I INTRODUCTION
In most developing countries while economic growth rates are increasing, the growth rates of social-economic deprivations are on the rise. The key drivers of development such as health care, education, job creation and infrastructure continue to deteriorate while countries reports continually show growth in gross domestic product. The growth of health and education sector in the development process of any economy cannot be over-emphasized because only well educated and healthy people produce optimally and contribute to national output. The importance government places on education and health in Nigeria has led to the increase in public expenditure allocation to both education and health sector over the years with the aim that this would in turn generate returns that will further enhance the growth and development of the country. However, a key aspect of achieving this is the efficiency with which inputs, mostly in the form of public spending, are transformed into desired social outcomes (Ebejer and Mandl, 2009).
Government health expenditure as a percentage of GDP in Nigeria was 4.8% in 1995. This increased to 5.6% in 1999 and 7.5% in 2003. It decreased to 5.74% in 2008; increased to 6.08% in 2009 and again reduced to 5.07% in 2010 (World Bank, 2012). Budgetary allocations to formal education system have an inverted pyramid shape in which secondary and tertiary education receive more than four times much of public resources as primary education in Nigeria. In most cases primary schools are starved of financing while Universities received heavy subsidies. Umo (1985) submitted that the implications of government assuming total financing of education system are enormous which may based the amount of education provided in a given year solely on the amount of money government is willing and able to allocate to education, reduce the level of educational services provided any time government declares its inability to meet the financial requirements of the educational sector.
Despite increase expenditure to health and education sector in Nigeria though in a pyramid shape, access to health care services has been severely limited and life expectancy has also been on decline for many years. For example, life expectancy declines from 54 years for women and 53 years for men in 1991 to 48 years for women and 46 years for men in 2009 (World Bank, 2010). Similarly in the education sector, schools at all levels lacked qualified teachers and basic infrastructures. The schools suffer from over-crowding, poor sanitation, poor management, and poor intra-sectoral allocation as well as abandoned capital projects. This most often led to closure of schools and workers strikes with the attendant and composite effects of poor quality of teaching resulting to poor quality of products.
This study examines the extent at which government expenditure as an input to health and education sectors produced optimal outcomes using a data envelopment technique borrowed from the production theory of firm. The rest of the work is organized as follows. In section two we briefly reviewed literatures on government spending on education and health. The trend of public spending on education and health in Nigeria was briefly discussed in section three. This is followed by theoretical framework and methodology in section four. Empirical analyses are presented in section five while summary and conclusions are made in section six.
II. LITERATURE REVIEW
Gupta et.al (2001) observed that budgetary allocations to key sectors such as health and education can enhance equity, growth and development and reduce poverty through its positive effects on human capital formation. Budgetary allocations to public sectors are classified into capital expenditure and recurrent expenditure. Capital expenditure can be defined as payment for non-financial assets used in production process for more than one year while recurrent expenditure is payment for non-repayable transactions within one year. Jafarov and Gunnarsson (2008) submitted that the existence of inefficiency may prevent productivity growth from reflecting technical change and hence retard development despite growth in expenditure. Efficiency is a relationship between ends and means and an efficient situation means that the desired ends is achieved with less means, or the means employed produce more of the ends desired.
Economic or cost efficiency is measured by the value of the ends and the value of the means (Pasour, 1981), thus, cost efficiency is a product of technical and allocative efficiency. Technical efficiency (also called productive efficiency) compares different levels of service produced at a given level of expenditure using a single method to produce a service while allocative efficiency relates to different mix of services or activities to achieve greatest outcomes. (Evans et.al., 2000).
Barro and Sala-i-Martin (1992) classified expenditures as productive and unproductive and assume that productive expenditures have a direct impact on the rate of economic growth and the unproductive expenditures have an indirect impact or no effect. Health expenditure covers government spending on medical products, medical appliances and equipment, outpatient services, hospital services, public health services and Research and Development (R&D) in health while education expenditure on the other hand embraces the various levels of formal education (pre-primary, primary, secondary, post-secondary non-tertiary, tertiary), as well as education not defined by level, subsidiary services as well as R&D in education.
