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Economic Growth, Unemployment and Poverty in Nigeria:A Macro-econometric Analysis

Joseph Ayoola Omojolaibi* and Phebean Oluyinka Omojolaibi**

Abstract: Nigeria as a nation is endowed with heterogeneous and innumerable resources thatcomprise both human and material. Nonetheless, due to lack of management culture, extravagantspending and adverse policies of various governments of Nigeria, these resources have notbeen optimally exploited; these resources have not been adequately channeled to profitableinvestments to bring about maximum economic benefits. As a result of the aforementioned,Nigeria has been gnawed with high rate of unemployment and poverty. Economic growth,which is supposed to be a panacea to the problems of unemployment and poverty, appears notto be so in the case of Nigeria. Statistics show that economic growth has not always beenaccompanied by decline in unemployment and poverty in Nigeria. It is in this regard that thisstudy finds it worthy to address the following questions using time series data covering theperiod between 1970 and 2010. (a) what is the nature of relationship between poverty,unemployment and growth in Nigeria? (b) what steps should be taken to ensure that growth issuch that brings about decrease in unemployment and poverty in Nigeria? A small open macro-econometric model, based on the standard Keynesian framework, is developed. The model isorganized into three blocks, namely, growth, unemployment and poverty. The model has linkageswithin and across the blocks. The study finds that economic growth is not alleviating povertyand unemployment rate in Nigeria rather it exacerbates it. This implies that, for povertyalleviation and unemployment reduction, economic growth is a necessary but not a sufficientcondition. Hence, the study recommends that the pattern of growth in Nigeria needs to bechanged so that the poor in rural and urban areas can adequately participate in the process.Nigeria needs broad-based and labour intensive growth strategies. Adequate social servicesand infrastructure to reduce the depth and severity of poverty in Nigeria should be provided.Growth strategies should be targeted at the poor, more investment should be made in humancapital. Agriculture should be adequately boosted and adequate emphasis should be placed onmanufacturing and petroleum industries.

JEL Classification: O16, E24, R15

Key words: Economic growth, Unemployment, Poverty, Nigeria.

1. THE PROBLEM

The Nigerian economy naturally endowed with immense wealth, still found a substantial portionof its population still in poverty. During the last three decades, the country earned over US$300

* Department of Economics, Faculty of The Social Sciences, University of Ibadan, Ibadan, Nigeria, E-mail:[email protected]

** Sectoral Executive, Manufacturers Association of Nigeria (MAN), Ikeja, Lagos State, Nigeria, E-mail:[email protected]

IJE : Volume 8 • Number 2 • December 2014, pp. 179-195

180 � Joseph Ayoola Omojolaibi & Phebean Oluyinka Omojolaibi

billion from crude oil alone (Osinubi, 2005). Today, this should have transformed into a hugesocio-economic development of the country. Instead, Nigeria’s basic social indicators nowplace her as one of the 25 poorest countries in the world.

The Nigerian economy has recorded a rising growth in its GDP especially over the lastdecades. But this has not translated into accelerated employment and reduction in povertyamong its citizens. This development has also been the case for most African countries. Theendowment of crude oil can be seen as the major factor fueling the economic growth. It ishowever expected that the oil revenue should spread to the rest of the economy leading to ahigher shared income for the owners of factors of production.

The objective of reducing poverty among the poor economies in the MillenniumDevelopment Goals (MDG) may not be achieved if the impediments to a rising domesticinvestment and employment creation are still evident in the socio-economic environment. Theimpediments to the nation’s socio-economic development can be attributed to the existence ofthe structural constraints embedded in the economy. These structural constraints can be regardedas the poor state of physical infrastructure in the country and also the absence of a correctinstitutional framework (good governance) that could attract direct investment into the country.

Unemployment is another undesirable phenomenon afflicting all underdeveloped regionsof the world. In Nigeria, unemployment is well pronounced. Many graduates cannot find jobs,and many engage in jobs in which their potentials are not fully utilized. Even though theofficial estimates of unemployment in Nigeria are not too robust, and they contradict the generalopinion about the problem, however, they indicate that there have been steady fluctuations inunemployment rate in Nigeria. Unemployment has been identified as one of the major causesof poverty in sub-Saharan Africa (Obadan, 1997). Indeed, unemployment is always expectedto be highly and positively correlated with poverty.

Economic growth, which is one of the major macroeconomic objectives, is regarded ascrucial – indeed, the driving force of conquering unemployment and poverty (Osinubi, 2005).However, although economic growth is necessary for reduction in unemployment and povertyalleviation, it is not sufficient, because growth alone cannot overcome all the crucial factorsthat contribute to unemployment and poverty. The foregoing appears to be the case with Nigeria,economic growth in Nigeria appears not to have provided the expected panacea forunemployment and poverty.

