural productivity should be the initiator of industrialization. He added that
emphasis should be placed on small-to-medium-size farmers because they are more likely
to use domestically produced intermediate goods as opposed to large-scale producers who
might import machinery and other inputs, which would weaken the linkages between
agriculture and other sectors.
2.2 Theoretical Literature
Over the years, the agro-pessimists have remained doubtful about the established role of
agriculture in economic development andput forward several arguments. For instance,
Gollin (2010) pointed out that the large share of agriculture in many developing economies
does not immediately imply that overall growth has to be based on an ADLI-type strategy.
Dercon (2009) believes in the possibility that the causation might run from economic to
agricultural growth. If agriculture is not the most productive in the entire economy, e.g. it
has no comparative advantage, supporting it is not the best route to economic progress.
Growth may be driven by the other sectors of the economy that provide people with the
prospect of leaving the marginalized farm. Hence, this type of economy is better off
exporting nonagricultural goods and importing food than relying on agriculture-led
industrialization.
With lower productivity in agriculture, wages will be higher in the modern sector, which
induces labour to move out of agricultureinto the modern sector, which in turn generates
economic growth.
Collier (2006), suggests “urban dynamism” as being the key to solving agriculture’s
problems. He is against the idea of a smallholder agricultural development strategy. He
notes that though the poor earn their livings from smallholder systems, there is little
evidence that productivity can increase sufficiently within these systems to generate growth.
He then proposes that a country’s development efforts should be directed at large-scale
commercial farms and the non-agriculture sector, for these could ultimately provide
increased livelihood opportunities for the poor.
There are several other arguments put forward by the agro-pessimists. For instance, they
contend that increasing agricultural productivity is becoming difficult, as the natural
resource base on which agriculture depends is poor and deteriorating. Skeptics also consider
the East Asian miracle as concrete evidence of the case where growth is achieved without
the broad agriculture-based development. For the Korean economy, Amsden (1989)
conclude that industrialization is achieved without any preceding agricultural revolution.
2.3 Empirical literature
In history, Aristotle, Aristarchus and Warren Anderson and many others provide us with a
frame that, agriculture is the key to the growth and development of any nation. The
Physiocrats in their ideology believe that agriculture is the sole engine that drives any
economy to her promised land. That is, out of the poverty line and obscurity; these thinkers,
the Physiocrats strongly have fate in the agricultural sector which serves as the propeller of
an economy. In essence, the Physiocrats think that the productivity and prosperity of any
nation either developed or less developed nation is hinged on the agricultural sector.
Given the importance of the agricultural sector to economic growth, especially in
developing countries like Nigeria, some empirical studies have been carried out on
agriculture and economic growth. The work of Ijirshar (2015) focused on analyzing the
agricultural export and economic growth from 1970 to 2012. The co-integration test showed
Journal of Economics and Allied Research Vol. 7, Issue 2 (June, 2022) ISSN: 2536-7447
5 | P a g e
that a long-run relationship exists among the variables (real GDP, real exchange rate, real
agricultural output, index of trade openness and inflation).The error correction method
shows that agricultural export has contributed positively to the Nigerian economy. In the
same vein, Odetola and Etunmu (2013) found that from 1960 to 2011, the agricultural sector
has contributed positively and consistently to economic growth in Nigeria, reaffirming the
sector’s importance in the economy. It was further affirmed using the Granger causality test
which showed that agriculture growth granger-causes GDP growth and a reverse
relationship was found.
A study carried out by Oyetade and Oluwatoyese (2014) on the effect of the agricultural
sector as the determinant of economic growth, using a time series econometric model from
1980 to 2011 covering 30 years. The study modelled several agriculture sector variables
namely food/crop production, fishery and forestry, as the explanatory variables against the
dependent variable, gross domestic product (GDP). The study revealed a positive
relationship between the agricultural sector and economic growth. The study also
discovered the agricultural sector as the determinant for exportation, if given due attention
in all ramifications in terms of funding and providing the enabling environment for the key
actors in the sector. The study also submitted that there are constraints to the full attainment
of agricultural sector progress.
Aremu (2014) using a data set of 30 years, that is, from 1981 to 2012, investigated the role
of agriculture in economic growth and development. He examined the role that the
agricultural sector played in the advancement of the Nigerian economy, considering the
years of neglect by the government and decision-makers. Aremu’s research used
econometrics to validate his hypothesis where he used the Solow growth model that
included gross capital formation (GCF) as the proxy for capital, labour proxy by post-
secondary enrollment, while agricultural output and economic growth and development as
a proxy by real gross domestic product (RGDP). The restricted Error Correction Approach
was employed for the long-run relationship. The study revealed that agriculture plays a
remarkable role in the economic growth and development of Nigeria. From his findings, it
was shown that the agricultural sector still contributed to gross domestic product, though,
there has been a decline since the 1990‟s explained by the arrival of the new bride (oil
discovery) in the late 1970‟s.