Measuring government efficiency has continued to interest policymakers and researchers as a result of the need to generate speedy socio-economic growth and development (Chu and Hemming, 1991; Chu et. al., 1995 in Gupta, Honjo, and Verhoeven, 1997). This interest received a boost with the initiation of wide-ranging institutional reforms by the government of New Zealand in the late 1980s, aimed at improving the efficiency of the public sector (Scott, 1996 in Gupta, Honjo, and Verhoeven, 1997). The central elements of these reforms tried to separate policy formulation from policy implementation, create competition between government agencies and between private firms, and develop output oriented budgets using a wide array of output indicators. Elements of this approach have also been adopted by many countries, and the theory and practice of result oriented public expenditure management has generated a wealth of information on how to control production processes within the government and enhance their efficiency (Oxley, 1990; and OECD, 1994 in Gerdtham, 1995).
Studies on efficiency of public expenditure on human development have utilized both parametric and non-parametric methods, borrowed from production theory. According to Mukherjee (2006), there are essentially three types of studies that have been undertaken in this regard. First, some studies focus on comparing changes in efficiency associated with reform programmes in the public sector in specific countries. These studies provide some examples of “best practices” at the policy level. Second, government efficiency has been investigated using data on inputs of government spending. In developed countries, these studies have dealt with health sector and social security reform, where the government expenditure is the highest among the social sectors. Third, some empirical research have also been carried out to explain cross-country differences in social indicators used as proxies for government output, after netting out the effects of income levels and distribution, as well as rate of economic growth (Anand and Ravallion, 1993; Aturapane, Glewwe and Isenman 1994; Karras, 1996; Bidani and Ravallion, 1997; Tanzi and Schuknecht, 1997 in Mukherjee, 2006).
Harbison and Hanushek (1992) gave an overview of 96 studies of education production functions in developing countries, and 187 studies of education production functions in the United States, and investigate the relationship between education inputs and outputs. These specified a functional form of the production function, and use the data from different schools in a region to estimate the coefficients for a regression of the production function. The output of the education production process is measured by test scores, and input used is gauged by indicators such as the pupil-teacher ratio, teacher education, teacher experience, and the availability of facilities. These studies show that inputs have positive significant impact on education output, and the effect of expenditure per pupil is significant in half of the studies while the pupil-teacher ratio and teacher salary have no discernable impact on education output.
Inefficiency in government spending has been assessed with the help of regression analysis, focusing on inputs. For example, a study of OECD member countries covering 20 years (Gerdtham et al., 1995) analyzed the efficiency of health care systems. The study shows that public-reimbursement health systems, which combine private provision with public financing, are associated with lower public health expenditures and higher efficiency than publicly managed and financed health care systems. Tanzi and Schuknect (1997) assessed the incremental impact of public spending on social and economic indicators (for example, real growth and the mortality rate) on industrial countries. From a comparison of social indicators in countries with varying income levels, they concluded that higher public spending does not significantly improve social welfare. Afonso and St. Aubyn, (2006) also estimate a semi-parametric model of health production process using a two-stage approach for OECD countries applying both Data Envelopment Analysis (DEA) and Tobit procedure to evaluate efficiency in health services across countries by assessing outputs (life expectancy, infant survival rate, potential years of life not lost) against inputs directly used in the health system (doctors, nurses, beds) and environmental variables (wealth and country education level, smoking habits and obesity). In methodological terms, they employed a two-stage semi-parametric procedure. Firstly, efficiency scores were estimated by solving a standard DEA problem with countries as decision making units (DMU). Secondly, these scores were explained in a regression with the environmental variables as independent variables. Results from the first-stage shows that inefficiencies may be quite high on average and as a conservative estimate, countries could increase their results by 40 per cent using the same resources. Countries like Hungary, the Slovak Republic and Poland displayed significant room for improvement. The second stage procedures shows that GDP per head, educational attainment, tobacco consumption, and obesity are highly and significantly correlated to output scores – a wealthier and more cultivated environment are important conditions for a better health performance while a more obese population and prevalence of smoking habits worsen health performance.
