Education, Labour Productivity And Income Inequality In Nigeria

EDUCATION, LABOUR PRODUCTIVITY AND INCOME INEQUALITY IN NIGERIA

Sharimakin, A.

Department of Economics, Adeyemi College of Education, Ondo, Nigeria

and

Oseni Mohammed

School of Basic Studies, National Institute of Construction Technology, Uromi, Edo State, Nigeria

ABSTRACT: This study examines the role of education and labour productivity on income inequality in Nigeria by considering both educational attainment and productivity growth over a period of time. A dynamic structure is devised for the analysis using data for the period 1981 to 2013. The cointegration and error correction methodology is adopted in the empirical analysis. It is shown that productivity has a stronger impact on inequality reduction than education. This implies that any policy that promotes education without the productive capacity of labour would not lead to reduction in inequality. It also suggests that policies of reducing income inequality in Nigeria should invariably incorporate productivity growth measures for such policies to be sustainable.

KEY WORDS: Education, workers’ productivity, income inequality, income distribution, Nigeria

JEL CLASSIFICATION: D3 E21 E24 O15.

1. INTRODUCTION

Rising income inequality is a growing concern for policymakers in many economies. These concerns have recently been heightened by high unemployment in many advanced economies in the aftermath of the financial crisis. Many policymakers view a more equal income distribution as a desirable goal, although the underlying motivations may differ. Lower income inequality is often viewed as important for achieving greater equality of opportunities to access economic, social, and political resources. Others view it as intrinsically desirable because the existing income inequality is perceived to be the outcome of unfair access to resources and thus detrimental to social cohesion. Generally known high levels of income inequality have historically persisted in Sub-Saharan Africa, and this unfortunate situation has changed very little over the past decades. There is no doubt that income inequality is a deeply rooted and multifaceted problem, with both moral and economic aspects, which is why the topic spurs a continuous heated debate.

In Nigeria, households suffer from vast inequality of incomes, assets and control over public resources and essential services as well as insecurity (World Bank, 2000). The distributional consequences of economic growth are one of the main policy issues begging for attention from the government. Inequality in income distribution has been a subject of controversy in the literature over the years. Policies seeking steady economic growth may not be enough without giving attention to means of generating such growth processes and the factors easing income inequality and eliminating barriers (Iwayemi, Afeikhena, & Adeboyejo, 2000).

One of such policies may be the improvement in the education system. Educational attainment was one of the strongest factors that led to rapid growth among the Asian tigers in the 1970s (Krugman, 1994) and if this is looked into for the Nigerian case, the issue of income inequality may be addressed. Moreover, productivity is viewed as the instrument for continuous progress, and of constant improvement of activities. It is often seen as output per unit of input. Hence, higher productivity connotes achieving the same volume of output with less factor inputs or more volume of output with the same amount of factor inputs. Thus, increased productivity could result from the reduction in the use of resources, reduction in cost, use of better methods or improvement in factor capabilities, particularly labour (Obadan & Odusola, 2000).

Investigating the sub-growth factors that exacerbate and tend to ensure persistence of income inequality is germane since it is important for policymakers to understand the forces behind distribution of income in order to tackle the problem in the most efficient way. Moreover, the initial response of the economy to income inequality is also a veritable aspect for empirical analysis. Efforts at understanding the causal pathways and transmission mechanisms through which various factors impact inequality over the short and long run are ongoing. In this study, we address this issue by considering the role of education and income redistribution in income inequality reduction in Nigeria.

2. THE LITERATURE

Inequality seems to be a straightforward concept which, as Cowell (1995) states, “obviously” suggests a departure from the simple idea of equality, this is, the fact that two or more quantities are the same size. The concept is generally related to differences in income, consumption or wealth and associated with social welfare. Globalization, free international trade, technology change, transition from communism to capitalism, the erosion of minimum wage are some reasons that have been suggested to explain rising inequality (Steward, 2004). Inequality compares the living standard of each individual in a specific society. Unfortunately, no agreement has been achieved among social scientists about what exactly the standard of living of an individual means and how to measure it. The controversies arise not only from the different ethical points of view of those who want to measure the extent of inequality, but also from the difficulties in capturing accurately the person’s wellbeing. It seems quite improbable to find out a single index able to provide a full description of living standard.