Ogundari and Awokuse (2016) went further to unequivocally support the role of improved
agricultural productivity in reducing food insecurity, stating the major challenge in sub-
Saharan Africa’s (SSA) agricultural sector is sustained agricultural productivity. Fuglie and
Rada (2013) argue for sustained agricultural productivity to be achieved, policy measures
that start with the dissemination of agricultural technologies and practices to farmers should
be established and investment in research and development encouraged.
However, Desai and Rudra (2018) think that most developing countries are transitioning
from traditional agriculture and moving up the value-added chain toward processed food.
O’Ryani and Miller (2003) in an earlier study on the role of agriculture on poverty
alleviation, income distribution, and economic development for the Chilean economy
conclude that agriculture and agro-industrial sectors are essential to alleviate poverty.
Furthermore, an increase in labour productivity in agriculture has a higher impact on the
decline of poverty incidence than an increase in the industrial sector.
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Ekiran et al. (2014) examined the relationship between agricultural export and economic
growth in Nigeria usinga multivariate Johansen co-integration analysis, from 1980 to 2012.
The findings from this research revealed that agricultural output has a long-run relationship
with the is seen as a key driver of economic growth and development of the Nigerian
economy. It was advocated that government should pay attention to agricultural export, as
it serves as a stimulant for the much canvass economic expansion and development in the
Nigerian.
Given that there have been several views on the topic, some of the researchers, (Okoro,
2011) find a positive causality that is, a positive relationship between the agricultural sector
and the Nigerian economy while others (Dim, 2013) found contrary results from their study.
Ahungwa et al., (2014) examined the impact of agriculture on GDP for 53 years, precisely
between 1960 and 2012 using time series data. The finding from their work revealed that
the agricultural sector’s share of GDP experiences a decline. The agricultural sector still had
a superior lead over other sectors, from 1960 to 1975.
3. METHODOLOGY
This research employs the use of the time series econometrics technique to validate the
objectives of this study. The study spans 49 years, that is, 1971 to 2020. The sources of data
are the World Bank development indicators and the Central Bank of Nigeria. The study
employs the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests, to
test for stationarity of all variables involved in the model to avoid a spurious regression
analysis. It is a well-known fact that most macroeconomic data exhibit trends and
seasonality. Johansen cointegration test is also carried out to test for the long-run
relationship between variables considered, Granger Causality test and the VECM approach
were utilized in the study to capture the possible disequilibrium in the short run and the
speed of adjustment of the variables considered towards their long-run path.
3.1Theoretical Framework
This study is premised on the Solow-Swan neoclassical growth theory and its extensionsof
a constant-return to scale aggregate production function expressed as:
t =ttβ Bt (1)
where Y, K, L, and B represent real GDP per capita, real gross capital, labour, and the
Hicks-neutral productivity term, respectively. The contribution of agriculture to aggregate
economic growth could be modelled as an intermediate input in the agriculture sector
(Timmer, 1995; Ruttan, 2000). Early development theories viewed agriculture as an
important source of resources to finance the development of other sectors within the
economy.
Thus, agricultural production growth serves as an engine of growth for the overall economy.
Hwa (1988) argues that agriculture is an engine of growth and added agriculture to the
standard Solow-Swan growth equation as a measure of linkages between the rural and
industrial sectors of the economy. Similarly, we also include additional determinants of
growth (oil rent) that are robust in explaining economic growth (Davis, 1995; Maloney
2001).
t = Lβ Xtφ (2)
Taking natural logs of equation (2) and including an error term yield:
= + + (3)
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7 | P a g e
According to the agricultural demand led industrialization growth literature, agricultural
productivity is expected to have a positive effect on aggregate economic growth, while Paul
Collier (2006), posits that oil rent is expected to have a positive effect on economic growth.
3.2Model Specification and Variables
To analyze the impact of the agricultural sector on the Nigerian economy’s growth,
twovariables are considered as the explanatory variables that were chosen based on previous
empirical studies and economic intuition. These variables are agricultural output (Lt) and
oil rent (Xt). Economic growth is measured by RGDP per capita (Yt). The data obtained
from the World Bank Development indicator (WDI), Span the period from 1970 to 2020.
