Impact of Formal Education on Economic Growth in Nigeria: A Composite Analysis

CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 647 © CINEFORUM Impact of Formal Education on Economic Growth in Nigeria: A Composite Analysis 1Kenneth Onyeanuna Ahamba, 2Hycenth Oguejiofoalu Richard Ogwuru, 3Leona Eucharia Ekechukwu, 4Cletus Offor Onwuka, 5Nwamara Chidiebere Isilebo, 6Chima Nwabugo Durueke, 7Aloysius Orogwo Alo, 8Chioma Rose Chime-Nganya, 9Chukwuemeka Ononuju Nwankiti, 10Michael Eze Odo, 11Alieze Sunday Ekpa, 12Chibuikem Sunday Ohanaka 1,4Department of Economics and Development Studies, Alex Ekwueme Federal University Ndufu-Alike, Ebony State, Nigeria 2Department of Economics, Novena University Ogume, Delta State, Nigeria 3,7,10,12Department of Educational Management and Foundational Studies, Alex Ekwueme Federal University Ndufu-Alike, Ebonyi State, Nigeria 5Department of Educational Foundation, University of Nigeria Nsukka, Enugu State, Nigeria 6Department of Business Management Studies, University of Hull, United Kingdom 8,9Department of Mass Communication, Alex Ekwueme Federal University, Ndufu-Alike, Ebonyi State, Nigeria 11Department of Educational Management, Enugu State University of Science and Technology, Enugu Authors’ emails: 1ahamba.ken[email protected]u.ng or kendr[email protected]m; [email protected]; [email protected]; [email protected]; [email protected]; 6C.DURUEKE2[email protected]c.uk; [email protected]; [email protected]; 9chukwuemeka.[email protected]m; [email protected]; [email protected]; [email protected] Corresponding author’s email: ahamba.kennet[email protected] or kendr[email protected]m Abstract: The value of real gross domestic product has been low, and the actual growth rate of real gross domestic product has fallen below the targeted growth rate on most occasions in Nigeria, despite the huge turnout of graduates from the formal education system. Therefore, this study examines the impact of formal education on economic growth in Nigeria from 1981 to 2020. The specific objectives of the study include the determination of the impact of composite formal education index and changes in the National Policy on Education on real gross domestic product, and the investigation of their direction of causality in Nigeria. The model specification was guided by the endogenous growth theory and the peculiarities of the Nigerian economy. The study employed the autoregressive distributed lag and the Toda-Yamamoto causality methods of data analysis. Short-run result indicates that composite formal education index (CEIND) made insignificant positive impact on real gross domestic product, (RGDP) while National Policy on Education (NPE) made significant positive impact on RGDP. Long-run result shows that the composite formal education index made a significant positive impact on real gross domestic product whereas National Policy on Education made insignificant positive impact on RGDP. Toda-Yamamoto causality test reveals that both CEIND and NPE stimulate real gross domestic CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 648 © CINEFORUM product in Nigeria without a feedback effect. Diagnostic tests for normality, serial correlation, heteroskedasticity, and multicollinearity confirm the justification and validity of the findings. The study recommends vocational, innovative and creative education; increased budgetary allocation to the education sector; extension of the compulsory tuition-free primary education to the secondary education level, and adequate motivation of formal education workers to promote formal education for economic growth in Nigeria. Keywords: Formal education, economic growth, ARDL, Toda-Yamamoto, Nigeria 1. Introduction One of the major concerns of developing countries including Nigeria is the attainment of a stable and satisfactory economic growth. But over the last four decades, the value of Nigeria’s real gross domestic product (RGDP) which is a proxy for economic growth has been low though with rising and falling trends, and the actual growth rate of RGDP has fallen below the country’s targeted growth rate on most occasions (CBN, 2023). This suggests that the Nigerian economy may be growing below its potential, a serious problem that requires urgent policy intervention. Due to the peculiarity of the Nigerian economy, there are many determinants of economic growth in Nigeria, and different researchers have explored some of these determinants in an attempt to address Nigeria’s economic growth problem. For instance, Babatunde and Shuaibu (2011), Akinleye, Olowookere, and Fajuyagbe (2021), Onwiodiokit and Otolorin (2021), Oyegoke and Aras (2021), and Ukangwa and Ikechi (2022) investigated the roles of macroeconomic drivers of money supply, inflation, capital formation, domestic investment, tax revenue, oil revenue, exchange rate, and foreign direct investment in fostering economic growth in Nigeria. Other studies like Yusuf (2014), Emediegwu and Clement (2016), Ayeni and Omobude (2018), Aigbedion, Iyakwari and Gyang (2017), and Ogunleye, Owolabi, Sanyaolu and Lawal (2017), Omojimite (2010), Omodero and Nwangwa (2020), Nenbee and Danielle (2021), among others, have examined the role of formal education in promoting economic growth in Nigeria producing mixed results. But the studies that focused on the formal education-economic growth nexus focused on school enrolment, budget allocation to education and government education expenditure, thus neglecting education attainment, education quality and education policies. The neglect of these vital formal education indicators by these studies could constitute a serious constraint and weaken their policy implications especially the role of formal education in fostering economic growth because the efficacy of macroeconomic drivers of growth is dependent on quality education (Wang and Wong, 2011). Again, the single education indicators used by these studies did not capture the total impact of the entire formal education on RGDP. To fill these knowledge gaps, the present study built a composite formal education index using all the vital education indicators of access to education (proxy by school enrolment rates), education attainment (proxy by school completion rate and mean years of schooling) and CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 649 © CINEFORUM education quality (proxy by adult literacy rate); and also constructed an education policy dummy; and investigated their short-run and