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Sahel Analyst: ISSN 1117-4668 Page 52

INFRASTRUCTURAL DEVELOPMENT, ECONOMIC GROWTH

AND POVERTY IN NIGERIA

Alhaji Bukar Mustapha1

Mohammed Danladi Tukur1

Jiddah Ajayi1

Abstract

This paper examines the impact of infrastructural development on economic

growth and poverty in Nigeria. The study used government capital

expenditure as a proxy for infrastructure development. The data was analysed

using seemingly unrelated regression estimation technique (SURE). Results of

the study revealed that economic growth, employment rate and real wages

reduce poverty. The findings also suggest that investment rate, population

growth, capital expenditure in education are found to be substantially strong

in increasing economic growth. The results of the employment model indicate

that economic growth, education in health, agriculture and transport sector

exert significant influence on the employment rate. Finally, results of the wage

model indicate that capital expenditure in education, health and transport are

positively related to a real wage. Therefore, the study recommends that there

is need to increase capital expenditure in education, health, and transport this

will help increase economic growth, employment and wages, and, thus

reduces poverty. This study contributes to the existing literature on

infrastructure and poverty as it tried to explore the impact from a sectoral

perspective.

Keywords: Capital expenditure, Infrastructure development, Economic

growth, poverty reduction

Introduction

The relationship between infrastructural development and economic growth

has been widely discussed in the development literature, but the nexus

between public infrastructure, economic growth and poverty are still

debatable. It has been argued that inadequate resources prevent Less

Developed Countries (LDCs) to invest in basic infrastructure and this is a

major hindrance to economic development. Targeted investment in sectors

1 Department of Economics, University of Maiduguri, Nigeria.

[email protected]

mailto:[email protected]

Sahel Analyst: Journal of Management Sciences (Vol.15, No.6, 2017), University of Maiduguri

Sahel Analyst: ISSN 1117- 4668 Page 53

such as agriculture, education and health can promote economic growth and

help a very poor country to spring itself free from extreme poverty. For

example, the United Nations Millennium Project has re-emphasised the need

for a „big push‟ strategy in public investment to help poor countries break out

of their poverty trap and meet the MDG challenge. The report argues that, to

enable all countries to achieve the MDGs, there should be identification of

priority in public investments to empower poor people, and these should be

built into MDG-based strategies that anchor the scaling-up of public

investments, capacity-building, resource mobilisation, and official

development assistance (Renzio & Levy, 2006). Similarly, the World Bank

(2015) reports that for developing countries to achieve a rapid poverty

reduction objective, adequate investment in social infrastructure is necessary.

Therefore, it called on governments to identify pro-poor sectors and expand

their investment for economic growth and development.

The developing countries adopted several strategies including the Poverty

Reduction Strategy Papers (PRSPs) with the explicit objective of agriculture

and rural development. Consequently, some progress has been achieved as the

poverty rate in the developing world declined from 43.5 percent in 1990 to

13.4 in 2015 (World Bank, 2015). This indicates that the developing countries

as a whole have been successful in meeting the MDG target. However, the

poverty rate is still pervasive in some countries particularly in South Asia

(SA) and Sub-Saharan Africa (SSA) regions (World Bank, 2015). The report

also confirms that poverty reduction rates were lowest in SSA, with a poverty

rate of 41 percent as at 2015. That is about 403.2 million people live below

the poverty line. Unfortunately, the poverty rates in many countries including

Nigeria is far above the region‟s poverty rate. For example, the Nigeria

poverty rate is about 71.5 percent implying that over 120 million of the

population lives below the poverty line (National Bureau of Statistics, 2010).

It is evident that the capital expenditure has increased tremendously over the

years, from N6.6 billion in 1981 to N874.8 billion in 2012 (Central Bank of

Nigeria, 2011). Also, the Nigerian economy has experienced stable growth in

both nominal and real GDP, with an average growth rate of 6.4 percent in the

last decade. However, despite registering high economic growth the poverty

rate has been on the increase.