The formulation of the model is given below.
t = Lβ Xtφ (2)
The stochastic form of the model is as follows
= + + (3)
Where,
Yt = Real Gross Domestic Product per capita
αo = intercept (constant),
Lt = Agricultural output (% GDP),
Xt = Oil rent (% GDP),
ut = Stochastic term (unobserved).
A priori expectation : Β, φ > 0
4. RESULTS AND DISCUSSION OF FINDINGS
4.1 Empirical Analysis
The first step is to conduct a unit root test for all the variables and test for the stationarity of
the variables, which is a necessary condition for understanding the long-run behaviour of
variables. In carrying out this test, the rule of thumb is that if the absolute value of ADF and
PP test statistic is greater than McKinnon's critical value at 5%, we reject the null hypothesis
that the variable is nonstationary. The variable is deemed stationary when the absolute value
of the ADF and PP statistics test is greater than the critical value at 5%.
Table 1: Augmented Dickey-Fuller (ADF) Unit Root Tests
Variables
ADF
@Level
Critical
value@5%
ADF at first
difference
Critical
value@5%
Order of
integration
Yt
-1.403361
-2.921175
-5.662821
-2.922449
1(1)
Lt
-2.579393
-2.921175
-6.727094
-2.922449
1(1)
Xt
-2.117749
-2.921175
-5.216472
-2.922449
1(1)
Source: Extract from E-view 9 output 2022
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Table 2: Phillips- Perron (PP) Unit Root Tests
Variables
PP @Level
Critical
value@5%
PP at first
difference
Critical
value@5%
Order of
integration
Yt
-1.474037
-2.921175
-5.726944
-2.922449
1(1)
Lt
-2.6943389
-2.921175
-6.565435
-2.922449
1(1)
Xt
-2.093359
-2.921175
-5.129292
-2.922449
1(1)
Source: Extract from E-view 9 output 2022
From Tables 1 and 2, all the variables are nonstationary at levels. To make all variables
stationary at the same level, the test is run on the first difference, thereby making all
variables stationary at the order I(1). In absolute terms, the ADF and PP test statistics are
greater than the critical value at 5%. Therefore, the variables are stationary at first
difference. Co-integration requires all the variables to be integrated in the same order.
A Co-integration test using the Johansen technique is used to ascertain the long-run
relationship between the dependent variable (Yt) and the independent variables (Lt, and Xt).
The decision rule states that if the values of trace statistics or maximum Eigenvalue are
greater than the critical values at 5%, then the null hypothesis of no co-integration is
rejected, which suggests co-integration among variables, implying a long-run equilibrium
relationship.
Table 3: Johansen Co-integration Test Results
Null
Hypothesis
Eigenvalue
Trace
statistic
Critical
value at 5
percent
Max-Eigen
statistic
Critical
value at 5
percent
α = 0
0.347760
36.53278*
29.79707
20.93979
21.13162
α ≤ 1
0.260198
14.59299
15.49471
14.76725*
14.26460
α ≤ 2
0.016711
0.825744
3.841466
0.825744
3.841466
Notes: α Represents at most the number of cointegrating equations. * Denotes significance
at the 5% level.
Source: Authors’ computations using E-view 9.0
From Table 3, we can see that under the hypothesized number of CE(s), at none*, the value
of the trace statistic is greater than the critical value at 5%. Therefore, we concludethat there
is one co-integrating equation, meaning there is a long-run relationship between the
dependent variable and one co-integrating explanatory variable. Also, the maximum
eigenvalue test, the Max-Eigen statistics at most 1 is greater than the critical value at 5%,
thereby concluding that using the Max-Eigen test, there is a long-run relationship between
the dependent variable and two co-integrating equations.
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Table 4. The result of vector error correction model to long-run causality
C
(lnyt-1)
(lnlt-1)
(lnxt-1)
ECTt-1
Summary
Δ(lny)
-0.0144
0.0117
(0.2252)
0.2939
0.1846
(0.1191)
0.0819
0.0519
(0.1222)
0.2284
0.2913
(0.4376)
-0.0144
0.0117
(0.2252)
R2: 0.2527
Adj. R2:
0.1219
F-stat: 1.93
Prob F-
Stat0.089)
Δ(lnl)
0.0873
0.0662
(0.1945)
-1.0083
0.3681
(0.0092)**
0.1475
0.1034
(0.1616)
-1.2031
0.5809
(0.0449)*
-0.4712
0.0702
(0.0000)**
R2: 0.6296
Adj. R2:
0.5648
F-stat: 9.717
Prob F-
Stat(:0.0001)**
Δ(lnx)
0.0019
0.0217
(0.9319)
-0.1279
0.1206
(0.2949)
-0.0274
0.0339
(0.4232)
-0.1691
0.1903
(0.3795)
-0.1249
0.0657
(0.0643)
R2: 0.1749
Adj. R2:
0.0305
F-stat: 1.2119
Prob F-
Stat(:0.3188)
Source: Authors’ computation using E-view 9.0.
