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Population and Sustainable Economic Growth in Nigeria: An Empirical Analysis

Ebenyi, Gabriel Okechukwu, Nwanosike, Dominic Udochukwu, Agbo, Blessing Onyinye

Population and Sustainable Economic Growth in Nigeria: An Empirical Analysis

By

Ebenyi, Gabriel Okechukwu,
Department of Economics, Renaissance University, Ugbawka, Enugu State benzgabis@gmail.com

Nwanosike, Dominic Udochukwu
Department of Economics, Clifford University, Owerrinta, Abia State mcdom2015@gmail.com

Agbo, Blessing Onyinye
Department of Accountancy, Renaissance University, Ugbawka, Enugu State

Abstract
The study employed time series data ranging from 1981 to 2024 to investigate the nexus between population and sustainable economic growth in Nigeria with the application of the Augmented Dicky-Fuller unit root test, the Autoregressive Distributed Lag bounds approach to cointegration (ARDL), and the Toda-Yamamoto dynamic Granger causality test econometric technique. The study model consists of real gross domestic product per capita, population growth rate, foreign direct investment, government expenditure on education, agricultural output, and gross fixed capital formation, with data sourced from the World Bank Development Indicators (WDI) and the Central Bank of Nigeria Statistical Bulletin. Findings from the study indicated that the population growth rate was insignificant but positively related to Nigeria's economic growth. In contrast, the control variables were all significant and positively related to it. The result also showed a unidirectional causal link from economic growth to population growth. The study recommended that Nigeria's policy objective of economic growth should be pursued independently of population planning. The government should invest more in human capital development projects to enhance and harness Nigeria's human resource potential. In addition, the annual budget allocation to the education and agricultural sectors should be increased, while the tax rate should be reviewed downward to encourage domestic savings.

Key Words:   Population, Economic Growth, ARDL, and Toda-Yamamoto Dynamic Granger
Causality test

Introduction
Economists generally believe that economic growth is an increase in a given economy's production volume from one year to another and that it is measured as the percentage change in a country's gross domestic product (GDP) over a given period.  Simsek and Atalay (2020) stated that population is a concept whose influence affects many aspects of human life, such as economics, sociology, psychology, and even politics. They opined that population is the total number of people living in a specified area at a particular time, that population growth is a function of many variables, and that these variables include increases in the fertility rate, decreases in the death rate, and migration.

According to Taban and Kar (2014), as cited in Seher (2021), population issues and structure are very important for both developed and developing countries in terms of policy implementation. According to them, population policies are state decisions that affect the quality, quantity, and

distribution of the population, and they also affect development in a country's health, education, housing, employment, urban planning, agriculture, and industry. They submitted that today, there are three types of population policies that countries employ to influence population growth or decline. The first is the policy aimed at slowing population growth. At the same time, the second is a policy aimed at accelerating population growth. The third policy focuses on improving the quality and quantity of the population (Dogan, 2011, in Seher, 2021).

The relationship between population growth and economic growth is as old as the human race. Robert Malthus (1798), as noted by Adeoyin (2021), postulated that the population growth rate tends to outstrip the growth rate of food production, potentially leading to human misery. His view was proved abortive by technological innovation that has revolutionised agricultural activities and manufacturing processes in both developed and developing countries today. The debate over the positive and negative aspects of population growth has generated a wealth of theoretical and empirical findings. Some of the authors were of the view that a well-developed human resources is a catalyst that stimulate economic growth as attested by the economies of the Asian Tigers (South Korea, Singapore, Indonesia, Malaysia and Taiwan) while the other school of thought postulated that increase in population retard economic growth especially in Sub Saharan Africa  where  astronomical  population  growth  has  led  to  abject  poverty,  (Orji, Ogbuabor, Nwanosike, and Anthony-Orji, 2019).

Generally, economists have not reached a unanimous conclusion on the impact of the population explosion on economic growth. Besides, empirical evidence on the issue is relatively small, especially in developing countries. However, the issue of whether population growth affects the economy cannot be overstated. This is because an increase in the population growth rate expands the labour market, thereby pushing down the wage rate. A decrease in the wage rate will spur investment in labour-intensive industries. Consequently, the economy's welfare will likely increase, accelerating economic growth. This is true because, as we all know, China is the most populous country on Earth and also the fastest-growing economy today. The secret of the success of that economy can be traced to the abundant and cheap labour resources that act as the fulcrum to the growth of that nation's economy.