Furthermore, unemployment and poverty have led to tremendous increase in criminalactivities and social vices in Nigeria. Also, unemployment and poverty are potential sources ofpolitical instability in Nigeria for disenchanted, disgruntled and revolutionary elements in thesociety (Anyanwu and Oaikhenan, 1995). Economic growth, which is supposed to be a solutionto the problems of unemployment and poverty, appears not to be so in Nigeria.

This study therefore, finds it worthwhile to address the following questions: (a) what isthe relationship between growth, unemployment and poverty in Nigeria? (b) what efforts shouldbe taken to ensure that economic growth brings about reduction in unemployment and povertyin Nigeria?

The rest of the study is organized as follows; Section 2 evaluates the performance of theNigerian economy within the study period. In Section 3, the review of the relevant literature is

Economic Growth, Unemployment and Poverty in Nigeria � 181

discussed, while Section 4 presents the research methodology and model specification. Thepresentation of major findings and analysis of result are the pre-occupation of section 5. Finally,section 6 concludes the study and provides policy recommendations.

2. EVALUATION OF THE PERFORMANCE OF THE NIGERIAN ECONOMY: A STYLIZEDFACTS

The stylized facts presented in this section focus on evaluating the productive capacity of theNigerian economy between the period 1970 and 2010. It revealed the oil dependency andstructural constraints embedded in the economy. It also shows how the performance of theeconomy has not translated into a significant reduction in poverty. As mention earlier, thegrowth performance of the Nigerian economy over the years has not been pro-poor. Povertyremains a huge challenge despite the rising growth in the country’s gross domestic product.

Given the low productive capacity of the country, the trade account reveals the wealth ofthe Nigerian economy. The country has been experiencing a robust trade surplus over the lastfew decades. Figure 1 shows the significant surpluses that were recorded between 1970 and2010. Despite the huge import component of the domestic consumption, the country’s exports(mainly from crude oil) are still significantly higher than its imports. This reveals the hugeforeign exchange earnings that the government receives from crude oil exportation withoutcorresponding increase in economic growth.

Figure 1: Nigeria’s Trade Account (1970-2010)

Source: Data Obtained form World Bank; World Development Indicators, 2012Notes: REX is Real Export; RIM is Real Import

Oil exportation has been on its increase and this has dictate on the average about 95 percentof total exports over the years. Figure 2 reveals the divergence between the oil exports and thenon-oil exports in Nigeria over the last four decades. The ratio of non-oil exports to totalexports has been on its downward trend with a higher steep since 1970, while the ratio of oilexports to total exports has been on its rising trend over the same period. This is a serious


indication of an economy that is totally resource driven (oil) with a low and declining productivecapacity.

Figure 2: Divergence of Oil Export and Non-Oil Export in Nigeria

Source: Data Obtained form World Bank; World Development Indicators, 2012

Notes: OETE is Oil Export as a share of Total Export; NOETE is Non- Oil Export as a share of Total Export


Notes: OPGDP is Oil Production as a share of Real GDP; TEGDP is Total Export as a share of Real GDP;TIGDP is Total Import as a share of Real GDP

Figure 3: Oil Production, Total Exports, Total Imports as a Share of GDP


Against this background, it is evident that the role played by the oil sector in the Nigerianproduction function cannot be undermined. Total oil production as a share of GDP has been ona rising trend since 1970 as shown in Figure 3, with an average of about 45 per cent recordedbetween 1999 and 2000 and about 30 per cent over the entire period. Total exports (oil andnon-oil) and imports as a share of GDP reveals similar trends with about 30 and 21 per centrecorded on the average respectively.

However, given the comparative advantage that Nigeria has in oil production, it is expectedto translate into a significant improvement in the productive capacity that will eventually reducethe high level of poverty over the long run period.

Figure 4: Trend in Nigeria’s Growth-Poverty Performance


Notes: PI is the poverty Index: GRGDP is the Growth rate of real GDP

Figure 4 reveals the Growth rate of real GDP and poverty performance of Nigeria over theyears. There has been a sustained increase in the trend of both the real GDP and poverty since1970 to 2010 indicating the presence of serious socio-economic constraints impeding a long-term pro-poor growth in the country. It is striking to note that poverty index increases over theyears and reaches its maximum in the year 2010 (about 1.5), however, growth rate of real GDPfluctuated over the period and recorded the highest in 1974 and 1985 with 1.22 and 1.19respectively.

3. REVIEW OF RELATED LITERATURE

3.1. Theoretical Review

The theoretical analysis presented in this section focuses on the literature on growth and pro-poor growth (poverty trap) theories. The last few decades has experienced resurgence in boththe growth theory (development of the endogenous growth models) and the pro-poor growthmodels in the macroeconomic literature.