From the cointegration results in Table 3, both max-Eigen and trace statistics reject the null
hypothesis of no cointegration at the 5% level. Specifically, both statistics confirm the
existence of a cointegrating equation among the variables, and the vector error correction
model (VECM) can be applied.
Table 4, shows the VECM is sensitive to the selection of optimal lag length. Thus, the
necessary lag length of agriculture added value (Lt), Oil rent (Xt) and economic growth (y)
series is determined by Schwarz Information Criteria (SC), Akaike information criterion
(AIC) and it reveals the optimal lag length of one for the model. Besides, the VECM result
shows that the error correction term, ECTt-1(0.4712) in the second model (i.e. Lt equation)
is negative and statistically significant at a 1% level. This result conforms to the findings of
Akiran et al 2014, which suggests the validity of the long-run equilibrium relationship
between the variables. It also implies that 47.12% of disequilibrium from the previous
period’s shock converges back to the long-run equilibrium in the current period. In other
words, there exists unidirectional long-run causality running from economic growth, oil rent
to agriculture added value.
Meanwhile, the VECM results of (Y equation) showed that there is no long-run causality
from agriculture added value (Lt) and oil rent (Xt) to economic growth. Similarly, the (Xt)
equation showed that there is no presence of a long-run equilibrium relationship between
Journal of Economics and Allied Research Vol. 7, Issue 2 (June, 2022) ISSN: 2536-7447
10 | P a g e
agriculture added value, and economic growth on oil rent. This is evidenced by the value of
ECTt-1being insignificant in the model.
We tested whether the various lags of the independent variable can jointly influence the
dependent variable or not. In other words, the short-run relation can also be tested among
the dependent and past values of the independent variable jointly. It can be tested with the
help of the Wald statistics test as presented in Table 5.
Table 5. The Result of Wald Tests to Short-run Causality
Dependent
variable
Δ(lnyt-1)
Δ(lnlt-1)
Δ(lnxt-1)
Inference (short-run
causality)
Δ(lny)
-
-
8.4055
(0.0150)*
0.3568
(0.6899)
Δ(lnLt) on Δ(lny): short-run
causality
Δ(lnx) on Δ(lny): no short-run
causality
Δ(lnL)
3.9421
(0.0194)*
-
-
2.2307
(0.1074)
Δ(lny) on Δ(lnL): short-run
causality
Δ(lnx) on Δ(lnL):no short-run
causality
Δ(lnx)
2.0240
(0.1327)
0.7165
(0.4884)
-
-
Δ(lny) on Δ(lnx):no short-run
causality
Δ(lnL) on Δ(lnx):no short-run
causality
Source: Authors’ computation using E-view 9.0.
The next is the hypothesis-null test at the short-run causality is that the past lags of the
independent variable, i.e. agriculture added value, and oil rent cannot jointly influence the
value of the dependent variable, i.e. economic growth. If the probability value of Chi square
in the Wald Statistics is less than 0.05, the Null Hypothesis is rejected or vice versa.
The same process is repeated for testing the short-run relationship between past lags of the
independent variable, i.e. economic growth, agriculture added value and the dependent
variable, i.e. oil rent. Similarly, for testing the short-run between past lags of the
independent variable, i.e. economic growth and oil rent and the dependent variable, i.e.
agriculture added value.
From table 5, it is confirmed that there is no short-run relationship between economic
growth and agriculture added value toward oil rent. However, the Wald statistics test shows
that between agriculture added value and economic growth, there exists a short-run. The
past lags of value-added agriculture jointly impact economic growth in the short run. There
is no short-run between economic growths to oil rent. The past lags of agriculture added
value impact the economic growth in the short run.
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Table 6. The result of the Granger Causality Tests
Null Hypothesis:
Lag
F-Statistic
Prob
LT does not Granger Cause
YT
1
6.53891
0.0138
YT does not Granger Cause
LT
1
2.10241
0.1537
XT does not Granger Cause
YT
1
5.07918
0.0289
YT does not Granger Cause
XT
1
0.41283
0.5237
XT does not Granger Cause
LT
1
1.14164
0.2908
LT does not Granger Cause
XT
1
0.07281
0.7885
Source: Authors’ computation using E-view 9.0.