Nigeria is the largest country in Africa and the most populous black nation in the world. It is bounded to the north by Chad and the Niger Republic, to the east and west by Cameroon and the Benin Republic, and to the south by the Atlantic Ocean. National Population Commission (2016) in Ogunleye, Owola, and Mumbarak (2018) stated that Nigeria's population was 182.2 million and given its high fertility rate, the country's population is set to increase tremendously in the future and that the rise in population growth is likely to have implications for the country's economic growth and development.

Many developing countries were implementing programmes to promote family planning in an attempt to control population growth. However, Nigeria, whose population is estimated to be growing at 3% per annum, seems to have ignored the consequences of population growth until
1980, when the country began to see it as a problem amid its economic growth constraints. After the oil price shock of the 1980s, Nigeria realised that a population explosion amid limited resources posed a threat to its citizens' welfare. This prompted the country to adopt a population policy to curtail its growth rate.

The country's first national population policy was promulgated in 1984 and revised in 2004. However, the policy was short-lived and ineffective due to the country's multiculturalism and religious diversity. In Nigeria, both Muslims and Christians and even traditional religious followers, believe that children are a gift from God Almighty and that any attempt to curtail their growth, either by government policy or individual action, is a sin against God (Chidi, Nwanosike, Onwuka, & Onyebuchi, 2023). These are the main reasons population policy has a limited impact on population growth in the country.

Growth is indispensable to the development of any economy, which is why, in Nigeria, economic growth has continued to dominate the government's paramount objectives. Besides, economic growth is associated with policies aimed at controlling population growth rate because a high population leads to a vicious depletion of a nation's material resources.

According to the Nigeria population and development fact sheet (2017), Nigeria's population stood at 40 million in 1950 and had increased to 192 million by 2017. During this period, Nigeria's total population increased fivefold. The paper postulated that if the population continues to grow at the rate observed in the last census, it would double in just over 20 years and increase threefold by 2050, reaching 543 million. Moreover, the contraceptive prevalence rate (CPR) is currently about 15.5%. This rapid population growth rate is primarily a result of a high fertility rate occasioned by low use of contraceptives in the country. The above presentation points to the critical state of the economy and therefore makes a clarion call for adequate measures to control Nigeria's population growth rate of3.2% per annum.

Economic theory has yet to provide a clear generalisation of the impact of the population explosion on economic growth in Nigeria. Hence, it is difficult to conclude about the prospects of the country's economic growth due to the increasing population growth rate (Adedoyin,
2021). Malthusian population theory posited that the population growth rate is negatively related to economic growth. In his view, the population grows in a geometric progression, while the food supply that sustains it grows in an arithmetic progression. If this development is left unchecked, it may lead to human misery (Orji, Ogbuabor, Nwanosike, and Anthony-Orji, 2019).

The endogenous growth model, contrary to the classical economist (Malthus), postulates that population growth is a catalyst for economic growth because a large population gives rise to a large labour force, innovators, and researchers in every economy. What we can draw from endogenous growth theory is that population is not a problem of numbers but of human welfare, given its impact on citizens' welfare and economic growth. Bucci, Prettner and Prskawetz (2019) formulated models indicating that the relationship between population growth and economic growth is monotonic, with effects varying in size, sign, and direction. Given the limited number of studies on the impact of population growth on Nigeria's economy, further investigation is required to clarify not only the relationship between the two concepts but also the causal link between the population growth rate and economic growth in the country.

The main thrust of this study is to empirically examine the long–run and causal link between population growth and economic growth in the country. It contributes to the literature by employing a new dataset spanning 1981 to 2024 and applying the Toda-Yamamoto Moto Dynamic Granger Causality test. The paper is divided into five sections. Section one introduces the study; section two reviews the relevant literature; section three presents the data analysis method; and sections four and five present the results and conclude, respectively.