The framework of neoclassical economics can be viewed as a summation of the variouscontributions of authors to the model of long-run economic growth. Solow (1956) made ahuge contribution to the growth theory in which he has been revered to as the pioneer ofneoclassical growth model (Domar, 1957). The implications of the neoclassical growth modelcan be view on a short and long-run analysis. In the short-run, policy measures like the tax cutswill affect the steady-state level of output but not the long-run growth rate. Instead, growthwill be affected as the economy converges to the new steady-state level of output which isdetermined mainly by the rate of capital accumulation. This is in turn determined by theproportion of output that is not consumed but is used to create more capital (Savings rate) andalso the rate at which the level of capital stock depreciate. This implies that the long-run growthrate will be exogenously determined and the economy can be predicted to converge towards asteady-state growth rate which depends on the rate of technological progress and labour forcegrowth. Therefore, a country will grow faster if it has a higher savings rate.

Modification of the neoclassical growth model can be greatly attributed to the line ofthoughts of Ramsey (1928), Cass (1965), and Koopmans (1965) which are centred on socialplanning problem (not market outcomes) that uses a dynamic optimisation analysis ofhousehold’s savings behaviour which is taken as constant fraction of income by Solow. Theirbasic assumption is that agents in the community are identical and they live forever. Thismeans that they will maximise their utility over their life time.

The new growth theory which is also known as the endogenous growth theory startedgaining its feet firmly in the growth literature in the early 1980s. This came about as a responseto series of criticisms with the assumptions made in the neoclassical theory. They tend todiscard the assumption of constant returns to scale by replacing it with an increasing returns toscale and try to see growth as being generated by variables that are been determined within themodel. So, technology and human capital are seen to be endogenous, unlike the neoclassicalmodel that assumed these to be exogenous. However, their main emphasis about the long-termgrowth is that they do not depend on exogenous factors and most importantly is that the modelgives room for policies that tend to affect savings and investment (King & Rebelo, 1990).

The assumption of increasing returns was a major challenge in the new growth modelssince this is not applicable under a perfectly competitive market because the production factorscannot be paid from the amount produced. But this problem was circumvented by using theincreasing returns that are only external to the firm and this was first seen in Romer (1986),Lucas (1988), and Barro (1990). Increasing returns has been fully specified in Romer (1986)as a major requirement in achieving an endogenous growth while emphasis on human capitalaccumulation as endogenous in growth models was explicit in Lucas (1988). However, thenew growth theory has gained tremendous popularity over the past few decades and theirstrength can be attributed to their ability to solve most of the limitations of neoclassical growthmodels and the inclusion of some socio-economic factors that will propel growth over the longrun.

Against these backgrounds on neoclassical and endogenous growth theories, an acceleratedeconomic growth may not necessarily be sustainable and translate into an accelerated economicdevelopment. Most developing economies are characterized by structural supply (capacity)constraints impeding the effects of any policy interventions targeted towards increasing growth


(Focus, 2007). It is expected that as an economy grows, one would see a sinking effect as animprovement in welfare of its citizenry. Meaning that, the growth of a country should have ahuge positive impact on its level of poverty. There has been a controversy on whether a countryshould focus on achieving growth and thereafter ensure that the pattern of its growth is pro-poor or focus on reducing poverty by ensuring that this will lead to growth. However, povertycan be viewed as a barrier to growth in the sense that a country will not grow if they are poor.This line of thought has opened the door to the existence of poverty trap where poverty andgrowth interact in a vicious circle. Meaning that a high poverty level will lead to low growthand low growth will also lead to high poverty level (World Bank, 2006).

3.2. Empirical Review

Several findings are discernible from the various empirical investigations on the relationshipbetween economic growth, unemployment and poverty. Prominent among these studies are thework of Obadan (1997) and Sagbamah (1997) who observed that growth and employmentmove in the same direction. All things being equal, the higher the growth rate, the higher theemployment rate. A corollary to the foregoing is that growth and unemployment move in oppositedirection. If the growth rate increases, unemployment rate will fall, all things being equal.Output is, among other things, a function of employment. Increase in employment will lead toincrease in output and hence economic growth. On the other hand, reduction in employment(which is unemployment) will lead to decrease in output and hence in economic growth. Theforegoing shows that there is a negative correlation between growth and unemployment.Therefore, to reduce unemployment, growth-boosting policies should be formulated and put inplace. However, it is important to note that for growth to bring about reduction in unemployment;such growth must be associated with labour force participation. According to the classicalschool of thought this brings about increase in the demand for goods and services and suchleads to increase in the demand for labour services which, in turn, leads to increase inemployment and thus decrease in unemployment.