Ebejer and Ulrike (2009) also measured the efficiency of public spending in Malta by applying two alternative non-parametric techniques: the Full Disposal Hull (FDH) and the Data Envelopment Analysis (DEA). Using a cross-country analysis of EU Member States, they estimated the efficiency scores of three output indicators each for expenditure on education and health. The findings show that whereas public expenditure in Malta appears relatively efficient at the primary and secondary levels of schooling, it is less so at the tertiary level. These results seem to be confirmed when efficiency was assessed from the output side. Concerning health, their results showed that even in the context of poor outcomes for the remaining member states, the efficiency of public healthcare expenditure in Malta is weak. Their findings suggest that there is scope for rationalizing tertiary education and healthcare spending without compromising outcomes and concluded that it is crucial to identify the institutional and structural factors that prevented Malta from achieving higher public spending efficiency. Jafarov and Gunnarsson (2008) also assessed the relative efficiency of government spending on health care and education in Croatia using Data Envelopment Analysis. The analysis finds evidence of significant inefficiencies in Croatia’s spending on health care and education related to inadequate cost recovery, weaknesses in the financing mechanisms and institutional arrangements, weak competition in the provision of these services, and weaknesses in targeting public subsidies on health care and education.
Studies on government expenditures on health and education in developing countries also revealed some interesting situations. For example, Omotor (2004) examined the profile of educational expenditure in Nigeria in 1977–1998. An education expenditure model was constructed and tested using the ordinary least squares (OLS) technique. It was discovered that federal government revenue is the singular significant determinant of educational expenditure; hence the author suggested that this may create inefficiency without other sources of financing. Gupta, Honjo and Verhoeven (1997) assessed the efficiency of government expenditure on education and health in 38 countries in Africa between 1984 and 1995, both in relation to each other and compared with countries in Asia and the Western Hemisphere. Their results showed that there was a wide variation in the way government spending in African countries impacted on measurable output indicators. For instance, in comparison with other countries in Africa and Asia, and the Western Hemisphere, health and education spending in Gambia, Guinea, Ethiopia, and Lesotho was associated with relatively high educational attainment and health output. The results further indicated that, on the average, countries in Africa are less efficient in the provision of health and education services than countries in Asia and the West Hemisphere, and suggests that improvements in educational attainment and health output in African countries require more than just higher budgetary allocations to translate expenditure growth to socio-economic development.
Literatures on efficiency of public expenditure in the social sector were critically reviewed by Ravallion (2005). He raises the question of whether FDH or DEA techniques borrowed from production theory of the firm are suited for application to the social sector. His major criticism is focused on the lack of theoretical foundation for the empirical exercises, and the incomplete accounting of interdependencies between various types of government spending that are related to improving social sector outcomes. He therefore submitted that the study on efficiency analysis need to consider the appropriate sectoral allocation of total government expenditure taking into account the complementarities between the outcomes and efficiency within a particular type of expenditure to account for the complementarities in inputs. He also suggested that the error term in regression analyses are likely to be highly correlated with both inputs and outputs, and proposes the use of lagged values as instruments and employing government expenditure alone in the analysis or inputs like infrastructural facilities, employment in the sector among others to alleviate this problem. However, Thanassoulis (1993) in a comparison of regression analysis and data envelopment analysis as two alternative methods for assessing the comparative performance of homogeneous units focusing on the estimates of relative efficiency, marginal input-output values and target input-output levels that the two methods offer, suggested that in general, data envelopment analysis outperforms regression analysis on accuracy of estimates but regression analysis offers greater stability of accuracy.
III. TRENDS OF GOVERNMENT EXPENDITURES ON EDUCATION AND HEALTH IN NIGERIA.
The trend of government budgetary allocations to education and health sectors in Nigeria is shown in Table 1.1. The table shows the percentage of the government expenditure allocated to the sectors from 1981 to 2007. The total percentage allocation to the education sector for the period ranges from 2.20 per cent to 8.40 per cent of the total government expenditure. During this period, none of the allocations of the year met the 25 per cent budgetary allocation recommended by UNESCO. The few years with budgetary allocation above 5 per cent coincided with deliberate Government Policy of Qualitative Education (1980 to1982) and the Universal Basic Education free programme of the Government. Government budgetary allocation to the health sector for the period under review also ranges from 1.05 per cent to 5.79 per cent. The sector’s allocations that were above 4 per cent were between 1999 and 2004. This was the period when Government placed emphasis on primary health care delivery and the development of the tertiary health care institutions like the Teaching Hospitals and Federal Medical Centers (Abdullahi, 2008).