This paper, therefore, examines the impacts of infrastructure development on

economic growth and poverty reduction. This is essential for two main

reasons: First, to provide policymakers with more detailed information on the

investment(s) that is most effective for economic growth and poverty

reduction. Secondly, there is a growing concern about the disproportionate

expenditure allocation to the detriment of productive investment which is

necessary for sustainable growth and development and poverty reduction in

Nigeria. Nigeria is the country with the largest population in SSA with about

Infrastructural Development, Economic Growth And Poverty In Nigeria


one-fifth of the SSA population and accounts for 29 percent of SSA‟s total

poor. The rest of the paper is organized as follows: the following section

reviewed the literature. Section 3 describes the methods used and data

sources. Section 4 presents the analysis of results. Section 5 is the conclusion

and recommendation.

Literature Review

Government intervention in the less developed countries is inevitable, where

social and physical infrastructure is inadequate and private investment is

limited. According to the economic growth literature, for an economy to grow

and develop investment in infrastructures such as good transport system,

schools and hospitals services are necessary (Gupta & Verhoeven, 2001;

Mankiw et al., 1992; Barro, 1991; Romer, 1990). The relationship between

economic growth and poverty reduction is extensively acknowledged in the

economic growth literature and many of the studies report that high economic

growth is important for poverty reduction (Besley & Burgess, 2003;

Ravallion, 2001; Ravallion & Chen, 1997; Dollar & Kraay, 2000; Fanta &

Upadhyay, 2009; Stevans & Sessions, 2008). For example, Fanta and

Upadhyay (2009) examined the effects of economic growth on poverty from

16 African countries and found that economic growth has a strong impact on

poverty reduction, but the magnitude of the impact varies across countries.

Adam (2004) investigated the impact of economic growth on poverty in 60

developing countries using two measures of economic growth; the survey

means income and changes in GDP per capita. The study reports that

economic growth exerts significant influence on poverty in developing

countries, the magnitude of the effect depends more on how economic growth

is defined.

Similarly, Stevans and Sessions (2008) find a negative relationship between

economic growth and poverty in the United States. Fosu (2009) provide

evidence based on comparative global studies that economic growth leads to

poverty reduction in all regions with the exception of Eastern Europe and

Central Asia. The results for developed and developing countries are

consistent with the proposition that economic growth benefits the poor and

thus reduces poverty. This provides a strong support that economic growth is

one of the major determinants of poverty reduction. On the other hand, it has

been argued that economic growth reduces poverty as it creates employment

opportunities. Economic growth generates employment opportunities, which

would lead to increase in demand for labour and thus income thereby

increases the standard of living and purchasing power that in turn contributes

to poverty reduction (Suryahadi et al., 2012).

The classical economists argue that due to market failure firms and private

individuals under-invest in social and economic infrastructures such as



education, health, transport and roads. Sachs (2005); Kalt (1981) and

Friedman (1955) argue that public expenditure is important to promote growth

and mitigate poverty. Public spending raises aggregate demand, which in turn

improve overall growth and thus reduces poverty. The literature shows that

there is a positive relationship between government expenditure and GDP

growth (Rubinson, 1977; Ram, 1986; Lin, 1994). Conversely, Grossman

(1988), Mallow (1986) and Peden and Bradley (1989) report a negative

relationship between government spending and output growth. On the

theoretical connection between investment and economic growth, Lewis

(1954); Schultz (1961) and Romer (1990) highlight the importance of

accumulation of capital stock to economic growth and development. They

argue that an increase in investment raises productivity, which in turn results

in higher economic growth. Consistent with this, De Long and summers

(1991); Mankiw et al. (1992); Kormendi and Meguire (1985); Levine and

Renelt (1992); and Islam (1995) find evidence that gross domestic

investments as a share of GDP are positively related to growth. It has been

argued that the low rates of capital formation are responsible for the low rate

of economic growth in the developing economies (Chow, 1993).