To find out the causality between economic growth, oil rent, and agriculture added value,
we used another alternative approach which is the Granger causality test.
From Table 6, the estimation result explains that the unidirectional relationship between
agriculture added value toward economic growth at a significant level of 1%. It means an
increase in the agriculture added value leads to economic growth increases. These results
are well supported by the previous studies conducted by Aremu (2014); Ogunbadejo and
Zubair (2021) and Okoro, (2011) but contrary to the view of agro-pessimist like Dercon
(2009) who opined the possibilities of causation running from economic growth to
agriculture value-added. Specifically, the null hypothesis that agriculture does not granger-
cause economic growth could be rejected at the 5% level for this study. This result is
consistent with previous findings for developing countries by Tiffin and Irz (2006) who also
concluded that agriculture value-added ‘Granger Cause’ economic growth. This finding
may reflect the so-called ‘Dutch Disease’ where resources from the agriculture sector were
siphoned to the industrial sector (Fardmanesh,1991).
Similarly, the relationship between oil rent and economic growth is unidirectional, where
oil rent increase will increase economic growth at a significant level of 5%. These findings
were also in line with the result of the studies by Fulnhas et al (2015), Matallah and Matallah
(2016) and David and Emmanuel (2020).
5. CONCLUSION AND POLICY RECOMMENDATIONS
The primary aim of this study is to investigate the relationship between agriculture and
economic growth and to enable policymakers to understand the linkage that facilitates the
direction of investment and policy implementation.
This study empirically examined the contribution of the agricultural sector to economic
growth in Nigeria. The study also queries if there exists a long-run relationship among the
variables in the study. Before the establishment of a long-run relationship, the stationarity
properties were also tested with the conventional unit root testing approaches of ADF and
PP to aid our regression analysis.
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12 | P a g e
The empirical analysis employed a co-integration and Johansen error correction
specification on a time series data for economic variables, which includes agriculture value-
added, oil rent and economic growth from the period 1970 to 2020 to explain the variation
in agricultural output. Results from the Granger causality test indicate a unidirectional
relationship between agriculture and economic growth which implies no backward and
forward linkages in the input-output interface.
This study reveals that in the short run, a positive statistical relationship exists between the
log value of agricultural output and RGDP. This shows that agriculture is a viable source
of economic growth in Nigeria.
Furthermore, the error correction term (ECTt-1) with a coefficient value of -0.4712 in the
third model (agricultural added value equation) revealed that about 47.12% of the imbalance
of the previous period shocks was corrected in each period, while the Johansen
Cointegration results confirmed the existence of a long-run relationship among the
variables.
Based on the finding, the study concluded that an increase in agriculture output and oil rent
leads to increased economic growth both in the long run and short run. The empirical
analysis shows the causal flow from agriculture value-added and oil rent to the economic
growth and no reverse flow evidence. It shows that the resources from agriculture value-
added and oil rent were the channel to develop other sectors of the economy.
A major policy implication arising from this study is the need for increased government
investment in the agricultural sector to boost yield in agricultural productivity. With
strategic investment and support to the oil sector, the necessary inputs to boost agriculture
could be obtained at minimum cost and agricultural productivity rising to provide necessary
input for other sectorsof the economy. In the same vein, there is a need for government
policy to encourage agriculture extension services, and to educate rural farmers on the
advantages of collaborating with commercial farmers and local financial institutions for the
purchase of farming equipment, tools, and seedlings to improve productivity. To tackle the
problem of the high cost of imported equipment posed by foreign exchange variability, the
government should encourage the fabrication of local farming implements by artisans.
Another policy strategy that is driven by agriculture (agricultural demand led to
industrialization), advocated by Adelman (1984) could be followed. For the Nigerian
economy, agriculture and overall economic growth drive each other, suggesting that the
country can enjoy economic prosperity by investing in agriculture. Development policies
should also be tailored to the specific economic environment of a country and should
reinvestigate the development strategies for a possible overemphasis on agriculture.