Review of Related Literature
Theoretical Review
There are a good number of well-developed, well-known theories that relate population growth to economic growth, ranging from Malthusian theory to the recent Kremerian model. These theories bring out a clear picture of the relationship between the two principal concepts. The relationship between the two concepts is trapped in a dilemma of two contradictory models. The Malthusian and Kremerian models.

Malthusian theory: Reverend Thomas Malthus, an English clergyman and college professor, in his first publication titled ''The principle of population as it affects the future improvement of society published in 1798, stipulated that food is essential for the existence of man on earth. He also postulated that the passion between the two sexes is necessary, and that the population growth rate is increasing in Geometric progression of 2, 4, 16, etc., while that of the food supply is increasing in Arithmetic Progression of 1, 2, 3, 4.5, etc. By the law of nature, which makes food necessary for the existence of man, according to him, the effect of these two unequal powers must be kept equal. This implies that a strong, consistent operating check on the population is required due to the difficulty of subsistence. He believed that man, like plants and other animals, is impelled to increase the population of their species by what he termed “The powerful instinct, the urge to reproduce (Ishumael, Mukyyanuzi & Akarro 2022).

In his view, the ultimate check to population growth is the lack of food. The Pillar of Malthus's argument is that population tends to grow faster than the food supply (Mec & Cermakova, 2016). Hence, in a few years, population growth will outstrip the food supply, and that food shortage will ultimately bring an end to population growth. Reverend Malthus knew that starvation rarely kills people directly because sometimes, sickness or other things are used to kill people before they actually die. He also advocated for population control, but not by the use of contraceptives, since, as a clergyman, that is a great sin against God and man. Hence, he suggested abstinence and delay in marriage as a natural check on population explosion.

Kremerian Theory: While Malthusian theory stipulated that population growth is a stumbling block to the welfare of the people. The Kremerian theory posits that world population growth is a catalyst for economic prosperity. According to that theory, if there are more people, there will be more scientists, inventors and engineers to contribute to innovation and technological progress. As evidence for this hypothesis, the theory posits that over the broad span of human history on Earth, world growth rates have always increased alongside its population (Jacob, Cecaire & Marie, 2016). Despite contradictory conclusions about the link between population growth and economic growth, economists and other social scientists continue to struggle to prove their respective positions.

Neo-Classical Growth Theory: Most ideas concerning economic growth start with the aggregate production function, in which factors of production determine national output. According to this theory, as advanced by Solow-Swan (1956), growth occurs in three ways if land is held fixed: an increase in the labour supply, an increase in the capital stock, and an increase in productivity. Increasing labour supply, in his view, generates greater output. Real output rises if more people take part in a country's production, that is, through immigration, or if people who are not part of the labour force begin to work (Chidi, Nwanosike, Onwuka, & Onyebuchi, 2023). Capital increase can be divided into two parts: an increase in physical and human capital. Physical

capital increases output by enhancing labour productivity and providing direct services. A productive increase can, for instance, occur through investment in equipment such as computers and machinery, thereby reducing labour hours (Jorge, Cecilia, Karen, Francisco, & Pedro,
2016).

Human capital promotes economic growth because skilled workers are more productive than unskilled workers. Investment in human capital is made through university studies and on-the- job training. Productivity increases account for the increase in output that cannot be explained by increases in inputs (labour and capital) (Nlandu & Justin, 2013). This is called the productivity of input and can be affected by several factors: By either financing or supplying directly the investments that the private sector would not supply in adequate quantities because of various market failure in certain kind of infrastructure projects and basic education and health expenditure, which could directly boost private sector productivity; by efficiently supplying certain basic public services that were necessary to provide basic conditions for entrepreneur activity and long term investment; and by financing its own activities in the manner that minimizes distortions to private sector savings and investment decision and to economic activities more generally. Within this framework, government expenditure could, in principle, affect growth by influencing capital and labour, as well as the generation of technological progress, as reflected in total factor productivity (TFP). However, since the model assumes that the long-run growth rate is driven by population growth and the exogenous rate of technical progress, the effect of government expenditure on growth through production factors is only transitional.

Empirical Literature
In recent years, economists and other social scientists have examined the nexus between population and economic growth in developing countries. However, the results of their empirical work have indicated a mixture of negative and positive effects, as well as evidence of no effect.