The diverse economic effects of different categories of public spending have

been recognized in the economic literature. For example, Lin (1994) and

Easterly and Rebelo (1993) find that the composition of public expenditure

has a significant impact on economic growth. Furthermore, the economic

growth literature has shown that education and health expenditure are

positively correlated with economic growth, while an increase in economic

growth reduces poverty (Mosley et al. 2004; Gomannee et al., 2003; Fan et al.,

2002; Lockheed & Verspoor, 1992). Other variables such as expenditure on

agricultural and transport services are important determinants of economic

growth and poverty reduction as shown in some studies. For example,

Adejuwon and Nchuchuwe (2012) argue that increase in agricultural sector

improves agricultural output, in turn, raises household‟s income and thus

reduces poverty. On the other hand, public provision of improved transport

system reduces agricultural production costs to the farmers through easy

access to markets. This could improve household income and thus reduces

poverty. Thus, the poor state of infrastructure in the developing countries

inhibits economic growth and poverty reduction (Anderson & Renzio, 2006).

Therefore the relationship between public expenditure variables and poverty

are expected to be negative.

Kenworthy (1999), investigated the impact of social expenditure on poverty

reduction in Europe and OECD countries and report that the social

expenditure is found to be effective in reducing poverty, but to different

degrees across the countries. Similarly, Fan et al. (2002) studied the effect of

government expenditure on rural poverty across China by decomposing public


Sahel Analyst: ISSN 1117-4668 6

expenditure into different types and the findings revealed an investment in

education and rural agricultural infrastructure have greatly contributed to

poverty reduction in rural China. A study conducted by Gupta and Verhoeven

(2001) confirm that investment in education is associated with the rapid

economic growth and rising standard of living. Moreover, a study on the

composition of government expenditure, economic growth and poverty

indicates that rural agricultural and infrastructure investment contributed to

the growth of output in Ghana (Dorosh, et al, 1996). A cross-country study

shows that government expenditure in education, agriculture and housing

infrastructure have a positive impact on poverty reduction in many countries

(Mosley et al., 2004 and Gorman nee et al. 2003). An investigation into the

differences in poverty rates across India states shows that the differing level of

infrastructure development attributed to such variation in poverty rates among

the states (Ravallion & Datt, 2002).

Jung and Thorbecke, (2003) using CGE modelling approach to test the impact

of public education expenditure on human capital, growth, and poverty

reduction in Tanzania and Zambia, they find that the impact of public

investment and on poverty alleviation has been positive, but the results of the

policy experiment imply that the effects differ across the countries. Sevitenyi

(2012) examines the long run relationship between public spending and

economic growth to determine the direction of causality using cointegration

techniques and the Toda-Yamamoto Granger Causality test. He finds a

unidirectional causality from both aggregate and disaggregated public

expenditure to economic growth. This implies that an increase in government

spending stimulates growth, which is consistent with Keynes‟s hypothesis but

contradicts Wagner‟s law.

Bello and Roslan (2010) analyse the relationship between economic growth,

MDGs expenditure and poverty in Nigeria. The study employed state-level

panel data to analyse the effects of growth, MDGs conditional grants on

poverty reduction. The study necessitated by the increasing poverty amidst

appreciable rate of growth and MDGs expenditure over the two decades. They

find that the poverty reduction effects of the economic growth and MDGs

programs are not only ineffective but also counterintuitive. They attributed

this largely to lack of proper planning and improper identification of the poor

households. Amakom (2012) investigates the impact of public expenditure on

health and education at all levels of poverty reduction across rural and urban

households using Benefit Incidence Analysis (BIA). They find that the benefit

of primary education and primary health care are much higher than the effects

of tertiary education and health. They suggest that subsidizing primary

education and healthcare services may expedite poverty reduction than social

transfers if properly implemented.



Enyim (2013) assesses the effect of public expenditure on agriculture and

Agricultural Credit Guarantee Scheme Fund on poverty reduction using OLS

techniques on time series data from 1980-2009. He finds that the public

spending on agriculture has a significant impact poverty reduction. He

suggests that the public expenditure and agricultural funds should target the

rural poor, and recommends that priority should be given to agriculture

mechanization for increased food production and hence poverty reduction.