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PUBLIC EXPENDITURE AND INFRASTRUCTURAL DEVELOPMENT IN NIGERIA: A
COMPARATIVE ANALYSIS OF DEMOCRATIC AND MILITARY REGIMES
TEMIDAYO O. AKINBOBOLA
Department of Economics
College of Arts, Management and Social Sciences,
Chrisland University, Abeokuta and Obafemi Awolowo University, Ile-Ife, Nigeria
Phone No: 08037172271
Email address tbobola@yahoo.co.uk
KEHINDE H. ODERINU
Department of Accountancy
School of Business and Management Studies,
Federal Polytechnic, Ede, Osun State
Phone No: 08034276642
Email address: kehindehassana@gmail.com
ABIODUN S. OLAYIWOLA*
Department of Economic,
College of Arts, Management and Social Sciences,
Chrisland University, Abeokuta, Nigeria
Phone No: 08034990654
Correspondence Email Address: abiodunolayiwola37@gmail.com
ABSTRACT
The Nigerian government has over the past decades increased spending on infrastructure in
the yearly budget but the level of infrastructural development does not seem to correlate
with the rate of government spending. It on this account that we examined the effect of
public spending on infrastructure and economic development in Nigeria with the view to
compare the extent at which public expenditure on infrastructure influences economic
growth during the military regime (1983 to 1999) and democratic government (1999 to
2018). Using the ARDL estimation technique, we discovered that public expenditure on
education, public expenditure on transportation and communication (TCM) all have positive
but insignificant effects on economic growth while public expenditure on agriculture has a
significant positive effect on economic growth in the short run. Whereas both public
spending on health services and public spending on road and construction has significant
negative effects on economic growth in the short run. However, all these public expenditure
variables have no significant influence on economic growth in the long run. This study
concluded that public infrastructure expenditure during the democratic government era
(1999 to 2018) is not significantly different from public expenditure on infrastructure during
the military regime (1983 to 1999) due to widespread corruption and inconsistent reform
policies in the economy and therefore recommended that infrastructural sector development
should be prioritized at all levels of government by increasing spending on infrastructure to
at least 25% of annual total spending.
Keywords: Public expenditure; Economic growth; ARDL approach; Nigeria.
JEL Classification: E21; O1; 019
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I. INTRODUCTION
One of the indices of growth, according to Denis Goulet (2006), is the quality of life, which
is determined by access to basic necessities of life, such as basic infrastructure. As a result,
improvements in such infrastructure would go a long way toward assisting any country's
growth and development. Public infrastructure is a critical tool in the economic process,
particularly in underdeveloped countries, where rigidities in the structure, weak support
systems and institutional structure, decreasing growth, high levels of corruption, and policy
uncertainty characterize these countries. World Bank (1994) stated that infrastructure
provision in the right quality and quantity determines a country's success or failure in many
aspects of the economy. The importance of government spending on infrastructure as well
as the availability of infrastructure may help to foster the concerned country's growth and
development.
Literature like Webb (2004), Hasselgren (2013), and Babatunde (2018), have shown that
the government has been solely responsible for infrastructure provision even from the time
of classical economists due to its huge capital requirement. Mundle (1998) as cited by
Ekpung (2014), states that certain public goods, such as protection of citizens, governance,
and a safe environment, cannot be offered by the market because no customer is exempted
from its consumption once these services are provided. Though encouragement of the
participation of the private sector in economic activities has been part of the
recommendation of previous studies to boost developing countries economic growth, the
cost of providing infrastructure is high and has therefore weakened their participation in
helping out to make available basic infrastructures and therefore the reason for the
unattractiveness of all infrastructural sub-sector. Year after year, huge public expenditures
for infrastructure were provided for by the government in the budget.
The divergent view has however been obtained from past studies as to the effects of
Nigeria’s government spending on infrastructural development. In their study on the joint
effects of government recurrent and capital spending on the economic growth of Nigeria,
Oni, Aninkan and Akinsanya (2014), asserts that the effect of recurrent spending on growth
is higher and faster than that of capital expenditure. Previous studies like Devarajan,
Swaroop, and Zou (1996), and Mohsen and Nafise (2016) have also shown that expenditure
on infrastructure increases seems not to have a significant impact on the economy,
especially in poor countries where the level of its availability has not met the need of the
citizens. The Nigerian government has over the past decades increased her spending on
infrastructure in the yearly budget. Despite these continuous increases in government
spending in Nigeria, the level of infrastructural development that can be physically
accounted for does not seem to correlate with the rate of government spending on
infrastructure. Citizens especially those in the rural areas do not have easy access to potable
water, good road and electricity supply is not reliable (Raheem, Ayana, & Fashedemi,
2014). However, the trend and pattern of government spending are dictated by various
factors like population, degree of urgency of public need, inflation, tax revenue, public debt,
and government era, which is, civilian and military era as the case is in Nigeria.