long-run impacts on RGDP. Formal education brings about economic growth by first developing the human capital which is indispensable in the production process. Human capital promotes productivity through healthy conditions, knowledge, skills, work experience and motivation (Eigbiremolen and Anaduaka, 2014; Igbal, Awan, and Tayyab, 2018; Keji, 2021). In fact, it is replete in the literature that formal education equips the human capital with the requisite productive knowledge, skills, and technologically innovative capacity which enhance employment opportunities, productivity and personal income generation for economic well-being and the overall improvement in economic growth (Asteriou and Agiomirgianakis, 2001; Lenkei, Mustafa and Vecchi, 2018; Mendy and Widodo, 2018). Therefore, effective and qualitative education is a quest for every developing and developed economy. To deny any individual the opportunity of formal education implies denying not only the individual to succeed, but also denying the country the expected tax revenues for expenditure and improvement in economic growth. The literature suggests that human capital development especially through formal education is justified by its positive impacts on individuals’ lifetime incomes, social rate of return, increase in real aggregate output, economic development and poverty reduction (Barro and Sala-i-Martin, 2004; World Bank, 1995; Schultz, 1999). Primary education could affect economic growth within the endogenous paradigm as it has the potential to boost output (Loening, 2005; Grant, 2017). It enhances employment prospects, especially in small-scale businesses and agriculture, which account for about 85% of employment in Nigeria as well as increases income (GDP), especially for rural farmers (Shettima, 2017). Secondary education equips the human capital with improved skills for employment above primary education skills. This increases the level of productivity and income. Moreover, secondary education imparts better health knowledge and awareness which translates into improved health outcomes thereby promoting productivity and economic growth. Through teaching, practical training, research and development, tertiary education produces professionals and specialists with advanced productive skills, knowledge and expertise which promote economic growth. These key components are strategic to the economic performance of any nation (Oketch, McCowan and Schendel, 2014). Successive Nigerian governments have utilized this knowledge to pursue policies aimed at improving formal education as a tool for promoting RGDP in Nigeria. These policies include: National Minimum Standards and Establishments of Institution Amendments which enables the private sector including individuals, religious bodies, civil society organizations (CSOs), nongovernmental organisations (NGOs) and international development partners (IDPs) to participate in the provision of formal education; the Free Universal Basic Education (UBE) Act of 2004 to rectify the lapses of the Universal Primary Education (UPE) scheme launched in 1976; the establishment of Education Tax Act No. 7 in 1993 which imposed a tax of 2% on all the CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 650 © CINEFORUM assessable profits of all the companies operating in Nigeria to act as intervention fund to all levels of education; the repealing and replacement of the Education Tax Act with the Tertiary Education Trust Fund (TETFund) Act in 2011 to provide supplementary support to all levels of public tertiary institutions in Nigeria; the provision of Early Childhood Care Development and Education Centres (ECCDEC) and the issues of access, equality, equity-inclusiveness, affordability and quality; the launching of the National Economic Empowerment and Development Strategy in 2004 which laid great emphasis on education as a tool for national development (Okoroma, 2000; UNESCO, 2010); the enactment of the National Policy on Education (NPE) in 1977 and its revisions in 1981, 1998, 2004, 2007 and 2013 to accommodate changes in the direction of formal education brought about by technological innovation (Nwangwu, 2007; FRN, 2013; Gabriel, 2018). Despite these policy measures, RGDP is still low. Though there have been remarkable improvements in access to formal education and educational attainment, education funding and quality of formal education are still very low, and the latest economic recession of 2020 which was deeper than that of 2016 is the most worrisome aspect of it. Again, Nigeria could not realise its Vision 20:2020 which aimed at enlisting the country among the top 20 largest economies of the world in the year 2020. Following the background, therefore, the study investigated the impact of formal education on economic growth in Nigeria, and its causal link from 1981 to 2020 using the autoregressive distributed lag (ARDL) model and the Toda-Yamamoto causality test. The specific objectives of the study include the determination of 1. the impact of the composite formal education index and the changes in the National Policy on Education on the RGDP in Nigeria; 2. the direction of causality between the composite formal education index, the changes in the National Policy on Education and the RGDP in Nigeria. The remainder of this paper is organized into Section 2, literature review, Section 3, methodology and data, Section 4, results and discussion, and Section 5, conclusion, policy implications and recommendations. 2. Literature Review Concepts of education, formal education and economic growth Education is “the development of the cognitive, affective and psychomotor domains and abilities of an individual for optimal function and performance in the society” (Ilechukwu, Njoku and Ugwuozor, 2014, p. 45). It is a process of learning. Education aids the acquisition of knowledge, skills, values, beliefs, and habits. “It is the process by which society deliberately transmits its accumulated knowledge, skills, and values from one generation to another” (Ngaka, Openjuru and Mazur, 2012, p. 110). It is a major determinant of employment, earnings and economic growth. Neglecting the economic importance of education would hinder the prosperity of future generations, with severe repercussions for poverty, social exclusion, and the CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 651 © CINEFORUM sustainability of social security systems (Woessman, 2015). There are different types of education depending