Based on a dynamic computable general equilibrium (CGE), Odior (2011)

argues that increasing the percentage share of health sector expenditure has a

significant impact on economic growth. The study further emphasizes that the

impact of increased health care services is not only to expedite economic

growth but also improves wellbeing. This implies that reallocating of funds

from unproductive sectors to health sector enables the government to expand

its free basic health services to the poor. Many studies argue that making

health care accessible to the vulnerable poor would improve the health status

of the poor and hence increases their productivity (Gupta, et al., 2003).

In conclusion, the literature reviewed shows that provision of roads, schools,

hospitals, and agriculture infrastructure promotes economic growth and

thereby lead to poverty reduction. The review further revealed that the effects

vary substantially across countries due to different policy choices. Public

investment in agriculture and rural infrastructure, education, transport and

communication has a strong positive impact on economic growth.

Furthermore, the literature shows that to complement the poverty reduction

impact of economic growth, there is a need for government to pay attention to

social infrastructure (Barro, 2000; Devarajan et al., 1996; Futagami et al.,

1993; Levine & Renelt, 1992). These studies have provided us with some

insight, but could not provide detailed information on the impact of the

different capital expenditure on economic growth and poverty. Hence, this

study improves on previous research by investigating the effect of different

types of public capital expenditure on growth and poverty in Nigeria.

Methodology

This study used seemingly unrelated regression estimation (SURE). In

principle, it may be possible to estimate the system of equations individually

using OLS. However, SUR was found to be more appropriate due to possible

correlations across equations and is most likely in the case of our expenditure

system. The SUR estimation procedure is an application of the generalized

least squares (GLS) procedure which is required to account for such

correlations. Zellner (1962) reports that the coefficient estimators obtained

from SUR regression are at least asymptotically more efficient than those

obtained from equation-by-equation OLS estimates.



The study adopts Fan et al. (2000) framework and some modifications were

made so that the framework is consistent with the focus of this study. The

analysis of the linkage between capital expenditure and poverty is based on

three channels: growth, employment and wages. The linkage between capital

expenditure and poverty is that economic growth means an increase in output

in an economy, which will stimulate aggregate demand; then an increase in

aggregate will cause demand for labour and thus increase the level of

employment and productivity. Therefore, the higher rate of employment and

productivity in the public expenditure framework can affect poverty in two

ways. Firstly, an increase in the rate of employment will cause a reduction in

poverty due to an increase in national wages and consumption. Secondly, an

increase in national output will lead to a rise in public expenditure. This study

is therefore designed around this conceptual framework.

Data Sources

The study used state-level poverty data, due to the unavailability of national

long time series poverty data, the data were obtained from different sources.

The poverty, GDP and employment data were sourced from various National

Bureau of Statistics of Nigeria (NBS) reports. The wages and public

expenditure (investment in agriculture, transportation and education) data are

sourced from the Central Bank of Nigeria‟s various statistical bulletins. Data

on investment/GDP ratio and population growth were obtained from World

Penn Tables.

The Model

The estimation models are specified below and the variables are log-

transformed in all the equations in the system. In order to investigate the

effects of public expenditure composition on poverty, we developed a system

of equations and Seemingly Unrelated Regression (SUR) is used for the

estimation.

(1)

(2)

(3)

(4)

Equation 1 states that poverty ( ) is being determined by economic growth

( ); the level of employment ( ); and the level of wages ( ). The

relationship between growth, employment, wages and poverty reduction has

been well acknowledged in various studies. The joint ILO-UNDP program for



„promoting employment for poverty reduction‟ has also discussed this issue.

Empirical studies such as Zepeda et al. (2007), Osmani (2005), Khan (2005)

and Islam (1995) have found that growth have positive impact on and poverty

and conclude that poverty could be reduced by creating job and employment.