The literature on inequality and poverty has often used income, consumption, and wealth as proxies for living standards, but none of these three concepts takes into account health, freedom or achievement. They do not measure happiness unless we assume that happiness is directly equivalent to level of income or consumption. Furthermore, what people regard as happiness is influenced by culture and personal preferences, and this varies from individual to individual. These proxies do not measure the ‘worth” of an individual. Income, consumption and wealth tell us about the command over resources potential in the case of income and wealth, and actual in the case of consumption, but not about welfare, (Goodman, Johnson & Webb, 1997). Furthermore, Cowell (1995) discuss that none of these concept cover completely the command over resources for all goods and services in society. They exclude “social wage” elements such as the benefits received from enjoying items such as public parks, public libraries, and the police force, whose distribution may only be conjectured.

According to Lipton and Ravallion (1995), measures based on person’s consumption of goods and services are intrinsically limited. They may reveal nothing about the disutility of work, the length or health of the life over which consumption is expected, risk and variability, etc. “Income is a useful indicator if we want to identify which people are likely to lack the resources to achieve a social acceptable standard of living”. However, it does not measure accurately their capacity to achieve access (which may be influenced by other factors such as education, information, legal rights, illness, threatened domestic violence or insecurity) (Wratten, 1995). Supplementary social indicators are sometimes used to compensate the weakness of income or consumption based measures in capturing adequately many aspects of wellbeing. Examples of these indicators are life expectancy, infant mortality, nutrition, the proportion of household budget spent on food, literacy, school enrolment rates, access to health clinics or drinking water. Again, the idea is to have a standard scale so that different population groups may be compared (Wratten, 1995). In practice for policy purposes, income, consumption and wealth remain the key measures of inequality (Cesar, 2002).

Until recently, the most widely accepted method of assessing the contribution of policies, programmes and projects to the benefit of the public relied on the calculation of the added-value (i.e. quantification of the change in social utility created by initiatives) obtained from these interventions. Added – value is an important concept in social cost benefit analysis. It stems directly from the work undertaken in the 1950s and 1960s by Simon Kuznets and Paul Samuelson to provide an analytical framework which allowed microeconomic measurements of welfare changes created by individual initiatives to be directly related to macroeconomic measurements of national or regional output. Kuznet and Samuelson’s research provided a sound methodological basis for asserting that a social cost-benefit assessment which could demonstrate a ‘Potential Pareto Improvement’ (i.e. that the present value of aggregate benefits exceeded the present value of aggregate costs) could be translated into a general improvement in the benefit of the public (Gowdy, 2005).

2.1 Determinants of Income Inequality

Different studies on both the transition and developed countries propose many factors that influence income inequality to a smaller or larger degree. However, the causal links between economic growth and income inequality may work through many other factors (Gallo, 2002). All the different factors described in literature as affecting inequality can be systematized into six groups as follows.

Economic growth and the overall development level of a country — this group includes growth in the GDP, technological progress and the structure of the economy, meaning the shares of the agricultural, industrial and service sectors. There are studies (Higgins & Williamson, 1999) that report the inverted U-shaped relationship between the average income and income inequality (Ferreira, 1999): growth from the low development level leads first to an increase in inequality, but then, at a higher development level, to a decrease in inequality. There is evidence that if a large part of the population moves to a higher sector (for example, from agriculture into the industrial sector), inequality will increase, but if the movement stops, income distribution will become more even again (Gustafsson & Johansson, 1997). Macroeconomic factors are inflation and unemployment, the size of government’s expenditure, external debt and foreign reserves, changes in the exchange rate, and other factors. High inflation mainly causes deepening inequality, because it redistributes resources from persons with fixed nominal income — usually from the socially less insured and poorer part of the population. However, by a progressive tax system, inflation can reduce the income share of the more affluent part of the population (Pikkety and Sez, 2003). The influence of unemployment is somewhat clearer: according to Gustafsson and Johansson, research usually shows that unemployment has inequality increasing effects, because high unemployment worsens the situation of those at the bottom of income distribution. The direction of influence on inequality of the exchange rate and other factors related to foreign economy is not clear. The influence of the government’s expenditure depends on its composition, mainly on the share of social transfers in public expenditure. For example, if the external debt increases, then the increase in interest payments will leave less to social transfers and the redistributive effect of public sector expenditures will decrease (Cornia & Kiiski, 2001).