on the context, methods, curriculum and teaching and learning materials used (Ngaka, Openjuru and Mazur, 2012). These include: formal, non-formal and informal education. Formal education refers to the hierarchically structured and chronologically graded education system that runs from primary (and in some countries from nursery) school to university, and includes specialized programmes for vocational, technical and professional training. Formal education usually leads to recognition and certification. Economic growth is the process whereby a country’s real national and per capita income increases over a period of time, usually a year. Real gross domestic product (RGDP) is one of the best ways of accurately measuring the size of the economy. The RGDP growth rate is a yardstick for gauging the economy’s general health as well as the people’s well-being in the country. “In broad terms, an increase in real GDP is interpreted as a sign that the economy is doing well” (Callen, 2012, p.15). Therefore, RGDP is adopted by the study as a proxy for economic growth. Educational policies in Nigeria “Educational policies are initiatives mostly by governments that determine the direction of an educational system” (Okoroma, 2000, p.190). These policies in conjunction with other educational regulations as issued by the Federal Ministry of Education from time to time guide the operation of education systems in Nigeria. Some of these policies are presented in this subsection. Before 1977, the educational policy operated in Nigeria was that inherited from Britain in 1960 at independence (Okoroma, 2006). The inability of this policy to fulfil national objectives necessitated the need for a better policy. Hence, the first post-independence National Conference on Curriculum was held in November 1969 at the former National Assembly Hall, Lagos. The aim of the conference was to discuss the structure and content of Nigeria’s education; and design new national goals which would guide the future and direction of education in Nigeria (NERDC, 1972; Fafuwa, 1974; Oyeleke & Akinyeye, 2013). Sequel to the 1969 conference, a National Seminar chaired by Chief S. O. Adebo was organised by the National Educational Research and Development Council (NERDC) in 1973. The seminar modified and perfected the 1969 conference resolution and gave birth to the introduction of free Universal Primary Education (UPE) in 1976, and the National Policy on Education (NPE) in 1977 (Akagbou 1985; Bello 1986; Okoroma 2000; Olatunji, 2018). The failure of UPE and the dissatisfaction arising thereof led to renaming and relaunching of the programme as Universal Basic Education (UBE) by Federal Government of Nigeria (FGN) in 1999 (Okoroma, 2006; UBEC, 2017). The UBE programme became effective in April 2004 when the compulsory free UBE Act was enacted (Irigoyen, 2017; Yamma & Izom, 2018). In addition to tuition free primary education, the UBE Act provides for free books, instructional materials, classrooms, furniture and lunch (Olatunji, 2018). The result of UBE programme appears worse than UPE due to corruption and implementation problems. In fact, the quality of public primary education in Nigeria become CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 652 © CINEFORUM more pathetic than the pre-1976 era (Okoroma, 2003). The 1977 NPE, which brought the 135 years of colonial domination and influences on Nigeria’s curriculum to an end, replaced the 75-2-3 (7 years of primary education, 5 years of secondary education, 2 years Higher School Certificate Levels, and 3 years of university education) school system with the 6-3-3-4 (6 years of primary education, 3 years of junior secondary education, 3 years of senior secondary education, and 4 years of university education) system (Ehindero, 1986; Imam, 2012). The 6-33-4 was designed to turn out graduates capable of making use of their hands, their heads and their hearts (i.e., the 3Hs of education) (Uwaifo & Uddin, 2009). The NPE witnessed some revisions in 1981, 1998, 2004, 2007 and 2013 to accommodate changes in the direction of education brought about by technological innovation (Nwangwu, 2007; FRN, 2013; Gabriel, 2018). The 1998 revision introduced the 9-3-4 (9 years of uninterrupted basic education involving 6 years of primary and 3 years of junior secondary education, 3 years of senior secondary and 4 years of tertiary education) system of education. Imam (2012) notes that the 2004 revision which retained the 9-3-4 school system is the 4th; while FRN (2013) observed that the 2007 NPE revised the 2004 edition to accommodate changes driven by the nations commitment to implement international protocols (e.g., Education for All {EFA}, the United Nations Millennium Development Goals {MDGs}) and the National Economic Empowerment and Development Strategy (NEEDS) which started in 2004. Similarly, the 2013 revision of the NPE updated the 2007 edition by accommodating the human capital development strategic goal and other transformation agenda initiated by the FGN in 2011 (FRN, 2013). It also brought the programme of early childhood care education (ECE) under the Basic Education in Section 2 and divided the ECE into two programmes namely Early Childhood Care, Development and Education (ECCDE) and Kindergarten Education (Akinrotimi & Olowe, 2016). Stylized facts about RGDP and formal education in Nigeria Let us look at some stylized facts about RGDP and formal education in Nigeria. It is a wellestablished fact in economic literature that a stable and satisfactory rate of economic growth is one of the four main objectives of macroeconomic policy of every country including Nigeria (Mulhearn & Vane, 1999). But over the years, the value of RGDP of Nigeria has been low, though with rising and falling trends, and the actual growth rate of RGDP has fallen below the targeted growth rate on most occasions as shown in Figure 1. Trends of primary, secondary and tertiary school enrolment ratios and adult literacy rate in Nigeria for selected years between 1981 and 2020 are presented in Figure 2. Figure 2 shows that Nigeria has made remarkable efforts towards improving primary school enrolment over the years when compared with enrolment at secondary and tertiary levels, though with upward and downward trends. Primary, secondary and tertiary enrolment ratios stood at 103.04%, 17.09%, and 2.32% respectively in 1981. Primary school enrolment ratio declined to 89.24% in 1995, CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 