This implies that government expenditure can affect poverty by raising the

level of economic growth via increased productive capacity through

increasing the level of education and skills formation, which in turn leads to

employment and higher wages and thus leads to poverty reduction. Equation 2

models the determinants of GDP growth ( ), which is hypothesized to

depend on the investment/GDP ratio ( ), population growth ( ) and

capital expenditure on education ( ), health ( ), agriculture ( ) and

transport and communication ( ), and on infrastructure ( ). Equation 3

represents the employment model ( ), which is a function of GDP growth

( ) and public expenditure composition, while the expression in equation

(4) is the wage determination function, which is assumed to depend on the rate

of GDP growth and the capital expenditure categories.

Justification of variables

Economic growth is measured as the annual rate of change of real gross

domestic product (GDP). The prior expectation between infrastructure and

economic growth is positive. It has been acknowledged in the economic

growth literature that investment in physical and social infrastructure

promotes economic growth. While employment rate is defined as the

proportion of the population that is employed and is measured as the

percentage of the working-age population that is employed. Employment is

crucial to poverty reduction, for growth to benefit the poor, it is necessary to

generate adequate employment to simultaneously absorb the increases in the

labour force and to raise total labour productivity (Islam, 1995). With the

increase in employment rate, income and real wages of labours increase, and

that in turn improves the standard of living and thus contribute to poverty

reduction (Suryahadi et al., 2012). Poverty reduces as employment

opportunities increases, as more unemployed people get jobs. Employment is

expected to be negatively related to poverty due to the significance of the

wage earnings to increase in income. Consistent with this proposition, Hanson

(2009); Block and Webb (2001) report a negative relationship between

employment and poverty. It has also been argued that poverty reduction of

increased employment opportunities leads to economic growth, which further

increases employment opportunities and thus poverty reduction. This shows

that the employment opportunities can lead to poverty reduction through

increases in economic growth.

Wages is a payment made by an employer to an employee for work done or

services rendered. Wages are measured as the annual change in real wages.

Real wage growth is one of the main indicators of the labour market situation.



A wage increase is expected to follow a rise in income so that the income

increase can lead to increase in the standard of living and thus reduces

poverty. In theory, an increase in wage tends to raise income and thus reduces

poverty. The link between real wages and poverty is very strong. In Nigeria,

wage growth plays an important role in poverty reduction as the greater

percentage of the working households have increasingly relied on wages and

work-related income. Loayza and Raddatz (2010) argue that occupations that

are more productive are beneficial to the poor only when accompanied by

higher real wages. The rise in poverty incidence in developing countries is

closely tied to low wages, which make it difficult for households to lift

themselves out of poverty (Alaniz et al., 2011). Ravallion and Datt (2002) and

Fan et al. (2000) argue that a sharp increase in wage appears to have been a

significant explanation for the decline in rural poverty in India. Thus, we

expect wages to be negatively related to poverty in Nigeria.

Investment is the spending of saved money for the purpose of creating future

wealth. In other words, it is referred to as expenditure on capital goods such as

factories, machines, plants, and buildings that are bought by firms for

production purposes. Investment is measured as gross capital formation as a

percentage of GDP. Thus, we expect investment to be positively related to

economic growth. Public capital expenditure is the government spending on

fixed assets and it consists mainly of buildings and infrastructure, examples

building of roads, hospitals, schools, and plant and machinery and so on. This

is sometimes referred to as government investment because it will be used

over many periods. Public expenditure has also been classified into different

types, namely government expenditure on education, health, agriculture,

transport and communication and infrastructure. This is to be consistent with

the Central Bank of Nigeria classification.

Results and Discussions This section consists of a summary of descriptive statistics and the SUR

results of the poverty, growth, employment and wage models. The study used

the capital expenditure composition which would allow us to examine the

disaggregated impacts of the different types of capital expenditure on growth,

employment and poverty reduction.