Ademola (2009), as cited in Degu (2019), examined the nexus between the demographic dividend and economic growth in the Nigerian economy, employing time-series data spanning
1970-2017 and a multivariate Vector Autoregression (VAR) model. The study found that innovation in gross enrolment contributed to economic growth, as measured by the innovation- to-economic-support ratio. Similarly, Degu (2019) investigated the nexus between population and economic growth in Ethiopia using empirical data spanning from 1981 to 2018. The econometric packages employed in the study were the Augmented Dickey-Fuller (ADF) and the Autoregressive Distributed Lag (ARDL) approaches to cointegration. The study's findings showed that population and economic growth (proxied by gross domestic product, GDP) have a long–run relationship, as confirmed by the bounds test of cointegration. Also, from the ARDL model estimates, population growth has a negative and significant effect on economic growth in both the short run and the long run. On the other hand, gross domestic product positively and significantly affects population growth in both the short and long run. The Toda-Yamamoto Granger Causality test showed unidirectional causality from population to economic growth in that country.

Davoud, Mir Hadi, and Somayeh (2020) investigated both the short- and long-run relationships between population and economic growth in the Organisation of Islamic Countries (OIC) from
1980 to 2018 using panel cointegration and causality techniques. The study found a long-run relationship between the population growth rate and gross domestic product. The Toda- Yamamoto Granger Dynamic Causality result indicated a bidirectional causal link between population and economic growth in those countries in the short run. Cairo and Patrick (2020) investigated the impact of population growth on economic growth in Tanzania using empirical data from 1991 to 2019. They employed the Vector error correction model and the Granger causality test in their analysis. The results showed that population growth negatively affects economic growth, but the Granger causality test indicated unidirectional causality from population growth to economic growth.

To examine the causal relationship between population and economic growth in Singapore, Seher (2021) used the Toda-Yamamoto Dynamic Granger Causality test, the Augmented Dickey-Fuller test, and time-series data ranging from 1970 to 2020. The empirical work showed a unidirectional causal link from population growth to economic growth in that country. Osobase, Ohioze, Musa, Tope, and Ayobola (2022) reinvestigated the impact of population growth rate on economic growth in 66 countries that constitute 85 per cent of the global population by employing annual data ranging from 2001 to 2019 and also the Pedroni residual co-integration test, the Fixed effect estimator and panel causality test for the analysis of the data. The results of the study indicated that the population growth rate is significant but negatively related to economic growth in those countries.

The study by Ogu and Ojimadu (2023) examined the effects of population and the unemployment growth rate on the Nigerian economy from 1981 to 2021, employing the autoregressive distributed lag bound approach to cointegration for data analysis. Empirical evidence from the study indicates that unemployment and the population growth rate have significant effects on Nigeria's economic growth, with the population growth rate positively related and unemployment negatively related, as expected. Using empirical data from 2001-
2019, Anthony, Wilson, Samuel, Musa and Ayobola (2024) re-examined the impact and predictability of economic growth on population growth in 66 countries, employing panel data analysis and cointegration techniques. The co-integration result showed that there is a long-run relationship between the two concepts in those countries. Also, the panel causality results indicated a bidirectional causal link between population growth and economic growth in those countries.

Methodology
Theoretical Framework
The theoretical framework adopted for this study is neoclassical growth theory, propounded by Solow and Swan (1956). According to Najeb (2013), the model employed the aggregate production function based on three key assumptions:
i.        The labour force grows at a constant exogenous rate
ii.       Output is a function of capital and labour such that
iii.      Y  =  F(K, L)           ……………3.1
There is no independent investment: S   =   I     =    sY
Where Y, L, K, S and I are the economy's output, input of capital and labour, saving and
investment, while F is the functional relationship relating output to the variable inputs.