653 © CINEFORUM while secondary and tertiary enrolment ratios increased to 26.91% and 5.26 respectively, but still less than primary enrolment by a very wide margin. With the implementation of Universal Basic Education Policy by many SSA countries including Nigeria coupled with the Dakar World Education Forum in 2000 which affirms Education For All (EFA) and the race to actualize MDG 2 by 2015, the primary enrolment ratio in Nigeria accelerated to 85.07% in 2010 which led to remarkable increases in both secondary and tertiary enrolment ratios to 44.19% and 9.56% in the same year. Enrolment ratios at primary, secondary and tertiary levels improved remarkably in 2015 hitting 95.01%, 46.75% and 23.53% respectively. Figure 1: Trends of RGDP and RGDP growth rate in Nigeria (1981-2022) Source: CBN Statistical Bulletin (2023) and World Development Indicators, WDI (2023) With the establishment of the National Commission for Mass Literacy, Adult and Non-formal Education, the National Minimum Standards and Establishments of Institution Amendments Decree, which provides for religious bodies, non-governmental organisations and private individuals to participate in the provision of tertiary education, the adult literacy rate improved to 69.10% in 2020. Despite the struggle to accomplish SDG 4 by 2030, primary and secondary school enrolment ratios declined to 68.3% and 36.7% respectively, in 2019. This may be attributed to the outbreak of the COVID-19 pandemic and the outcome of poor education funding seen in Figure 3 as empirical evidence (Anyanwu & Erhijakpor, 2007) has established a positive and significant relationship between education funding and enrolment rates and vice versa. This 0 10000 20000 30000 40000 50000 60000 70000 80000 -15 -10 -5 0 5 10 15 20 RGDP (N'Billion) RGDP Growth Rate (Annual %) Year RGDP GROWTH RATE (ANNUAL %) RGDP CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 654 © CINEFORUM necessitates the need for the government of Nigeria to improve on education funding. Without this, the dream of actualizing SDG 4 (i.e., to ensure inclusive and equitable quality education and promote lifelong learning opportunities for all by 2030) by the country will evaporate. From the figure, the primary school enrolment ratio is higher than the secondary and the tertiary school enrolment ratios because many poor families in Nigeria cannot afford secondary and tertiary education for their children, especially for the girl child. Similarly, the secondary enrolment ratio is higher than the tertiary enrolment ratio as shown by the wide gaps between the three levels of education in Nigeria. The rising and falling trends in Figure 3 depict inconsistent commitment of the Federal Government of Nigeria to funding education over the years, which is necessary for the production of a quality labour force. In 1981, for example, government recurrent expenditure on education, government capital expenditure on education, and total government expenditure on education as a percentage of RGDP in Nigeria stood at N0.17 billion, N1.30 billion, and 0.007%. Figure 2: Trends of primary, secondary and tertiary school enrolment ratios (% gross) and adult literacy rate in Nigeria. Source: Nigeria Digest of Education Statistics, NDES (2023), National Bureau of Statistics, NBS (2023), UNESCO Institute for Statistics, UIS (2023) and WDI (2023); Note: PGER = primary school gross enrolment ratio; SGER = secondary school gross enrolment ratio; TGER = tertiary school gross enrolment ratio; ALR = adult literacy rate. This narrative remained almost the same after the adoption of the Structural Adjustment Programme (SAP) in 1986, as recurrent and capital expenditure leap-frogged to N0.23 billion 0 20 40 60 80 100 120 1981 1985 1990 1995 2000 2005 2010 2015 2020 Enrolment ratio, both sexes (% gross) & Literacy rate Year PGER SGER TGER ALR CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 655 © CINEFORUM and N0.62 billion respectively. With the institutionalization of the National Economic Empowerment and Development Strategy (NEEDS), which greatly emphasized education as a veritable tool for development and further revision of the NPE in 2004 and 2007 to improve the quantity and quality of education, recurrent and capital expenditures on education improved significantly to N150.78 billion and N150.9 billion respectively, in 2007. With further revision of the NPE in 2013, recurrent expenditure on education witnessed remarkable increases and climaxed at N593.44 billion in 2020 despite the outbreak of the COVID-19 pandemic in December 2019 and its attendant lockdown in 2020. Capital expenditure on education increased to N264.69 in 2019 but dwindled to N194.41 in 2020. The decline may be attributed to the COVID-19 lockdown which hindered many public capital investment projects. Total government education expenditure as a percentage of RGDP continued its traditional marginal rising and falling to 1.11% in 2020. This poor education expenditure made the achievement of the two MDGs on education (i.e., all children to complete primary school by 2015 and to achieve gender equality at all levels of education by 2015) a mirage in Nigeria. Several countries are working hard to achieve the 2030 Sustainable Development Goals (SDGs), which was adopted at the 70th Session of the United Nations General Assembly in 2015 to replace the defunct MDGs. The achievement of inclusive and equitable quality education and promotion of lifelong learning opportunities for all by 2030 (that is, SDG 4) may elude Nigeria if the Nigerian government continues its poor education expenditure pattern. Figure 3: Trends of government education expenditure in Nigeria (1981-2020) 0.00 100.00 200.00 300.00 400.00 500.00 600.00 700.00 0 0.2 0.4 0.6 0.8 1 1.2 1.4 Govt. capital & recurrent edu. expenditures (N'Billion) Govt. education expenditure as % of RGDP Year TGEEXPGDP GREEXP GCEEXP CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 662 © CINEFORUM variables. Table 1 presents the summary of the variables, measurements and the specific sources of data used for each of the variables. Table 1: Summary of the variables, measurement and data sources Variables Measurement Source(s) Real gross domestic product (RGDP) GDP at 2010 constant market prices (N’Billion) CBN Statistical Bulletin (2023) Composite formal education index (CEIND) Primary, secondary and tertiary school enrolment ratios (% gross); primary and secondary school completion rates; primary, secondary and tertiary school mean years of schooling; and adult literacy rate (% of people 15 and above) Researchers’ computation using principal component analysis (PCA) technique and data from National Bureau of Statistics (NBS) (2023), Nigeria Digest of Education Statistics (NDES) (2023), and World Development Indicators (WDI) (2025) Changes in National Policy on Education (NPE) Dummy variable constructed by the researcher. 