Descriptive statistics of the data sets

The summary of descriptive statistics is shown in Table 1. An examination of

the descriptive statistics in reveals some important information. As it can be

seen from results, the mean is greater than the media, except for poverty and

GDP. The results indicate that the average wage is 291.448. The disparity in

national wages ranges from 12.201 (minimum value) for some years to 556.66

(maximum value) for other years. The difference in employment level ranges

8.851 (minimum value) to 18.032 (maximum value). The results further



suggest that the data is mostly characterized by positive skewness. The

standard deviation which measures the degree of dispersion of the variables

from their mean shows that the most volatile is wages (269.08). However, the

least volatile variable is population growth (0.002). On the other hand, the

standard deviation of the real GDP growth is lower when compared with

employment and wages. This implies that the GDP data is less volatile.

Table 1 Descriptive statistics of the data sets

Variable Mean Median SD Min Max Skewness

POV 51.19 50.00 19.73 7.2 95.1 -0.07

GDP 0.0467 0.25 0.032 -0.06 0.233 0.59

EMP 147.42 1.328 83.99 12.20 556.66 1.78

WAG 291.44 212.52 269.08 8.85 18.03 2.32

INV 13.07 10.79 7.51 6.18 29.37 1.55

POP 0.03 0.03 0.02 -0.04 0.29 8.44

CEE 10.48 4.38 15.83 0.53 89.38 2.64

CEH 4.410 2.80 4.25 0.16 22.47 1.39

CEA 12.06 10.42 9.47 1.10 45.74 1.13

CET 22.65 5.78 40.12 0.71 220.43 1.61

CEI 28.50 5.33 44.93 0.49 239.22 2.20

Source: Computed from STATA Output Table

The Results of Capital Expenditure, economic growth and Poverty

This section presents the SUR results of the poverty, growth, employment and

wage models. The results of the poverty model in Eqn.1 in Table 2 indicates

that coefficients of GDP, employment and wages carry negative signs and

statistically significant. The GDP and EMP are statistically significant at 1%

significant while wage is statistically significant at 5% level. These indicate

that the variables are inversely related to poverty. In other words, increase in

economic growth, employment level and wages exert significant influence on

poverty reduction. This corroborates the findings of Fan et al. (2000); Ruben

(2001); Lanjouw (2001) and Sen (1996), who reports that economic growth,

non-agricultural employment and real wages contribute to poverty reduction.



Table 2. Poverty reduction and sectoral capital expenditure POV-eqn.1 GDP-

eqn.2

EMP-

eqn.3

WAG-

eqn.4

Economic growth (GDP) -0.767***

(-3.22)

- 0.484***

(5.56)

0. 020

(0.21)

Employment (EMP) -0.216***

(-9.67)

- - -

Wages (WAG) -0.010**

(-1.99)

- - -

Investment (INV) - 0.012***

(4.04)

- -

Population growth (POP) - 0.939***

(16.88)

- -

Education Capital

Expenditure (CEE)

- 0.09***

(4.23)

0.563***

(14.28)

0.609***

(3.66)

Health Capital

Expenditure (CEH)

- 0.001

(1.38)

0.412***

(21.88)

0.073*

(1.77)

Agriculture Capital

Expenditure (CEA)

- -0.071**

(-2.22)

0.072***

(12.43)

0.003

(0.09)

Transport Capital

Expenditure (CAT)

- -0.053***

(-4.53)

0.250***

(12.80)

0.072**

(2.46)

Infrastructure Capital

Expenditure (CEI)

- 0.013***

(4.18)

-0.053***

(-9.99)

0.504

(1.15)

Number of Obs. 222

Number of Eqn. 4

“R-square” 0.34 0.76 0.80 0.73

Breusch-Pagan LM test 46.117

(0.000)

Correlation matrix

Poverty 1.000

GDP growth 0.126*** 1.0000

Employment -0.075** -0.4147*** 1.000

Wages -0.117*** -0.008 -0.021 1.000 Figures in parentheses are t-statistics, except for the Breusch-Pagan LM test; *, ** and***

indicate 10%, 5% and 1% significance levels respectively.