The current claim of a yearly increase in public debt by the Nigerian government on the
basis that the bulk of this public debt (excess spending) is expended by the government on
infrastructure has called for the reason to assess if over the years increased government
budget has assisted or resolved the state of infrastructural development in the country. The
question that therefore comes to mind is if, an increase in public spending has translated or
influenced the rate of infrastructural development in Nigeria. Hence, the need to look into
how prudence in public spending could be used to achieve the efficient and effective
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provision of infrastructures that are accessible for the benefit of the Nigerian citizens.
Studies on public spending have concentrated much on the revenue side of the government
budget with emphasis on the tax system as a source of government cash inflow in the
discharge of her responsibilities. Other relevant ones that have ventured into the expenditure
side of the government budget have done so mostly in relation to developmental challenges
while some have viewed the development of the Nigerian economy with respect to national
security, and a few have looked at government expenditure on infrastructure.
An observation from the previous studies on the connection between government
infrastructure expenditure and economic growth did not break down government spending
into sectors of allocation but had considered aggregate government spending in their study.
Those who break down government spending into sectors carried out their research on
government infrastructure spending in relation to the expansion of the economy over a
period that has an overlapping of both the military and democratic era. None of the previous
studies carried out research separating the period of study into a democratic or military
regime. Take for instance; the public expenditure on education witnessed tremendous
fluctuations over the study period such that during the military regime (1983 to 1999), the
percentage change in recurrent expenditure on education rose from 22.66 percent in 1984
to 30.01 percent in 1985, decreased as low as -14.35 percent in 1987, increased to 548.34
percent in 1988, declined to its lowest value of -76.81 percent in 1992, rose sporadically to
peak at 2949.24 percent in 1993, decreased again to -16.88 percent in 1994 before it rose
haphazardly to 220.91 percent in 1999. In the democratic era, trend of the percentage change
in public expenditure on education followed irregular pattern, it reduced from 32.89 percent
in 2000 to -31.18 percent in 2001, increased to 101.91 percent in 2002, declined to -19.55
percent in 2003, rose to 43.74 percent in 2006, decreased to -16.38 percent in 2009,
increased again to 96.60 percent in 2011 before it declined to -11.95 percent in 2014 and
rose to 15.18 percent in 2018. Whereas, during the military regime (1983 to 1999),
percentage change in public expenditure on health services increased from 22.6 percent in
1984 to 30.0 percent in 1985, declined to -69.1 percent in 1987, increased sharply again to
923.3 percent in 1988 and decreased till it reached -75.7 percent in 1992 which is the lowest
for the period of study. This decline was immediately followed by a tremendous increase to
2478.3 percent in 1993 which is the highest value for the period of study. In just a year span,
it declined to -45.9 percent in 1994 and rose again to reach 250.8 percent in 1999. During
the democratic era (1999 to 2018), the percentage change in expenditure on health services
started with a negative value of -8.5 and increased to 65.6 percent in 2002. It therefore
continuously fluctuates throughout the democratic era (1999 to 2018) as recorded change
values.
In view of this and the lack of comparative evidence of public expenditure on infrastructural
influence on economic growth nexus in Nigeria, this paper examines the effect of
government expenditure on infrastructure during the military and civilian administration
and also brings up a position to be able to distinguish if the military and democratic eras of
government have a correlation with the effect of huge government spending on
infrastructural development. The rest of the study is structured as follows; section two is on
a survey of the empirical literature. Section three: explains the methodology and analyses
the data. Section four presents the empirical results while the summary and conclusion of
the study are outlined in section five.
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2 LITERATURE REVIEW
Studies on public spending have concentrated much on the revenue side of the government
budget with emphasis on the tax system as a source of government cash inflow in the
discharge of her responsibilities. Other relevant ones that have ventured on the expenditure
side of the government budget have done so mostly in relation to developmental challenges
while some have viewed the development of the Nigerian economy with respect to national
security, and a few have looked at government expenditure on infrastructure. An
observation from the previous studies on the connection between government infrastructure
expenditure and economic growth, did not breakdown government spending into sectors of
allocation, but had considered aggregate government spending in their study. Those that
break down government spending into sectors carried out their research on government
infrastructure spending in relation to expansion of the economy over a period that has an
overlapping of both the military and democratic era. None of the previous studies carried
out research separating the period of study into a long democratic or military regime has
revealed in the following reviewed studies on the subject matter.