Table 1.1: Percentage of Total Government Expenditure on
Education and Health Sectors in 1981-2007. (NB)
|
Years |
Total Government Expenditure |
Education Expenditure as o/o of Total Govt. Expenditure |
Health Expenditure as o/o of Total Govt. Expenditure |
|
|
1981 |
6,564.2 |
6.71 |
1.95 |
|
|
1983 |
6,807.3 |
5.09 |
1.99 |
|
|
1985 |
6,516.4 |
2.77 |
3.93 |
|
|
1987 |
4,759.4 |
2.92 |
1.46 |
|
|
1989 |
9,297.10 |
2.38 |
1.35 |
|
|
1991 |
13,085.4 |
2.20 |
1.05 |
|
|
1993 |
18,600.0 |
8.40 |
1.89 |
|
|
1995 |
44,559.0 |
7.42 |
2.87 |
|
|
1997 |
115,690.0 |
3.29 |
1.92 |
|
|
1999 |
136,984.0 |
6.21 |
5.39 |
|
|
2001 |
438,696.5 |
4.52 |
4.58 |
|
|
2003 |
241,688.6 |
6.07 |
2.66 |
|
|
2005 |
706,884.2 |
3.88 |
3.06 |
|
|
2007 |
883,830.9 |
5.46 |
5.79 |
|
Central Bank of Nigeria Statistical Bulletin (2007)
IV. METHODOLOGY
This study is hinged on the production theory of firm because efficiency has its foundation in the production theory of the firm (Mukherjee, 2006). Studies on efficiency of public expenditure on human development have utilized both parametric and non-parametric methods borrowed from production theory
Technical efficiency can be input-oriented measure or output-oriented measure. The input-oriented measure address the question: “by how much can input quantities be proportionally reduced without changing the output quantities produced?” The output oriented measure alternatively ask the question: “by how much can output quantities be proportionally expanded without altering the input quantities used?”
Data Envelopment Analysis is a non-parametric method often used for frontier efficiency analysis because of its simplicity and wide applications especially when data points are few. This method was originally developed and applied to firms that convert inputs into outputs. The DEA as originated from Farrell (1957) seminal work and popularized by Charnes, Cooper and Rhodes (1978), assumes the existence of a convex production frontier. The production frontier is constructed using linear programming methods. Coelli, Rao and Battese (1998) described several applications of this method. The approach uses DMU that may include non-profit or public organizations, such as hospitals, schools or local authorities or governments. In this study, government is regarded as a DMU or as producers combining resources to provide an array of goods and services. Combinations involving higher output for a given input or the same output for less input are viewed to be superior since they are more efficient. The simple neoclassical production function in equation (1) below specifies a relationship between inputs and outputs, where qi is producible outputs and xi is input factors, i = 1,----,n and q = 1-----,n,
Inputs adopted are public expenditure on education and health while primary school and secondary school enrollment, infant mortality and life expectancy were the outputs.
Deriving an envelopment form of the DEA model using Duality Linear Programming approach as in Coelli et al. (2005), gives the minimization problem as:
Min ø,λ Ø,
Subject to -qi + Qλ ≥ 0 ,
Øxi – Xλ ≥ 0 , ………………………………………………(2)
λ ≥ 0 ,
Where Ø is a scalar and λ is a I × 1 vector of constants. The value of Ø obtained is the efficiency score for the i-th government. It satisfies; Ø ≤ 1, with a value of 1 indicating a point on the frontier and hence a technically efficient government (Farrel, 1957, Coelli et al., 2005)
The production technology associated with our Linear Programming (LP) specification in equation (2) can be defined as H ={ (x, q) :q ≤ Qλ, x ≥ Xλ } . Fare et al. (1994), show that this kind of technology defines a production set that is closed and convex, and exhibits constant return to scale and strong disposability. Therefore, the Variable Return to Scale (VRS) LP model that corresponds to production technologies and have less restrictive properties in which the convexity constraint: I1? λ = 1 is added to equation (2) to form:
Min ø,λ Ø,
Subject to -qi + Qλ ≥ 0,
Øxi – Xλ ≥ 0, …………………………………………………. (3)
I1? λ = 1, (where I1 is an I × 1 vector of one’s)
λ ≥ 0 ,
This approach forms a convex hull of intersecting facet that envelope the data points more tightly than the CRS conical hull and thus provides technical efficiency scores that are greater than or equal to those obtainable using the CRS model. The general principle of the DEA technique of analysis applied in the study is that years which achieve the same or better outcomes with lower levels of spending than other years in the sample are the most efficient and determine the best-practice frontier. The relative spending efficiency of other years can be measured by how far away they are from the best-practice frontier which should be equal to one and when less than one indicate inefficiency.