Source: Computed from STATA Output Tables

While, the results of the GDP growth model in Eqn. 2 shows that the

coefficients of investment, population growth, capital expenditure on

education, and infrastructure are statistically significant and carry positive

signs. This implies that increase in investment rate, population, capital

expenditure in education and infrastructure could increase economic growth.

This is consistent with the a priori expectation, investment, capital

expenditure in education and infrastructure are positively correlated with

economic growth. The economic growth literature has shown that increase in

investment rate would lead to high economic growth. Similarly, the

importance of government expenditure in education and infrastructure in



accelerating economic growth has been emphasized in the endogenous growth

theory. Government investment in infrastructure and human capital

development is important for the private sector investment. While, the health

expenditure, though carry positive sign but not statistically significant. Also,

the results show that the coefficients of the capital expenditure in agriculture

and transport are negatively related to GDP which is contrary to the prior

expectation.

The estimated results of the employment model in Eqn.3 indicate that with the

exception of capital expenditure on infrastructure all the variables in the

model have positive signs and statistically significant at 1%. This implies that

economic growth, capital expenditure on education, health, agriculture and

transport communications have a positive impact on the level of employment,

as the theory suggests. The capital expenditure on infrastructure has negative

significant coefficients. The positive interdependence between capital

expenditure on health, agriculture, and transport services and employment rate

makes sense, as the role of investment in the agriculture, transport and health

sectors in improving productivity and thus labour demand is well established

in the literature. The fact that the coefficients of infrastructure variables carry

negative signs does not mean that building schools and investing in training

and development are unimportant for employment generation. Rather, this

may imply that the effect of this class of expenditure on employment rate

depends on numerous factors, including its composition. Studies have shown

that expenditure that is seen as pro-poor tends to benefit the richer quintiles of

the population, with the exception of expenditure on public school

infrastructure (see Wilhelm and Fiestas, 2005; World Bank, 2004).

Finally, the estimated results of the wage model in Eqn. 4, which

hypothesized to depend on GDP growth, education, health, agriculture,

transport and infrastructure expenditure shows that the coefficient of the

capital expenditure in education, health and transport carry positive signs and

statistically significant at 1%. 5% and 10% levels respectively; while

agriculture and infrastructure expenditure coefficients are not significant. This

suggests that increase in education, transport and health sector capital

expenditure exert significant influence on real wage. That is, increase in

capital expenditure in education, health and transport could lead to increase in

real wages.

The results R-squared indicate that the regression line perfectly fits the data.

While the correlation matrix of the residuals suggests that there is a strong

positive correlation between GDP growth and poverty (0.126). The

employment rate and poverty rates are negatively related (-0.074). Likewise,

the correlation between wages and poverty is statistically and negative (-

0.116). Similarly, the correlation between real GDP growth and employment



is statistically significant and negative (-0.414). Also, the test for the

independence of the residual vectors was conducted using the Breusch-Pagan

LM of independence. The test results reject the null hypothesis of

independence of the error terms at the 1 percent level, implying that there is

cross-sectional dependence. This means that the residuals are correlated across

entities. Hence, the SUR estimates are more appropriate than the OLS

estimates, since the SUR estimator takes into account the correlation between

the error terms.

Policy implication and Conclusion

This study examines the impact of infrastructure on economic growth and

poverty reduction in Nigeria. The findings indicate that investment in physical

and social infrastructure has a strong impact on the economic growth while

factors associated with poverty rates were economic growth, employment rate

and wages. The policy implications are that economic growth could be

increased by providing adequate investments in infrastructures such as

education, agriculture and transport and communication. The increase in

economic growth would, in turn, creates employment opportunities, which is

crucial to rapid poverty reduction. Therefore, the study concludes that public

provision of basic infrastructure could stimulate growth and reduce poverty.

The study recommends that there is need to make policy framework that is

geared towards developing the power, agriculture and transport and

communication sectors for rapid growth and poverty reduction.

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