Chiou-Wei, Chen & Zhu (2008) investigated the connection between energy consumption
and economic growth, between1971 to 2011. The study revealed that causality does not run
from the use of energy to the expansion of the economy. Olorunfemi in 2008 investigated
the relationship between infrastructural services and Nigerian manufacturing production,
using Vector Auto regressive model (VAR) and granger causality test, as well as time series
data from 1981 to 2005. His work reveals that transport and electricity services did not
granger-cause growth in the manufacturing sector, however, there was a strong correlation
between governmental capital expenditure and economic growth. Batterman, Eisenberg and
Hardin (2009) also argued that inadequate water infrastructure is a major challenge facing
majority of developing countries and concluded that providing this key infrastructure will
not only foster economic development, but it will also reduce the rate of diseases in the sub-
Saharan Africa. Gbadebo and Okonkwo (2009) in their research into the impact of energy
infrastructure on Nigeria's economic growth between 1970 and 2005 adopting the co-
integration approach documented that the current period's energy use and economic growth
have a positive relationship. Gbadebo and Okonkwo (2009) using the co-integration
approach in their research into the impact of energy infrastructure on economic growth in
Nigeria from 1970 to 2005, that the current period's energy use and economic growth have
a positive relationship. Wagner in his law explains “that economic growth is relative to the
size of government”. The law explains that as an economy's per capita income rises, so does
the size of the public sector grow as well (Obiechina, 2010).
Umar and Zakari (2011) with the use of Auto-regressive distributed lag (ARDL) bounds
testing procedure as well as time-series data between 1980 to 2010, examined the
relationship between energy infrastructure and Nigeria's economic growth. The study
revealed that the use of petroleum, gas, and electricity has a long-term relationship with
economic growth. Bolaane and Ikgopoleng (2011) in studing the connection between water
infrastructure and economic accessibility in Botswanna, found that there is a need for
adequate water facilities to protect human health, and enhancthe e environment and improve
cultural values.
Manase, Nkuna, and Ngorima (2009) studied how communities with high Human
Immunodeficiency Virus (HIV) rates benefited from the provision of water and sanitation
infrastructure in rural areas of South Africa, and concluded that appropriate financing of
this infrastructure has technically reduced the rate of spread of HIV diseases in the country.
The desire for infrastructural development through the provision of water, with the
expectation that the percentage of people without access to clean water should reduce by
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2015, did not eventually materialize as the situation became worse, as more governments of
these countries failed to invest in water infrastructure (United Nations, 2010).
In Nigeria, Nurudeen and Usman (2010) looked into the relationship between government
spending and economic development, using the error correction method and co-integration
approach. They observed that state spending was having a negative effect on the economy.
Although, the research established that a rise in government spending on transport and
communication promotes economic growth. But it was not able to explain the condition and
behavior of the specified variables used. Samli (2011), stated that a reasonable quality of
life is guaranteed through infrastructural development as this helps to expand the markets
and hence, economic growth. Edame (2014) used ECM to investigate the factors that
influence public infrastructure expenditure in Nigeria he discovered that the pace of external
reserves, urbanization, government revenue, population density, and the form of
government all have an effect on public infrastructure spending. Yikudi (2014) examines
the effectiveness of the bond market as a viable engine of infrastructure in Nigeria from
1999 to 2012, drawing on experiences from Lagos state, India, Mexico, Poland, South
Africa, and the United States. The study essentially considers discretionary appropriation,
public-private partnerships, bank funding, and capital markets as the only likely
determinants of infrastructure. The study concludes that municipal bonds are useful for
financing public works projects such as infrastructure production with the reliance of
governments on funds from constitutional allocations emphasized.
According to Uma, Onwusogbulu, and Enwere (2014), infrastructure repositioning is a
viable strategy for long-term growth. According to the study, adequate investment in
transportation infrastructure is critical for Nigeria's competitiveness. Nwaka and Onifade
(2015) also observed that, in few African countries’ economic growth and the size of
government are positively related. Iheanacho (2016) looked into the role of government
spending in Nigeria and discovered a positive effect and long-term relationship between
recurrent spending and economic growth. Shobande & Etukomeni (2016) in their study
titled Infrastructural Investment and Industrial growth: A Private Investment Led Approach,
using Autoregressive Distributed Lag (ARDL) bound testing approach, examined the
impact of infrastructural investment on industrial growth in Nigeria, with the availability of
the annual time series data obtained from the statistical bulletin of Central Bank of Nigeria’s
(CBN) from 1960 to 2015, suggests the variables exhibit a long run relationship while a 1%
rise in industrial output is accounted for by an increase in infrastructural, industrial
relationship between government and labor growth in the short run. They therefore conclude