1 for a year with changes in the National Policy on Education (NPE) and 0 for a year without changes in the NPE Researcher’s construct, 1 for a year with change in the NPE and 0 for a year without change in the NPE Electric power consumption (ETECH) Electric power consumption (kwh per Capita) WDI (2025) Gross fixed capital formation (GFCF) Gross fixed capital formation (N’Billion) CBN Statistical Bulletin (2023) Population growth rate (PGR) Population growth rate (annual %) WDI (2023) Institutional quality (IQG) Quality of government ICRG (2025) Inflation rate (INFR) Inflation, consumer prices (annual %) WDI (2025) Trade openness (TOPEN) Sum of exports and imports divided by GDP in (N’Billion) Researchers’ computation using data from CBN (2023) Exchange rate (EXR) Official exchange rate (LCU per US$, period average) WDI (2025) Source: Researchers’ Compilation (2025) CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 663 © CINEFORUM This study adopted the autoregressive distributed lag (ARDL) estimation technique developed by Pesaran, Shin and Smith (2001) for the analysis of data in order to achieve its objective one. The (ARDL) technique is preferred to the conventional OLS multiple regression analysis, the Engle-Granger static procedures, and the Johansen cointegration analysis because of its superiority. The OLS multiple regression analysis estimates variables that are stationary at levels only, while the Johansen cointegration estimates variables that are stationary at first difference only. But the ARDL approach is suitable for estimating variables that are stationary at levels, at first difference and both levels and first difference. Additionally, it has the capacity to estimate both short-run and long-run coefficients. The justification for the use of the ARDL estimation technique in this study is that it is the best approach for our finite sample size (19812020), and the variables are stationary at both levels and first difference. To investigate the existence of cointegration between RGDP and the independent variables, the ARDL bounds cointegration test incorporating the National Policy on Education was adopted. To capture shortrun and long-run impacts of formal education variables on RGDP and the error correction term, equation (7) is compactly re-specified in ARDL form in equation (8). 0 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 1 10 1 11 1 1 2 3 4 0 0 0 0 2011 2016 t t t t t t t t t t t t k k k j t j j t j j t j j t j j j j j LNRGDP LNRGDP CEIND NPE ETECH LNGFCF PGR IQG INFR EXR BRK BRK LNRGDP CEIND NPE ETECH                 − − − − − − − − − − − − − − − = = = =  = + + + + + + + + + + + +  +  +  +     5 6 7 8 9 0 0 0 0 0 10 11 12 13 0 0 0 0 2011 2016 k k k k k k j t j j t j j t j j t j j t j j j j j j k k k k j t j j t j j t j j t j j j j j LNGFCF PGR IQG INFR TOPEN EXR BRK BRK ECT          − − − − − = = = = = − − − − = = = = +  +  +  +  +  +  +  +  +            (8) where the variables are as defined above, LNRGDPt-1 is the lagged value of RGDP in its natural logarithm, BRK2011 and BRK2016 in PGR and EXR are policy dummies identified by ZivotAndrews breakpoint unit root test in 2011 and 2016 respectively (note that NPE captured most other structural breaks), β0 is the constant whereas β1, β2, …, β11, are the long-run coefficients, 1  , 2  ,..., 13  are the short-run coefficients, ECT is the error correction term, ∆ is difference operator, and k is the optimal lag length. Tracing causal links among variables enhances understanding of policy implications towards empirical findings (Shahbaz et al., 2013). Hence, the study investigates the causal link between education variables and RGDP using the Toda-Yamamoto causality test developed by Toda and Yamamoto (1995, hereafter TY) and utilized in Salahuddin and Gow (2019) and Wolde-Rufael (2009). Taking a cue from Rambaldi and Doran (1996) and Sinha and Sinha CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 664 © CINEFORUM (2007), the TY causality test is valid for series that are integrated or cointegrated and serves also as an augmented Granger causality test and is formulated as follows: Let dmax = maximum order of integration in the VAR system below: The VAR (c + dmax) shall be estimated to use the modified WALD test for linear restrictions on the coefficients of VAR which follows an asymptotic ꭓ2 distribution. Using the Schwarz-Bayesian Information Criteria (SBC). To increase the number of lags in the WALD model up to the maximum cointegration level of variables entered in the model is crucially fundamental in opting for the TY causality testing procedure. The TY approach is an alternative causality testing approach based on the Granger causality equation but augmented with extra lags determined by the potential order of integration of the series causally tested. Adopting the seemingly unrelated regression analytical system, the study investigates the specified VAR four. 1 2 3 4 4 4 1 2 3 0 1 2 3 4 1 0 0 1 2 3 1 2 3 t t t t t t t t t i i i t t t t t t t t LNRGDP LNRGDP LNRGDP LNRGDP LNGDP CEIND CEIND CEIND CEIND D D D D D NPE NPE NPE NPE ETECH ETECH ETECH ETECH − − − − − − = = = − − − − − −                         = + + + +                            4 44 04 4 (9) LNRGDP t CEIND tt NPE itt ETECH tt CEIND NPE ETECH     − − =− −       +        The null hypothesis of causality between CEIND and LNRGDP is Dij = 0; the alternative hypothesis is Dij ≠ 0, where Dij shows the coefficients of the variables. 