Model Specification
Our empirical estimation will start with a modified version of Equation 3.1, with the population
growth rate, foreign direct investment, public expenditure on education, Agricultural output, and
Gross fixed capital formation included as inputs in the production function. Hence, we specify
our aggregate production function bearing in mind our variable of interest, thus:

GDPpc      = F( POPGR, FDI, GEE, AGROPT, GCFC) …………………3.2
Econometrically, equation 3.2 was transformed from mathematical form into:
^GDPpc ^= ^âï ^+ ^â_1^POPGR ^+ ^â_2^FDI ^+ ^â_3^GEE ^+ ^â_4^AGROPT ^+ ^â_5^GFCF+ ^ìt ^………………  ^3.3

Where
GDPpc | = | Gross domestic product per capita
POPGR | = | Annual population growth rate
FDI | = | Foreign direct investment
GEE | = | Government expenditure in education
AGROPT | = | Agricultural output
GFCF | = | Gross Fixed Capital saving

Restating the empirical model as an ARDL model in line with the framework of the study gives:

------------------------------------------------------------3.-4

Where p denotes the lag length, Ä represents the difference operator, á_0   is the drift, µ_t  is the disturbance term, and á_1, á_2, á_3, á_4, á_5, and á6 are coefficients of short-run dynamics. At the same time, â1, â2, â3, â4, â5, and â_6  are coefficients of the long-run relationship. Hence, the ARDL model is the base equation for estimating the short-run and long-run relationship among the variables.

The null and alternative hypotheses of no cointegration and cointegration can be evaluated by comparing the computed F-statistic with the tabulated F-statistic for the lower bound 1(0) and the upper bound 1(1), respectively. In the ARDL model, the coefficients that would be verified under the null hypotheses of no cointegration and cointegration between economic growth and the causal factors are stated as shown below:
^H_0^: ^â_1^=â_2^=â_3^=â_4^= ^â_5 ^= ^â_6^=0
Against

^H_1^: ^â_1

^â_2       ^â_3

^â_4       ^â_5

^â_6       ^0

If the computed F-statistic is below the critical value at the lower bound 1(0), we conclude that there is no cointegration among the variables and hence no long-run relationship in the series. However, if the computed F-statistic is above the critical value of the upper bound 1(1), the conclusion is that cointegration and a long-run relationship exist among the variables in the

series. On the other hand, if the value of the F–statistic falls between the lower 1(0) and the upper
1(1) bounds, the test is inconclusive. The presence of cointegration will lead to the estimation of short-run and long-run parameters; if there is no cointegration among the variables, the procedure will cease.

Table 3.1: Definitions, measures, sources and expected signs of variables used in this study.

Variables | Definition and/ or proxy | Sources of data | Expected sign

GDPpc

Real Gross Domestic

Product per capita

World Bank Development

Indicator (WDI)

Dependent

variable

POPGR | Population growth rate | WDI | +
FDI | Foreign direct investment | WDI | +

GEE

Government expenditure in

education

Central Bank of Nigeria

Statistical Bulletin

+

AGROUTPUT

Agricultural output

Central Bank of Nigeria

Statistical Bulletin

+

GFCF | Gross Fixed Capital Saving | WDI | +

Source: Researchers compilation 2026
The Toda and Yamamoto multivariate framework of our case study can be stated as follows:

The study used secondary data that range from 1981 to 2024. The study timeframe was based on data availability. The data for this study were sourced from the World Bank's World Development Indicators (WDI) and the Central Bank of Nigeria (CBN) Statistical Bulletin. The study used the Autoregressive Distributed Lag (ARDL) Bound test for cointegration, popularised by Pesaran, Shin and Smith (2001). The Augmented Dickey-Fuller unit root test was used to examine the time-series properties of the data prior to estimating the economic growth equation. Definitions, measures, sources, and expected signs of the variables used in this empirical work are shown in Table 3.1 above.

Result Presentation, Analysis and Discussion of Findings
4.1 Results of Augmented Dickey Fuller (ADF) Unit Root Test on Series
Table 4.1.1: Results of the unit root tests

Variable

Augmented Dickey -Fuller

(ADF)

Order of

Integration

Decision

| Level | First Difference | I(1) | Stationary
GDPPC | - | -64.91705 | I (1) | Stationary
POPGR | | -5.587658 | I (1) | Stationary
FDI | - | -2.793133 | 1(1) | Stationary
GEE | - | -6.091094 | 1(1) | Stationary
AGROUTPUT | - | -6.232623 | I (1) | Stationary
GFCF | -3.931591 | - | I (0) | Stationary
Source: Researchers' Estimation using E-views 9

The result of the ADF stationarity tests indicates that only the gross fixed capital formation was stationary at the level form. In contrast, gross domestic product per capita, population growth rate, foreign direct investment, government expenditure on education, and agricultural output were stationary after first differencing, indicating that cointegration exists among these variables. Hence, the Autoregressive Distributed Lag (ADL) approach to cointegration was employed to estimate the short–run and long-run relationship between the regress or and the regress and.