Many empirical evidences show a negative relationship between growth and unemployment.For instance, in the Caribbean, countries that have sustained high growth rates have decreasingunemployment rates; these countries include Antigua and Barbuda, the Bahamas, Barbados,and St. Kitts and Nevis (Baker, 1997). In Nigeria, the high rate of growth between 1988 and1992 was accompanied by decline in the rate of unemployment (Osinubi, 2005). A majorstrategy that can be used to bring about rapid economic growth and reduction in unemploymentis investment in human capital. A World Bank study shows that the most important factor thatbrought about rapid growth and reduction in unemployment rate in East Asian countries wasinvestment in human capital (see Obadan, 1997).

Meier (1989) asserted that whether absolute poverty is measured by low income, low lifeexpectancy or illiteracy, there is a negative correlation between poverty and growth. Meier(1989) stated that there is a great deal of truth in the proposition that there is a strong inverseassociation between economic growth and poverty but this needs to be carefully qualified. Acomparison of different countries shows that the relation between absolute poverty and economicgrowth is far from perfect. This is due to differences in income distribution. Looking at changeswithin particular countries, the connection between growth and poverty reduction over periods


of a decade or two appears inexact. However, there is general agreement that growth in thevery long-term eliminates most absolute poverty (World Bank, 2006).

The connection between economic growth and poverty goes both ways. Health, educationand well-being of the people in industrialized countries are a cause, as well as a result ofnational prosperity. Similarly, people who are unskilled and sick make little contribution to acountry’s economic growth (Meier, 1989).

Economic growth is very crucial in poverty reduction. Growth reduces poverty throughrising employment, increased labour productivity and high real wages. Countries in theCaribbean that have sustained high growth rates and invested in human capital have relativelylow levels of poverty; these countries include Antigua and Barbuda, and St. Kitts and Nevis.But poverty has increased in Caribbean countries that have had low or negative rates of growthfor protracted periods; these countries include Guyana, Haiti, Jamaica, Suriname and Trinidadand Tobago (Baker, 1997). For growth to bring about reduction in poverty, among other things,it has to promote the productive use of the poor’s most abundant asset which is labour. Provisionof employment that goes with living wages for the poor is very important in any povertyalleviation strategy; this is in line with the capitalist entrepreneurial theory of poverty. Jobcreation and generation of adequate income earning opportunities for the poor are made possiblethrough high and sustainable economic growth.

As stated earlier, economic growth that is associated with huge investment in human capitalleads to reduction in poverty. And such investment may be made possible by increase in savings.No wonder, in the classical theory of growth, in the Harrod-Domar growth model and in theMeade’s neoclassical model of growth, savings is positively correlated with growth. Indeed,when savings are adequately channeled to profitable investment it brings about growth.

There is a very strong positive correlation between high levels of unemployment andwidespread poverty. In most cases, those without regular employment or with only scattered part-time employment are among the very poor. Those with regular paid employment in the publicand private sectors are typically among the middle to upper-income class; they are typicallyamong the non-poor. However, it would be wrong to assume that everyone who does not have ajob is necessarily poor or that all those who work full time are among the non-poor. There may besome unemployed urban workers who are “voluntarily” unemployed in the sense that they aresearching for a very specific kind of job, may be because of high expectation based on theirpresumed educational or skill qualifications. They refuse to accept jobs they consider to be inferior,and they able to do this because they have outside sources of finance (e.g. finance from friendsand relatives). Such people are unemployed by definition but they may not be poor. On the otherhand, some people work full-time in terms of hours per day but earn very little income are “fullyemployed” but often they are still very poor (Gunter et al, 2005).

Empirical evidences show that poverty can be reduced through reduction of unemploymentamong the poor. For example, in Nigeria, there was a steady decline in unemployment ratebetween 1987 and 1991 and this was followed by reduction in poverty (Federal Office ofStatistics, 1999; Central Bank of Nigeria, 1998). In Indonesia and Malaysia, reduction inunemployment among the poor brought about reduction in the level of poverty (World Bank,1990). The foregoing supports the assertion that there is a strong positive correlation betweenunemployment and poverty.


4. RESEARCH METHODOLOGY AND MODEL SPECIFICATION

4.1. Research Methodology

Here, macro-econometric model is specified to capture the objectives of the study, and thereafterthe estimation techniques and procedures are articulated. The macro-econometric model consistsof three blocks, namely, the growth equation block, the Unemployment block and the povertyblock. Each block captures specific equations whose formulations are guided by economictheory as presented in the literature as well as the structure of the economy. The model used inthis research work is derived from the endogenous growth theory.