4. Results and Discussion This section presents the results of data analysis and their discussion. The analysis started with the descriptive statistics to ensure an accurate understanding of the behaviour of the employed dataset and to bolster confidence in the policy inferences arising from the analysis. The summary of the descriptive statistics is presented in Table 2. A careful observation of Table 2 shows that the composite formal education index, National Policy on Education, population growth rate and institutional quality datasets cluster around their sample means as indicated by the proximity of their means and median values, and their small standard deviation values. This suggests the absence of outliers in the series. Conversely, real gross domestic product, electric power consumption, gross fixed capital formation, inflation rate, trade openness, and exchange rate datasets have wide gaps between their mean and median and high standard deviation values. This indicates the presence of outliers in the series. The skewness which measures the degree of asymmetry of the series shows positive skewness for all the series. The kurtosis which measures how much of the values of a distribution can be found in the tails indicates that RGDP, CEIND, ETECH, PGR, TOPEN, and EXR are platykurtic, given their kurtosis values of less than 3. IQG is mesokurtic given its kurtosis value of 3.182499 whereas NPE, GFCF and INFR are leptokurtic, given their kurtosis values of higher than 3. The probability values of the Jarque-Bera statistics indicate that RGDP, CEIND, ETECH, PGR, IQG, TOPEN, and EXR are normally distributed since their p-values are greater than 0.05 CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 665 © CINEFORUM whereas NPE, GFCF and INFR are not normally distributed since their Jarque-Bera p-values are less than 0.05. There are forty observations for each variable. The graphical trend analysis of the individual variables is presented in Figure 4. The correlation matrix which shows the degree of correlation between the variables of the model is shown in Table 3. Table 3 reveals that composite formal education index, changes in National Policy on Education, electric power consumption, gross fixed capital formation, population growth rate, trade openness and exchange rate are positively correlated with RGDP while institutional quality and inflation rate are negatively correlated with RGDP. If the correlation coefficient between any pair of regressors exceeds 0.8, then there is multicollinearity between the two variables (Gujarati and Porter, 2009). The correlation coefficients reveal that none of the independent variables are correlated at above 0.69, which implies the absence of multicollinearity among the variables. Tables 4 and 5 show the ADF, PP and Zivot-Andrews unit root test results of the variables employed by the study. CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 666 © CINEFORUM Table 2: Summary of Descriptive Statistics RGDP CEIND NPE ETECH GFCF PGR IQG INFR TOPEN EXR Mean 37243. 45 0.3408 37 0.1250 00 105.83 25 8598.2 36 2.5807 69 0.2870 52 18.998 95 173.02 37 100.76 01 Median 26182. 87 0.1772 06 0.0000 00 98.964 37 8206.8 30 2.5824 95 0.2777 78 12.707 20 110.04 43 106.46 43 Maximum 72094. 09 1.0000 00 1.0000 00 154.17 23 15789. 67 2.7098 30 0.4444 44 72.835 50 559.83 09 358.81 08 Minimum 16211. 49 0.0000 00 0.0000 00 51.080 55 5668.8 70 2.4887 92 0.1231 48 5.3880 08 0.8675 04 0.6177 08 Std. Dev. 20015. 68 0.3217 75 0.3349 32 27.610 01 1987.9 39 0.0663 33 0.0817 74 16.868 50 170.11 58 100.72 83 Skewness 0.6310 29 0.8336 97 2.2677 87 0.1486 64 1.3299 24 0.1462 62 0.3023 26 1.8234 76 0.5764 87 0.8887 17 Kurtosis 1.7913 12 2.2051 97 6.1428 57 1.8158 87 5.7398 91 1.7728 24 3.1824 99 5.1589 97 2.0027 81 2.9947 74 JarqueBera 5.0895 29 5.6865 24 50.748 30 2.4842 13 24.303 00 2.6525 50 0.6648 50 29.935 87 3.8729 95 5.2654 99 Probabilit y 0.0784 92 0.0582 35 0.0000 00 0.2887 75 0.0000 05 0.2654 64 0.7171 82 0.0000 00 0.1442 08 0.0718 81 Observatio ns 40 40 40 40 40 40 40 40 40 40 Source: Researchers’ computation using Eviews; Note: RGDP = Real gross domestic product; CEIND = Composite formal education index; NPE = Changes in National Policy on Education; ETECH = Electric power consumption, GFCF = Gross fixed capital formation; PGR = Population growth rate; IQG = Institutional quality; INFR = Inflation rate; TOPEN = Trade openness; EXR = Exchange rate Table 3: Correlation matrix CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 667 © CINEFORUM Correla tion RGD P CEIN D NPE ETEC H GFCF PGR IQG INFR TOPE N EXR RGDP 1.000 000 CEIND 0.666 906 1.000 000 NPE 0.006 954 0.005 834 1.000 000 ETEC H 0.648 472 0.602 210 - 0.004 530 1.000 000 GFCF 0.400 035 0.373 659 0.226 472 0.153 077 1.000 000 PGR 0.495 338 0.413 953 0.191 637 0.537 555 0.360 816 1.000 000 IQG - 0.008 153 0.013 409 - 0.266 193 0.083 310 - 0.391 812 - 0.399 735 1.000 000 INFR - 0.346 928 - 0.321 563 - 0.160 224 - 0.223 445 - 0.275 634 - 0.304 554 0.534 780 1.000 000 TOPE N 0.644 676 0.676 571 0.021 640 0.663 500 0.348 976 0.449 285 - 0.008 592 - 0.370 243 1.000 000 EXR 0.622 668 0.613 833 - 0.049 621 0.655 672 0.363 819 0.266 021 - 0.031 290 - 0.341 839 0.697 357 1.000 000 Source: Researchers’ computation using Eviews Figure 4: Graphical trend analysis of the RGDP and its covariates (1981 to 2020) CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 668 © CINEFORUM 0 20,000 40,000 60,000 80,000 1985 1990 1995 2000 2005 2010 2015 2020 RGDP 0.0 0.2 0.4 0.6 0.8 1.0 1985 1990 1995 2000 2005 2010 2015 2020 CEIND 0 1 2 1985 1990 1995 2000 2005 2010 2015 2020 NPE 40 60 80 100 120 140 160 1985 1990 1995 2000 2005 2010 2015 2020 ETECH 4,000 6,000 8,000 10,000 12,000 14,000 16,000 1985 1990 1995 2000 2005 2010 2015 2020 GFCF 2.48 2.52 2.56 2.60 2.64 2.68 2.72 1985 1990 1995 2000 2005 2010 2015 2020 PGR .1 .2 .3 .4 .5 1985 1990 1995 2000 2005 2010 2015 2020 IQG 0 20 40 60 80 1985 1990 1995 2000 2005 2010 2015 2020 INFR 0 100 200 300 400 500 600 1985 1990 1995 2000 2005 2010 2015 2020 TOPEN 0 100 200 300 400 1985 1990 1995 2000 2005 2010 2015 2020 EXR Source: Researcher’s computation using Eviews Table 4: Results of ADF and PP unit root tests of stationarity Variable ADF Test PP Test tstatistic I(0) tstatistic I(1) Result tstatistic I(0) tstatistic I(1) Result LNRGDP -1.041159 -3.783083* I(1) 0.451047 -3.783083* I(1) CEIND -0.320564 -5.930561* I(1) -0.214498 -5.619217* I(1) NPE -7.555210* -3.937994* I(0) -7.574747* -20.70182* I(0) ETECH -2.174719 -7.478639* I(1) -2.152015 -7.604205* I(1) LNGFCF -2.404291 -5.103451* I(1) -3.610453** -5.613544* I(0) PGR -5.125087* -3.058851** I(0) -2.403062 -4.363696* I(1) 1QG -2.509514 -2.771642*** I(1) -2.234615 -4.511792* I(1) INFR 2.958792** -5.752876* I(0) -2.827894** -10.01334* I(0) TOPEN -0.203450 -5.158102* I(1) 0.256962 -4.994068* I(1) EXR 2.168856 -4.120537* I(1) 2.403217 -4.066745* I(1) Source: Researchers’ computation using Eviews; Note: *, **, *** implies rejection of the null hypothesis at 1%, 5%, or 10% level of significance. The test