Demographic factors include processes of demographic development, including the age structure of population (share of economically active population), the growth and density of population; urbanisation, level of human capital, including the level of education and health condition of population. For example, inequality tends to be lower in countries with high population density than in those with low population density. In the latter there exists a stronger possibility for land concentration, which leads to a greater inequality through capital income. The level of human capital and especially education is of great importance, too (Eicher & Garcia -Penalosa, 2000). A further rise and equalisation in the educational level will equalise the income distribution and bring about a decline in inequality (Gallo, 2001).

Political factors include privatisation and the share of the private sector, level of taxes and the share of the public sector, openness of a country, especially trade openness and freedom of labour movement; social policy and other decisions of economic policy. Durham (1999) has analysed regime type as a factor influencing inequality. Privatisation in the transition countries causes wealth concentration to a greater or smaller extent, leading to a more uneven income distribution. Earnings inequality in the public sector is typically lower than in the private sector; thus, the bigger the shares of the public sector in economy, the lower the overall inequality (Gustafsson & Johansson, 1997). Besides these, for example, the regional policy that favours urbanisation will cause income distribution between urban and rural population to be more uneven. The increasing trade openness in developing countries can cause a greater need for low-priced labour and hence a decrease in inequality, but the overall relationship between openness to trade and income inequality is not clear (Cornia & Kiiski, 2001). Also, a negative relationship has been found to exist between the extent of social transfers or income redistribution and income inequality (Caminada & Goudswaard, 2001), but apart from the direct influence redistribution can likewise affect work and investment decisions, so it is not clear to what extent and in which direction inequality is influenced by the tax system and social transfers.

Historical, cultural and natural factors, which among others include distribution of land ownership, people’s attitude to inequality, extent of shadow economy, which are all formed in the course of long history. In addition to these, there is one more factor — availability of natural resources. Countries well endowed with natural resources tend to have greater inequality because of capital-based technology and a lower need for unskilled labour (Cornia & Kiiski, 2001). Inequality is certainly higher in those countries, during whose history land, natural resources and wealth have concentrated into the hands of a small group of the population. Finally, social scientists have found a relationship to exist between the cultural characteristic s of a society and its income inequality (Mushinski & Pickering, 2000).

Cross-sectional allocation of national income resources which have to deal with the factors that may explain the distribution of income among various households in a country based on their distinct behavioural patterns to spending, savings and income levels. As shown in Liyang (1992) savings, employee compensations and private consumption expenditure may help to identify these patterns of income distribution and inequality in an economy.

2.2 Income Inequality in Nigeria

Between 1985 and 2004, inequality (as measured by Gini coefficient with ‘1’ standing for ‘perfect inequality’ and ‘0’ for ‘perfect equality’ in Nigeria worsened from 0.43 to 0.49 placing the country among those with the widest gap between their poorest and richest citizens (Human Development Report, Nigeria 2009). For every given mean income, higher inequality implies higher poverty as a smaller share of resources is obtained by those in the lowest deciles of the population (Elbadawi and Milante, 2005). The poverty problem in Nigeria is partly a feature of high inequality which manifests in highly unequal income distribution, differing access to basic infrastructure, education, training and job opportunities.

The National Bureau of Statistics (2012) report indicates that the number of Nigerians living below poverty line rose from 68.7m to 112.5m (63.7% rise in poverty incidence) during the period while the population rose from 139.2m to 158.6m (13.9% rise in population) over the same period. Earlier figures on unemployment in Nigeria corroborated this situation as the number of unemployed members of the labour force continued to grow from 12.3% in 2006 to 23.9% in 2011. However, during the same period, Nigeria economy grew strongly at an average annual growth rate in excess of 6.6%, making the country the 5th fastest growing economy in the World in 2010 at 7.87% real growth rate. The above represents the paradox of growth in the face of poverty and inequality; it conflicts rational economic and social theories as well as historical trends. It highlights vividly the structural disequilibrium in the Nigerian economy. The figure for the Gini coefficient for the states and Geo-political zones in Nigeria indicates that the trend of inequality in the country is getting worse. Rural inequality as depicted by the Gini coefficient increased from 0.4296 in 2004 to 0.447 in 2010 indicating a 4.1% increase in rural income inequality. For Urban inequality the Gini coefficient rose from 0.4239 in 2004 to 0.4334 in 2010 representing a 2.2 % rise in urban inequality. The Table below shows Gini coefficient.