4.2. Model Specification

The macro-econometric model used in this study is estimated in a recursive system consistingof three blocks which are discussed in turn:

(i) The Growth Equation;

(ii) The Unemployment Equation; and

(iii) The Poverty Block;

4.2.1. The Growth Equation

Equation (1) presents growth as a function of poverty index, unemployment rate, money supply,exchange rate, index of manufacturing production and gross investment. Growth is expectedto be inversely related to poverty. Growth is expected to be inversely related to unemploymentrate. Higher rates of unemployment will, all things being equal, bring about lower levels ofgrowth, for economic theory postulates that growth is a positive function of employment. Growthand money supply are expected to be positively related (Ajayi and Ojo, 1979). Increases inmoney supply will, all things being equal; bring about growth through its effect on prices.Also, growth is expected to be positively related to exchange rate. Increase in exchange ratebrings about increase in domestic prices through the multiplier process; this, in turn, bringsabout growth. Growth is also expected to be positively related to manufacturing productionand gross investment (see the Harrod-Domar growth model).

RGDPt = �

0 + �

1POV

t + �

2UNEMP

t + �

3EXR

t + �

4MP

t + �

5MS

t + �

6GI

t + µ

t(1)

Where RGDPt is the real gross domestic product, POV

t is the poverty index, UNEMP

t is

the unemployment rate, EXRt is the exchange rate, MP

t is the index of manufacturing production,

MSt is the money supply, GI

t is the gross investment and µ

t is stochastic disturbance term.

4.2.2. Unemployment Equation

In equation (2) where unemployment rate is a function of poverty, growth, population index ofmanufacturing production and gross investment. Unemployment rate is expected to be positivelyrelated to poverty and inversely related to growth. High level of population growth causesunemployment in Nigeria, whereas, increase in manufacturing production index reducesunemployment. Huge gross investment in human, capital and infrastructure reducesunemployment. For unemployment model to be estimated we therefore specified equation (2)as follows:


0 1 2 3 4 5t t t t t t tUNEMP POV RGDP POP MP GI� � � � � � � � � � � � � � (2)

Where UNEMPt is the unemployment rate, POP

t is the population rate, other variables are

defined earlier and �t is stochastic disturbance term.

4.2.3. Poverty Equation

In equation (3) where poverty level is a function of growth, unemployment rate, inflation rate,agricultural production and petroleum production. Poverty is expected to be inversely relatedto growth. Higher levels of growth will, all things being equal, bring about lower levels ofpoverty. Poverty is expected to be directly related to unemployment rate. Higher rates ofunemployment will, all other things remaining the same lead to higher levels of poverty.Agricultural and petroleum productions are major activities in Nigeria. Increase in agricultureand petroleum productions are expected to bring about reduction in poverty in Nigeria throughemployment creation, income generation, provision of basic consumption needs andinfrastructure. Poverty is expected to be positively related to inflation rate. High rates of inflationmake it impossible for many people to afford basic necessities of life. Indeed, high rates ofinflation bring about high levels of poverty. The impact of growth, unemployment, inflation,agricultural production and petroleum production on poverty is represented in equation (3).

0 1 2 3 4 5t t t t t t tPOV RGDP UNEMP INF AGP PEP� � � � � � � � � � � � � � (3)

Where POVt is the poverty index, INF

t is the inflation rate, AGP

t is the index of agricultural

production, PEPt is the index of petroleum production, other variables are defined earlier and

�t is stochastic disturbance term.

0 1 2 3 4 5, 0 1 2 3 4 5 0 1 2 3 4 5, , , , , , , , , , , , , , , ,� � � � � � � � � � � � � � � � � � are the parameters of the model.

4.3. Estimation Techniques and Procedures

The first task in the estimation procedure is to examine the connection between growth,unemployment and poverty in Nigeria. Most studies that have examined similar relationshipadopted the ordinary least square (OLS) technique, cointegration approach and vectorautoregressive (VAR) to estimate their models. However, these methodologies have been flawedon the ground that they are unable to take care of sample selection and simultaneity biases andis, therefore prone to the problem of weak instrument (Clarida et al., 2000). Thus, this presentstudy however, departs from previous works because it estimated a small macro econometricmodel via a superior and more policy applicable Two Stage Least Squares (2SLS) technique.

Next, the time series properties of the variables were examined. The classical econometrictheory is anchored on the assumption that the observed data come from a stationary process, thatis, a process whose means and variances are constant over time. Any series that is not stationaryis said to be non stationary. The rationale behind stationarity test is the fact that most economicvariables evolve, grow and change over time in both real and nominal terms. This is so becausea substantial part of economic theory generally deals with long-run equilibrium relationshipsgenerated by market forces and behavioural rules. Consequently, running a regression amongsuch economic variables with the false assumption that they are stationary will result in spuriousregression. (Granger and Newbold, 1974; and Chhiber and Wijnbergen, 1988).