was implemented with intercept and the maximum lag length of 9 was auto-selected on SIC basis for augmented Dickey–Fuller (ADF) test and Newey–West Bandwidth employing the Bartlett–Kernel procedure for Phillips– Perron (PP). CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 669 © CINEFORUM The ADF and PP results in Table 4 reveal that the majority of the variables are stationary at first difference, I(1) while few of the variables are stationary at levels, I(0). The ZivotAndrews unit root test with structural break in Table 5 indicates that the mid-point (break point) years are at 2004, 2013, 1998, 2004, 2001, 2011, 1997, 1995, 2005, and 2016. Table 5: Zivot-Andrews unit root test with unknown single structural break Variable Level form I(0) First difference form I(1) t-Statistic Break Date Lag t-Statistic Break Date Lag Results LNRGD P -2.916131 2004 4 - 4.988638*** 2000 4 I(1) with break CEIND -5.652112* 2013 4 -6.231667* 2012 4 I(0) with break NPE -8.384042* 1998 4 -6.290714* 2008 4 I(0) with break ETECH -4.460320 2004 4 -8.637637* 2002 4 I(1) with break LNGFC F -6.387448* 2001 4 -5.606443* 1994 4 I(0) with break PGR - 4.398053*** 2011 4 -2.446218* 2012 4 I(0) with break IQG -3.745643* 1997 4 -5.715811* 1993 4 I(0) with break INFR -5.281657 1995 4 -5.758397* 2007 4 I(1) with break TOPEN -4.370664 2005 4 -6.573263* 2012 4 I(1) with break EXR -1.715613 2016 4 -5.080660* 2002 4 I(1) with break Source: Researchers’ computation using Eviews; The break locations, i.e. intercept/trend and both are denoted by the midpoint implying rejection of the null hypothesis at 10% (*); 5% (**) and 1% (***) significance levels respectively, based on percentage points of the asymptotic distribution critical values as provided by Zivot and Andrews (1992) Table. These years are significantly policy-oriented as regards formal education as a driver of RGDP in Nigeria. For instance, in 2004, the Nigerian policy makers introduced the National Economic Empowerment and Development Strategy (NEEDS) which is a home-grown poverty reduction strategy that addresses the critical issues of improving education, infrastructure, CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 670 © CINEFORUM expansion of institutional capacity to produce quality manpower, and expansion of total school enrolment to increase the literacy level. The NEEDS also incorporates vocational and entrepreneurial skills acquisition, information communication technology (ICT), and strategies to improve the quality of technical education to meet the technical manpower needs of the economy. The structural break identified in RGDP in 2004 may be an indication that this policy influenced Nigeria’s GDP growth as it aimed at promoting private sector-led growth, reforming public institutions and improving governance, liberalising markets and encouraging investment and diversifying the economy. Other policy initiatives implemented in 2004 include the banking sector consolidation which increased the minimum capital base of commercial banks from 2 billion naira to 25 billion naira leading to mergers and acquisition. This played pivotal role in stabilizing the financial system, increasing availability of credit and boosting investor confidence. The federal government also tightened fiscal discipline in 2004 through better control of public expenditure, savings from oil revenue via Excess Crude Account established in 2004 which helped to stabilize the macroeconomic environment and support economic growth. The government launched the Transformation Agenda (TA) in 2011, a new medium-term strategy with human capital development as one of the prioritised thematic areas which aligned with the defunct Vision 20: 2020 (with a focus on making the Nigerian economy one of the top 20 economies in the world by 2020). This is very significant as transformation of the population by improvement in human capital could catalyse growth. Other key thematic areas of the policy include: (i) economic growth and job creation through diversification of the economy away from crude oil, large investments in agriculture, power, infrastructure, and manufacturing; (ii) governance and public sector reform like strengthening institutions, curbing corruption and enhancing transparency, reforming the civil service for better service delivery; (iii) Infrastructure development through expanding roads, rails, and aviation networks, revamping the power sector via reforms toward privatization and increased capacity for power generation; (iv) security and social inclusion by addressing internal security challenges, reducing poverty and enhancing welfare programmes. Again, the National Policy on Education (NPE) in 2013 spelt out the prospects of early child care development, pre-primary, primary and junior secondary education. The need and prospect of senior secondary education, technical and vocational education and training and mass and nomadic education were also spelt out by the 2013 National Policy on Education. The structural break identified in exchange rate in 2016 is very significant as the Central Bank of Nigeria (CBN) formally adopted a managed floating exchange rate regime to promote efficiency and allow market forces of demand and supply exert greater influence due to persistent dollar scarcity and reserve pressures. This study captured some of these identified structural breaks in two ways (i) by constructing NPE policy dummy that used one for the years of changes in national education policy (1981, 1998, 2004, 2007, and 2013) and zero for years without a change in education policy; (ii) by incorporating another policy dummy (BRK2011) for the identified break in population growth rate as Nigeria’s GDP is heavily influenced by the CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 671 © CINEFORUM quality of its labour force as a labour intensive production technique country; (iii) by incorporating an additional policy dummy (BRK2016) to capture the impact of the identified breakpoint in exchange rate as Nigeria’s economic growth is heavily influenced by trade openness where exchange rate plays pivotal role. The ADF and PP stationarity properties of the variables were validated by the ZivotAndrews break-point unit root results of I(1) and I(0). Since the variables are stationary at the levels or first difference, the study proceeds with the co-integration test to examine the long-run relationship between the variables. Table 6 presents the autoregressive distributed lag