Table 2.1: Income Inequalities at National and State Level for 2004 and 2010

Source: NBS (2012).

3.1 METHODOLOGY

3.1 Model Specification

The model specified in this study follows the theoretical framework laid down in the previous section. It also follows the income distribution models developed in several papers on human capital-inequality nexus (Forbes, 2000; Gallo, 2002; Ostry et al, 2014). Specifically, the model hypothesizes that income inequality is generally explained by education and the rate of productivity of the economy as well as other private and public sector variables. The model is does specified as:

I = f(edu, prod, sav, rd, rgdp, ges)

The expanded form of the model is written as:

It = λ0 + λ1edut + λ2logprodt + λ3savt + λ4rdt + λ5gest + λ6rgdpt + δECMt-1 + ut

Where

I = income inequality (measured using the Gini coefficient);

edu = level of education in the country, measured as the secondary school enrolment

prod = productivity growth (this is measured as the ratio of total output – real GDP and cost of labour input);

rgdp = real gross domestic product (derived from the CBN statistical);

rd = income redistribution (measured as share of private consumption expenditure in total expenditure);

sav = gross private sector savings;

ges = government expenditure on social services

ECM = the error correction mechanism

u = the stochastic error term and t represents time.

Apriori expectation λ1, λ2 λ3 λ4 λ5 > 0. This implies that each of the factors in the model are hypothesized to be capable of reducing income inequality in the country. Note that in the income inequality equation, government expenditure on social services (ges – a proxy for government transfer) is included in order to capture the effect of government insurance on inequality. Apparently, the higher the role of government in transfer of resources, the higher will be the distribution of income which is expected to reduce income inequality. Thus, a negative relationship is expected to exist between the variable and income inequality. Moreover, a lagged productivity growth variable is used in the model since it has been shown that income inequality responds to productivity growth with a lag.

3.2 Data and Method of Analysis

The nature of this study necessitated the use of secondary time series data. The data are be sourced from both International and Nigerian Data Agencies such as the Central Bank of Nigeria (Statistical Bulletin), the National Bureau of Statistics (NBS), and World Bank (World Economic Indicators). In this study, a dynamic framework is devised for the analysis in order to examine the interactive patterns of the relationship among the variables. Hence, the cointegration and error correction mechanism (ECM) is adopted for the empirical analysis of the study. This method would also involve the test of the time series properties of the data using the unit root tests.

4. EMPIRICAL ANALYSIS

Unit Root and Cointegration Tests

Unit root test is the test of stationarity of time series. A time series is stated as non-stationary if mean and variance of the time series are dependent over time (Gujarati, 2004). On the other hand, a time series is stated as stationary if the mean and variance is constant over time. According to Gordon (1995), most economic time series are non-stationary and only achieve stationary at the first difference level or at a higher level.

In the study, the ADF test statistic is used for the unit root test. The results indicate that each of the variables possesses ADF values that are less than the 95 percent critical values for the levels series and greater than the critical value for the differenced series. The implication of this is that the time series are non stationary in their levels but stationary after first differencing. In order words, the variables are time-dependent and word not guarantee a long run relationship unless tested. Thus, we would accept the hypothesis that the variables possess unit roots. Indeed, the variables are integrated of order one (i.e. I[1]).

Table 4.3 Unit Root Test for Variables

Note: * significant at 5 percent

Having established that the series in the analysis are not stationary in their levels, we move on to determine if they are cointegrated. The Engle and Granger two stage method is employed for the test of cointegration and the result of the cointegration tests are summarized in Table 4.3 below. From Table 4.3 using the Engle and Granger cointegration procedure, the ADF value of the ECM in levels is significant at the 5 percent level. This shows that the residuals are stationary in levels. Based on this result, we cannot accept the null hypothesis of no cointegration among the variables. Therefore, long run relationships exist between the particular dependent variable and the selected independent variables. An inter-temporal model can therefore be estimated for the relationships.

Table 4.3: Results of Engle-Granger Two-Stage Cointegration Test

The Dynamic Analysis

The dynamics of the relationship between education and economic income inequality in Nigeria is analysed within a dynamic error correction framework, using the specified model in chapter three. Moreover, we estimate the relationship within the error correction framework which brings out the pattern of short term changes in the inequality measure arising from movements in the explanatory variables. The diagnostic results of the ECM estimates are generally impressive. The R squared indicates that about 78 percent of the short term variations in income inequality was captured in the model. The F-value passes the significance test at the 1 percent level. This indicates that the hypothesis of a significant relationship between income inequality and all the independent variables combined cannot be rejected.