It therefore follows that any analysis, forecast and policy recommendation based on suchresults would be meaningless. These problems are avoided by determining the order ofintegration of the variables. To conduct this stationary test, several approaches are employed inapplied econometrics, prominent among these are the Ng-Perron Modified test and DickeyFuller-GLS test. If the variables are non-stationary in levels, they are differenced at least onceto make them stationary. However, differencing a variable may lead to a loss of long-runinformation. Thus, to determine whether a long run relationship exists between the dependentvariable and the explanatory variables, cointegration test is conducted.

In cointegration, it is believed that individual variables might not be stationary but alinear combination of the variables tends to be stationary, implying the existence ofcointegration. To test for cointegration, the study adopted both the Engle-Granger andJohansen maximum-likelihood approach. The existence of cointegration is indicative of along-run relationship between the explained and the explanatory variables. Given that themodel represents a system of simultaneous equations, the study used the Two Stage LeastSquares estimation technique in estimating the model, since the use of ordinary least square(OLS) estimation seems to be inappropriate because it gives biased and inconsistent estimatesof the parameters. To overcome this problem in our model, simultaneous equation estimationtechnique was used.

4.4. Data Requirements and Sources

This study has to do with an economic analysis of growth, unemployment and poverty inNigeria. The study used times series data that spans 1970 to 2010. This period witnessed a lotof policy changes in Nigeria. The study considered, among other things, many conceptualissues relating to poverty, unemployment and growth. The data were obtained from secondarysources, for example, from World Bank Publications, WDI, IMF Publications and CentralBank of Nigeria Publications.

5. EMPIRICAL ANALYSIS AND INTERPRETATION OF RESULTS

This section presents the estimated results of the models specified in the previous section. Itbegins with the preliminary estimates of the model. The results of the unit root tests are reported.That is, the Ng-Perron Modified Unit Root and Dickey Fuller-GLS Unit Root Tests. TheJohansen Maximum Likelihood cointegration test is used to determine the long run relationshipamong the variables. The relationship between growth, unemployment and poverty are examinedwith the aid of Two Stage Least Squares (2SLS) estimation technique. The estimated resultsfor 2SLS model are then presented and analysed.

5.1. Unit Root Tests

In line with recent developments in time series modeling, unit root tests of the time seriesproperties of the data are examined to determine the order of integration of the variables usedin the model. A series is said to be integrated of order d, denoted I(d), if the series becomesstationary or I(0) after being differenced d times. The Dickey Fuller-GLS tests are performed.The statistics of the tests allow one to test formally the null hypothesis that a series is I (1)against the alternative that it is I (0). The results from the tests show that all the variables are


stationary at first difference (that is, they are integrated of order one). The results of thestationarity tests for the variables are presented in Table 1.

Table 1Dickey Fuller-GLS Unit Root Tests Results

Variable t-Statistics 1% 5% Order of Integration

RGDP -3.866463* -3.77000 -3.190000 I(1)UMEMP -6.817927** -3.77000 -3.190000 I(1)POV -6.176292** -3.77000 -3.190000 I(1)EXR -9.154214* -3.77000 -3.190000 I(1)MP -5.436809** -3.77000 -3.190000 I(1)GI -9.100975* -3.77000 -3.190000 I(1)POP -7.637348* -3.77000 -3.190000 I(1)MS -5.465237** -3.77000 -3.190000 I(1)IJF -8.378248** -3.77000 -3.190000 I(1)AGP -7.982548* -3.77000 -3.190000 I(1)PEP -5.981536** -3.77000 -3.190000 I(1)

Notes: All the variables are stationary at first difference. The asymptotic critical values of Dickey Fuller-GLSunit root tests are in their respective levels of significance. ** (*) denotes the rejection of the null hypothesisat 1 %( 5%) significance level.

Source: Computed by the Author using E-views 7.1

5.2. Cointegration Test

Time series variables which are not stationary may have some linear combination of them thatis stationary. In such a case, the variables are said to be cointegrated. This implies that there isa long-run relationship among the non stationary variables. If the tests for stationarity revealthat most of the variables are not stationary, there is need to conduct cointegration test. Thisstudy follows the Johansen and Juselius (1990) to determine the number of cointegrating vectorusing two likelihood ratio test statistics, the trace and maximal eigenvalue test statistics wereutilized to determine the number of cointegrating vectors. However, it is commonlyacknowledged that the statistical properties of the Johansen procedures are generally betterand the cointegrating test is of higher power compared to that of the Engle-Granger (Charemzaand Deadman, 1997). The results of the trace and maximal eigenvalue tests statistics arepresented in Table 2. The results of Johansen maximum likelihood procedures showed that thevariables in each of the stochastic equations are cointegrated.