Results of Diagnostic Tests for the ARDL Model
Table 4.1.2: Diagnostic Results for ARDL Model

Test

Test

Statistic

P-value

Null Hypothesis

Conclusion

Breusch-Godfrey Serial

Correlation LM Test

1.251853

0.3047

^H_o^: ^No ^serial

Correlation

^Accept ^H_o

Ramsey RESET test

0.371701

0.7127

^H_o^: ^not               ^correctly

specified

^Accept ^H_o

Jarque-Bera normality test

34.11718

0.000000

H_o: Normal

Distribution

Reject H_o

Heteroskedasticity Test:

ARCH

1.008909

0.4748

^H_o^: ^Homoskedasticity

^Accept ^H_o

Source: Researcher's Estimation using E-views 9

Table 4.1.2 shows the diagnostic test results for the ARDL model. The diagnostic test showed that the model was not correctly specified, as indicated by the significance of the Jarque-Bera normality test. While the insignificance of the Breusch-Godfrey Serial Correlation LM Test, Ramsey RESET test and Heteroskedasticity Test (ARCH) indicated that there was no serial correlation in the model, because of the insignificance of the Breusch-Godfrey Serial Correlation LM Test and that the model was correctly specified, as indicated by the insignificance of the Ramsey RESET test. Besides, the error term has a constant variance.

Results of the Bounds Test for Cointegration
Table 4.1.3: Bounds Tests for the Existence of Co-Integration

Test Statistic

Value

Lag

Significance

Level

Bound Critical Values* Lower Bound Upper Bound

F-statistic | 8.937104 | 2 | | I(0) | I(1)
| | | 1% | 3.93 | 5.23
_R^2 | 0.650000 | | 5% | 3.12 | 4.25
Adjusted R^2 | 0.537097 | | 10% | 2.75 | 3.79
Critical value bounds for the F-statistic at 95% confidence level from Pesaran, Shin, and Smith (2001).
Source: Researcher's Estimation using E-views 9

The results of the bounds test for cointegration are shown in Table 4.1.3 above. The calculated F- statistic for the combined test of the parameters in the empirical design for Nigeria was 8.93714, which exceeded the upper critical values at the 1%, 5%, and 10% significance levels, respectively. Based on this result, we reject the null hypothesis of no cointegration and accept the alternative hypothesis that a long–run relationship exists among the variables.

Results of the Long-run Relationship
The results in Table 4.1.4 revealed that only the population growth rate variable was insignificant and had the expected sign in the long run. All other variables were significant and had the expected signs, except for gross fixed capital formation, which had a negative sign. The result indicated that all the variables conform to a priori expectations.

Table 4.1.4: Results for Estimated Long-Run Coefficients

Dependent Variable: GDPPC
Variable | Coefficient | Std. Error | t-Statistic | Prob.
C | -1.975992 | 877.557755 | -0.002252 | 0.9982
POPGR | 590.872098 | 301.438258 | 1.960176 | 0.0590
FDI | 91.911967 | 36.050760 | 2.549515*** | 0.0160
GEE | 0.000813 | 0.000240 | 3.383786*** | 0.0020
AGROUTPUT | 0.109868 | 0.010125 | 10.850765 | 0.0000
GFCF | -5.487534 | 2.400254 | 2.400254*** | 0.0292
Note: *** denotes significance at 1% level of significance.
Source: Researcher's Estimation using E-views 9

Table 4.1.4 depicts the estimated long-run result of the nexus between population growth and sustainable economic growth in Nigeria. The population growth rate had a positive and insignificant impact on the growth of the country's economic activities. This implies that population growth did not significantly contribute to economic expansion during the period. The insignificant effect may be linked to:
·High dependency ratio,
·Unemployment and underemployment,
·Insufficient capacity of the economy to absorb the growing population productively Foreign direct investment was significant and positively related to Nigeria's economic growth, indicating that the trade liberalisation policy embraced by Nigeria over the years is yielding the desired results by attracting foreign investors and that their investment is achieving the desired outcomes.