The contribution of the individual predetermined variable to the behavior of the endogenous variables is determined by observing the coefficients of the variables in the model in terms of signs, size and significance. In the inequality result, the coefficients of education, income redistribution, productivity growth and savings each has a negative coefficient, suggesting that these variables have negative impacts on income inequality in Nigeria. The other coefficients in the equation are positive. These results indicate that the coefficients of economic growth and government expenditure do not possess the signs in line with a priori expectations. In terms of significance, only the coefficients of education and government social expenditure fail the significance test at the 5 percent level.

Table 4: ECM Estimates

Specifically, the results from the empirical estimation shows that

Education level in the country has a negative bu weak impact on income inequality. This implies that with more education, income inequality does not seem to reduce significantly in Nigeria.

Productivity growth has a negative significant impact on income inequality in Nigeria. The implication of this is that as productivity of the labour force increases, income inequality reduces. Thus, it is not the level of education in itself that matters for income levels to change, rather it is how productive the individual is.

Savings has a strong impact on income inequality in Nigeria. Apparently, as private sector savings increase, ability to invest also rise giving rise to increases in jobs and wages which would tend to reduce inequality in Nigeria.

Income redistribution as expected has a negative impact on income inequality. When more resources are moved into the private sector, this study shows that the ability to reduce inequality rises.

Government social spending does not have strong impact on income inequality. That implies that government social welfare programs actually do not have strong effect in reducing income inequality.

We had noted earlier that focusing more resources in the hands of the private sector may act to widen inequality the inequality gap in the country since the private sector does not seem to be efficient in the equitable allocation of resources. However, the results from the estimation demonstrate the reverse conditions that private sector concentration of resources may actually provide leverage for income inequality reduction in Nigeria. The savings coefficient also passes the significance test, thus showing that as savings increases inequality is likely to reduce in the country. When it is considered that savings provides the needed background for investment, the relevance of this factor for inequality reduction can be better appreciated.

The coefficient of the error correction term has the expected negative sign and it also passes the 1 percent significance test. This goes to show that any short-term deviation of income inequality from equilibrium in the short-run can be restored in the long run. The low value of the error correction term means that adjustment to equilibrium in the long run is rather slow. Just about 11 percent of long run adjustment to equilibrium is completed during the first year.

Overall, the study demonstrates the capacity of productivity growth to promote income equalization in the Nigerian economy. However, educational attainment was shown not to be the actual factor that drives inequality. The main linkage in this analysis is that since education is a very strong way of improving productivity, education has a rather indirect impact on income inequality in Nigeria.

5. CONCLUSION

This study has examined the role of education on income inequality in Nigeria by considering both educational attainment and productivity growth. It is shown that productivity has a stronger impact on inequality reduction than education. Any policy that promotes education without the productive capacity of labour would not lead to reduction in inequality. It also suggests that policies of reducing income inequality in Nigeria should invariably incorporate productivity growth measures for such policies to be sustainable. For policy directions, tools available in the hands of policy makers to promote productivity can also be used to reduce inequality in income. For instance, increasing savings rate the economy will stimulate productivity growth and also reduce income inequality in Nigeria.

Finally, although this study has provided extensive analysis of the relationship between education and income inequality in Nigeria, the results may not be generalized for more particular instances of sectoral components in the economy. There is wide heterogeneity in sectoral characteristics in Nigeria ranging from size, labour specialization and technology. Therefore, further studies on this relationship patterns are required for individual sectors in Nigeria in order to specify the individual sectoral behaviours in Nigeria.

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Bio-note

Sharimakin, Akinwunmi is currently a Mphil student at the Obafemi Awolowo University, Ile-Ife, Nigeria. His research area is with special focus poverty, income inequality and rural development.

Oseni, Mohammed is currently a PhD student at the Uniiversity of Benin, Benin City, Nigeria. His interests are in human capital development and financial markets.

Irughe, I. Roland is also a PhD student at the Uniiversity of Benin, Benin City, Nigeria. His research areas are in microeconomic aspects of development economics and public sector economics.