The procedure followed to determine the number of cointegrating vectors began at the topof the table with the hypothesis that there are no cointegrating vectors, H

O. A rejection of the

hypothesis would lead to testing the alternative hypothesis, which is HA. The testing procedure

continues until the null hypothesis cannot be rejected any longer. Based on the test statistics,the hypothesis of no cointegration, H

O is rejected. The results indicated the existence of more

than one cointegrating vectors in some of the stochastic equations, as shown by the MaximumEigen values and trace statistics, which are statistically significant at the 5% level. The resultfurther reveals that three cointegrating vectors were identified for the real output equation,while two cointegrating vectors were observed for each of the following equations;unemployment and poverty. These results are not surprising as their long-run relationshipsmay well involve more than just the variables tested. The consistency in the test results confirmed


the existence of long-run relationship among the exogenous and endogenous variables in themodel.

Table 2Johansen Maximum Likelihood Cointegration Test Results

Trace Test k=4 Maximum Eigenvalues Test k=4H

OH

A(�

trace) Critical values H

OH

A(� max) Critical values

Equation 5% 1% 5% 1%Real Output r � 0 r � 0 144.49 95.75 104.65 r = 0 r = 1 50.44 40.08 51.80Unemployment r � 0 r � 0 94.05 69.82 98.04 r = 0 r = 1 44.05 33.87 49.71Poverty r � 0 r � 0 49.99 47.86 85.3 r = 0 r = 1 27.06 27.58 28.96

Note: r represents number of cointegrating vectors and k represents the number of lags. *(**) denotes rejectionof the null hypothesis at the 5% (1%) level

Source: Computed by the Author using E-views 7.1

5.3. Macro-econometric Model Estimation and Interpretation of Results

Results for the macro-econometric model estimations are set out in Tables 3-5. Each Tablecontains a column with the baseline 2SLS estimation for each equation using output growth,unemployment and poverty as dependent variables. The results of the behavioural equationscontained in Tables 3 to 5, and the discussion of the results are in the order in which theequations are presented.

5.3.1. Growth Equation

From the result of Table 3, growth is negatively related to poverty index, positively related tounemployment rate, positively related to exchange rate, negatively related to both the index ofmanufacturing production and money supply and finally has a positive relationship with grossinvestment. These imply that increase in poverty level leads to decrease in growth in Nigeria,increase in unemployment rate leads to increase in growth, increase in money supply leads todecrease in growth in Nigeria, increase in exchange rate leads to increase in growth, increasein gross investment leads to increase in growth in Nigeria, and, of course, the positive constantterm shows that there will be growth even when poverty index, unemployment rate, moneysupply, exchange rate, manufacturing production index and gross investment are zero. Thevery low R2 in the equation may be responsible for the insignificance of some of the determinantsof growth in the regression, and most of the parameter estimates are not statistically significantas well. The speed of adjustment to disequilibrium from the growth model is 74.8 per cent.Thus, about 75 per cent of the disequilibrium between the short-run and long-run growth rateis covered up within a year.

5.3.2. Unemployment Equation

The estimation result of the unemployment function in Table 4 reveals that unemployment rateis positively related to growth and population, it is however, negatively related to povertyindex and manufacturing production index. These imply that increase in level of poverty leadsto reduction in unemployment rate in Nigeria. It is possible that poverty will make peopleaccept jobs with very low wages. Increase in growth leads to increase in unemployment rate in


Table 3Growth Equation Regression: Dependent Variable-Real GDP Growth Rate

Variable Coefficient t-statistics

constant 0.012 0.315POV -1.034 -3.127UNEMP 0.513 5. 188EXR 0.150 1.237MP -0.474 -4.142MS -0.912 -3.125GI 1.021 0.674ECM (-1) -0.748 -4.543R2

Adj R2

DW

Source: Author’s Calculations, using E-views 7.1.

Nigeria. This suggests that Nigeria uses capital intensive techniques of production which oftenleads to technological and structural unemployment. Increase in manufacturing productionindex leads to decrease in unemployment rate in Nigeria. This implies that vacancies will existand people who were hitherto unemployed or underemployed will be employed to fill thevacancies. Furthermore, an increase in population leads to a corresponding increase inunemployment. This means that the larger the population, the higher the level of competitionfor the few available jobs. The error correction term shows that 24.5 per cent of the disequilibriumbetween the short-run and long-run unemployment is covered up within a year.