V. EMPIRICAL ANALYSIS
Table 1.2 displays DEA results on technical efficiency (TE) of government spending in delivery of education services. The results showed that government spending on education in Nigeria was efficiently employed in the years 1988, 1991, 1992, 1995, 1997, 2001 and 2003, 2004 and 2005. This implies that the fund allocated to education was utilized efficiently both at the primary and secondary schools level. In the periods, 1989, 1990, 1993, 1994, 1996 and 2002, the technical efficiencies (TEs) scores attained were above the average TE scores over the period. The TEs scores below the mean TE score were obtained in periods, 1998, 1999, 2000, 2006 and 2007. The least TEs score were obtained in 2006 and 2007. Overall, the number of years which government spending on education was inefficient was more than the number of years the funds were efficiently or optimally used. The mean TE score over the period was 0.986, which means that the technical inefficiency or x-inefficiency over the period was 0.014. With the deviation of efficiency score from one, it is suffice to state that government spending on education in Nigeria to raise enrollment level of pupils and students was inefficient in 1988-2007. This finding is consistent with the founding of Gupta et al. (1997) for African countries and Jafarov and Gunnarsson (2008) for Croatia.
Table 1.2: DEA RESULTS FOR EDUCATION EFFICIENCY IN NIGERIA (1988-2007)
|
YEARS |
Output Orientation: 1 input (Federal Government Expenditure on Education) and 2 outputs (secondary and primary school enrollment) |
||
|
VRS TE |
RANK |
Efficiency loss or inefficiency |
|
|
1988 |
1.000 |
1 |
- |
|
1989 |
0.989 |
13 |
0.011 |
|
1990 |
0.990 |
12 |
0.01 |
|
1991 |
1.000 |
1 |
- |
|
1992 |
1.000 |
1 |
- |
|
1993 |
0.992 |
11 |
0.008 |
|
1994 |
0.989 |
13 |
0.011 |
|
1995 |
1.000 |
1 |
- |
|
1996 |
0.994 |
10 |
0.006 |
|
1997 |
1.000 |
1 |
- |
|
1998 |
0.983 |
16 |
0.017 |
|
1999 |
0.978 |
17 |
0.022 |
|
2000 |
0.951 |
18 |
0.049 |
|
2001 |
1.000 |
1 |
- |
|
2002 |
0.987 |
15 |
0.013 |
|
2003 |
1.000 |
1 |
- |
|
2004 |
1.000 |
1 |
- |
|
2005 |
1.000 |
1 |
- |
|
2006 |
0.938 |
19 |
0.062 |
|
2007 |
0.938 |
19 |
0.062 |
|
Mean |
0.986 |
|
|
Note: VRSTE = Variable Returns to Scale Technical Efficiency
Source: Authors’ Computation
Table 1.3 shows DEA results on TE scores of government spending on health services delivery. The results showed that funds expended by government on health were efficiently utilized for improvement in life expectancy and infant mortality rate in the periods 1988-1991, and 2007. The TEs scores for the periods 1996-2005 were below the average TE score of 0.970. The periods 1992-1995 and 2006 recorded TEs scores that were above the average TE score. The least TE score was obtained in 2002. In all, the number of years in which government spending on health was inefficient was more than the number years the funds were efficiently or optimally used.
Comparatively, inefficiency was higher in the health sector than the education sector. While the health sector recorded 0.03 deviations from average efficiency score, the latter had 0.014. Since the efficiency score is less than one, it can be concluded that government spending on health was inefficiently utilized in increasing life expectancy and reducing infant mortality in Nigeria. This result is also consistent with the findings of Gupta et al. (1997) for African countries and Jafarov and Gunnarsson (2008) for Croatia.
Table 1.3: DEA RESULTS FOR HEALTH EFFICIENCY IN NIGERIA (1988-2007)
|
YEARS |
Output Orientation: 1 input (Federal Government expenditure on Health) and 2 outputs (infant mortality and life expectancy) |
||
|
VRS TE |
RANK |
Efficiency loss or inefficiency |
|
|
1988 |
1.000 |
1 |
- |
|
1989 |
1.000 |
1 |
- |
|
1990 |
1.000 |
1 |
- |
|
1991 |
1.000 |
1 |
- |
|
1992 |
0.996 |
6 |
0.004 |
|
1993 |
0.989 |
8 |
0.011 |
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