bounds test for co-integration, and the result indicates the existence of cointegration as the F-statistic value of 5.247033 is greater than the critical upper bound value of 3.3 at the 5% level of significance. Table 6: ARDL bounds test to cointegration Test statistic Value K F-statistic 5.247033 9 Critical Value Bounds Significant I0 Bound I1 Bound 10% 1.88 2.99 5% 2.14 3.3 2.5% 2.37 3.6 1% 2.65 3.97 Source: Researchers’ computation using Eviews Table 7 presents the ARDL short-run result while Table 8 presents the long-run result under ARDL(2,1,2,2,1,2,1,1,2,2) using the Akaike information criterion (AIC) and maximum dependent lag length of two. Table 7: ARDL short-run estimates (Dependent variable: D(LNRGDP) Variable Coefficient Std. Error t-Statistic Prob. D(LNRGDP(-1) 0.612997 0.212371 -2.886443 0.0148 D(CEIND) 0.123499 0.093195 1.325174 0.2120 D(NPE) 0.048160 0.023500 2.049302 0.0651 D(NPE(-1) 0.070944 0.024953 2.843065 0.0160 D(ETECH) -0.003173 0.000841 -3.771108 0.0031 D(ETECH(-1) -0.000815 0.000664 -1.228191 0.2450 D(LNGFCF) -0.080517 0.077165 -1.043433 0.3191 D(PGR) 2.204140 1.126984 1.955786 0.0764 CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 678 © CINEFORUM -12 -8 -4 0 4 8 12 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 CUSUM 5% Significance -0.4 0.0 0.4 0.8 1.2 1.6 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 CUSUM of Squares 5% Significance Source: Researchers’ computation using Eviews 5. Conclusion, Policy Implications and Recommendations This paper examines the impact of formal education on economic growth in Nigeria by applying the ARDL and Toda-Yamamoto causality test to time series data spanning 1981 to 2020. ADF, PP and Zivot-Andrews unit root tests indicate a mixture of I(0) and I(1). The ARDL bounds test for cointegration indicated the existence of a long-run relationship among the variables. Findings reveal that: composite formal education index made an insignificant positive impact on real gross domestic product (RGDP) in the short-run and a significant positive impact on RGDP in the long-run, changes in National Policy on Education impacted positively and significantly on RGDP in the short-run, and insignificantly positive in long-run. TY causality test established that both composite formal education index and changes in National Policy on Education cause economic growth without a feedback effect. On the overall, the study concludes that the formal education sector drives economic growth in Nigeria based on the ARDL and Toda-Yamamoto causality results. It can also be inferred from the empirical findings that given the performance of the control variables used to capture the peculiarities of the Nigerian economy, the endogenous growth theory which formed the theoretical framework of the study is operative in Nigeria. The following policy recommendations are made based on the empirical findings. First, the budgetary allocation to the education sector should be stepped up from the 7.9% assigned to the education sector by the Federal Government of Nigeria in 2024 to at least the recommended 26% minimum for less developed countries by UNESCO. This is to ensure that enough funds are available for the provision of adequate teaching and learning facilities and a conducive environment for effective teaching and learning in the formal education system in Nigeria. Consequently, the quality of education and educational attainments which are drivers of RGDP CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 679 © CINEFORUM will improve. Secondly, there is a need for the government to set up a committee of stakeholders charged with the responsibility of reviewing and revising the National Policy on Education to recommend practical entrepreneurial, creative, innovative and vocational education in Nigeria. Thirdly, there should be extension of the compulsory tuition-free primary education to secondary education level, enactment of law that makes it a punishable offence for parents that fail to send their children to at least primary and secondary schools, and motivation of staff of formal education through adequate remuneration, improved welfare packages and staff development programmes in order to promote formal education for economic growth in Nigeria. Fourthly, there is need to promote science, technology, engineering, mathematics (STEM) and digital skills development as the digital economy is one of Nigeria’s fastest-growing sectors. 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No. 4, 2025 686 © CINEFORUM Appendix 1: Detailed information on computation of CEIND using PCA Comp8 .0403977 . 0.0050 1.0000 Comp7 .110433 .0700352 0.0138 0.9950 Comp6 .14075 .0303175 0.0176 0.9811 Comp5 .178978 .0382277 0.0224 0.9636 Comp4 .563787 .384809 0.0705 0.9412 Comp3 .759635 .195848 0.0950 0.8707 Comp2 2.66672 1.90708 0.3333 0.7758 Comp1 3.5393 .872584 0.4424 0.4424 Component Eigenvalue Difference Proportion Cumulative Rotation: (unrotated = principal) Rho = 1.0000 Trace = 8 Number of comp. = 8 Principal components/correlation Number of obs = 40 USSCR 0 LSSCR 0 PSCR 0 SSYS 0 ADLR 0 TSGER 0 SSGER 0 PSGER 0 Variable Unexplained USSCR -0.1619 0.5488 0.1078 0.3169 0.2863 0.1294 -0.2013 0.6491 LSSCR -0.0320 0.5641 0.1030 0.4596 -0.0249 -0.0459 0.1666 -0.6546 PSCR 0.2554 0.3444 0.6319 -0.4549 -0.3366 -0.2919 0.0247 0.1039 SSYS -0.3721 -0.3028 0.2886 0.4792 -0.6083 -0.0103 0.2020 0.2144 ADLR 0.4939 -0.0508 0.2065 0.0725 0.0166 0.7418 0.3888 0.0618 TSGER 0.4721 -0.1586 0.1019 0.3407 -0.1803 0.0254 -0.7639 -0.0938 SSGER 0.4546 -0.2028 0.0477 0.3612 0.3287 -0.5824 0.3707 0.1867 PSGER -0.3091 -0.3185 0.6632 0.0011 0.5415 0.0757 -0.1349 -0.2143 Variable Comp1 Comp2 Comp3 Comp4 Comp5 Comp6 Comp7 Comp8 Principal components (eigenvectors) CINEFORUM ISSN: 0009-7039 Vol. 65. No. 4, 2025 687 © CINEFORUM Source: Researchers’ computation using Stata software (version 14). USSCR -.1619 .5488 .1078 .3169 .2863 .1294 -.2013 .6491 LSSCR -.03203 .5641 .103 .4596 -.02486 -.04588 .1666 -.6546 PSCR .2554 .3444 .6319 -.4549 -.3366 -.2919 .02466 .1039 SSYS -.3721 -.3028 .2886 .4792 -.6083 -.01027 .202 .2144 ADLR .4939 -.05082 .2065 .07254 .01663 .7418 .3888 .0618 TSGER .4721 -.1586 .1019 .3407 -.1803 .02538 -.7639 -.09381 SSGER .4546 -.2028 .04775 .3612 .3287 -.5824 .3707 .1867 PSGER -.3091 -.3185 .6632 .001098 .5415 .07575 -.1349 -.2143 Comp1 Comp2 Comp3 Comp4 Comp5 Comp6 Comp7 Comp8 component normalization: sum of squares(column) = 1 Principal component loadings (unrotated)