Table 4Unemployment Equation Regression: Dependent Variable-Unemployment Rate


constant 0.019 1.418POV -0.365 -2.136RGDP 0.267 3.244POP 0.482 2.547MP -1.045 -0.296ECM (-1) -0.245 -0.745R2

Adj R2

DW


5.3.3. The Poverty Equation

It is evident in Table 5 that poverty index is negatively related to index of agricultural productioninflation and petroleum production. However, it is positively related Growth and unemploymentrate. This imply that higher growth levels in Nigeria go with decreases in poverty index and asstated earlier, decreases in poverty index means decrease in level of poverty. An increase inagricultural production and petroleum production lead to decrease in poverty level. However,an increase in unemployment rate and inflation rate go with increase in poverty level. Thepositive relationship between poverty index and growth contradicts the a priori expectation,


which suggests that growth in Nigeria does not trickle down to the poor; it also suggests thatthere is high level of income inequality in Nigeria.

Also, the negative relationship between poverty index and agricultural production indexsuggests that as more people go into agriculture in Nigeria, poverty level rises. This may bedue to the fact that agriculture is no more lucrative in Nigeria. More so, the positive relationshipbetween poverty index and unemployment suggests that as more people become unemployedin relative terms, the general level of poverty increases. In Nigeria, nominal wages are frequentlyincreased, this often lead to the laying-off of many workers. On the other hand, there is negativerelationship between poverty index and inflation rate which means that increase in inflationrate has a negative impact on poverty level in Nigeria. This suggests further that increase ininflation serves as impetus for people to work hard and improve their economic conditions,and this resulted into a reduction in their level of poverty. However, the experience of manydeveloping nations shows that some degree of inflation is necessary for growth.

Furthermore, there is a negative relationship between poverty index and petroleumproduction. These imply that increase in petroleum production, impact negatively on povertyin Nigeria. The intuition here is that, an increase in petroleum production lead to reduction ininfrastructure and quality of life of people. The result is therefore, in dissonance with theempirical result of Osinubi, (2005), who found a positive relationship between petroleumproduction index and poverty index in Nigeria. Finally, with the parameter value of -0.435, theerror correction term has the expected signs and shows that poverty rate in Nigeria adjust by43.5 per cent towards equilibrium annually.

Table 5Poverty Equation Regression: Dependent Variable-Poverty Index


constant -0.003 -0.065RGDP 0.091 -0.781UNEMP 1.006 2.921INF -2.362 1.532AGP -0.835 -4.110PEP -0.050 5.236ECM (-1) -0.435 —3.002R2

Adj R2

DW


6. CONCLUSION AND POLICY IMPLICATIONS OF FINDINGS

The study stated clearly that there is very high level of poverty in Nigeria. Majority of Nigerianslive in abject poverty. Unemployment is also a major problem plaguing many Nigerians.Unemployment is highly correlated with poverty. The estimates of the model of the study,however, show a direct relationship between poverty level and unemployment rate which impliesthat increase in unemployment rate increases poverty in Nigeria. This was due to the fact thatwhen people are unemployed in Nigeria, they find it difficult to provide basic needs of life forthemselves like food, clothing, housing, good health, education etc, and inability to provide all


of these needs is termed poverty. The result is therefore, in accordance with the empiricalfindings of Obadan, 1997.

However, in the contrary, some of the workers who become unemployed in Nigeria dependon their non-poor relatives for survival, and in many cases, their non-poor relatives make themto be better-off and bring them out of poverty (Osinubi, 2005). By implication, when peoplebecome very poor, they tend to accept jobs that go with very low wages, this reducesunemployment. Economic growth on the other hand is not alleviating poverty and unemploymentrate in Nigeria rather it exacerbates it. For poverty alleviation and unemployment reduction,economic growth is a necessary but not a sufficient condition. For growth to be an effectivestrategy, it has to be accompanied by a deliberate policy of redistribution. The pattern of growthin Nigeria needs to be changed so that the poor in rural and urban areas can adequately participatein the process.

Nigeria needs broad-based and labour intensive growth strategies. Adequate socialservices and infrastructure to reduce the depth and severity of poverty in Nigeria should beprovided. Growth strategies should be targeted at the poor, more investment should be madein human capital. Agriculture should be adequately boosted and adequate emphasis shouldbe placed on manufacturing and petroleum industries. Moreover, exports should be increasedand imports reduced. Savings should be sufficiently channeled to profitable investment.Finally, adequate and effective monetary policies should be used for rapid and sustainablegrowth.

In sum, setting out appropriate macroeconomic policies to significantly reduce the highlevel of income inequality that is crucial for poverty alleviation in Nigeria are essential. Growthpolicies should be people-centred. Huge investment should be made in human capitaldevelopment. Policies are required to provide more employment opportunities for the poor.There is need for restrictive policies that will bring about moderate inflation. There should bepolicies to adequately increase the real wages and quality of life of agriculturalists. Lastly,there is need to increase investment in the manufacturing and petroleum sectors.

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