Government expenditure in education was also significant and positively related to economic growth in Nigeria. This significance and alignment with the a priori expectation imply that the substantial funds budgeted to the educational sector by both the state and federal governments annually are producing the desired human capital resources capable of propelling the country's economy to greater heights.

Additionally, agricultural output and gross fixed capital formation were positive and significantly related to the sustainable growth of Nigeria's economic activities. This implies that the agricultural sector has assumed its rightful position as one of the catalysts that accelerate the growth and development of Nigeria's economy. Also, judicious use and application of funds, along with a conducive investment climate in the country, encouraged greater investment in the economy, as investors were not only breaking even in their businesses but also reporting substantial annual profits.

Table 4.1.5: Results of the Estimated Short-run Error Correction Model

Dependent Variable: GDPPC
Variable | Coefficient | Std. Error | t-Statistic | Prob.
D(POPGR) | 287.799955 | 126.774012 | 2.270181 | 0.0303
D(FDI) | 7.561523 | 15.092070 | 0.501026 | 0.6199
D(GEE) | -0.000049 | 0.000117 | -0.415553 | 0.6806
D(AGROUT) | 0.053514 | 0.010274 | 5.208649*** | 0.0000
D(GFCF) | -2.672849 | 1.273780 | -2.098361*** | 0.0441
^ECM_t-1 | -0.487077 | 0.069316 | -7.026863*** | 0.0000
ECM= RGDPPC - (590.8721*POPGR + 91.9120*FDI + 0.0008*GEE
+ 0.1099*AGROUTPUT -5.4875*GFCF  -1.9760 -22.5893*@TREND

Source: Researcher's Estimation using E-views 9

The results of the short-run dynamic estimates were shown in Table 4.1.5. The short-run dynamic estimates largely agree with the long-run estimates. The population growth rate from the previous year was positively and significantly associated with sustainable economic growth

in Nigeria. This implies that economic growth would increase by 288% if the population growth rate were to increase by 1 unit. Changes in foreign direct investment showed a positive but insignificant link with the country's economic growth. Changes in government expenditure on education were insignificant and negatively related to sustainable economic growth in Nigeria. Changes in agricultural output were positive and significantly linked to sustainable economic growth in Nigeria in the short run. Moreover, this means that Nigeria's economy will increase by
54% if agricultural output increases by one unit. The change in gross fixed capital formation was negative and significantly associated with the country's economic growth, implying that a 1-unit increase in gross fixed capital formation would lead to a 27% decline in economic growth. The coefficient of the error correction model, 49%, implies that 49% of the previous deviation of economic growth from equilibrium was corrected within one year. In addition, the negative sign and significance of the coefficient of the error correction term for the long-run suitable equilibrium further corroborate the existence of a long-run nexus between population growth rate and sustainable economic growth in Nigeria.

Toda Yamamoto Granger Causality Test Result

Table 4.1.6 Results of the Granger Causality Test (TYAugmented Lags Methods)

| Sources of Causation

Dependent/ Variable

RGDPPc
_X ^2

POPGR
_X ^2

POPGR | | 21.10388***
RGDPPc | 2.802613 |
Source: Researcher's Computation using Eview 9

Toda and Yamamoto's (TY) estimation result is depicted in Table 4.1.6. The results revealed unidirectional causality from real gross domestic product per capita to the population growth rate. The unidirectional causality detected for Nigeria suggests that the policy objectives of sustainable economic growth and the population growth rate were pursued independently. The implication of these findings for Nigeria is that the country does not pursue the policy objectives of population growth and economic growth simultaneously.

Conclusion
The nexus between population growth rate and sustainable economic growth has been a controversial issue in both developed and developing countries, yielding mixed findings. Hence, this paper contributed differently to the prevailing literature on population growth rate and economic growth by examining the causal link between the two concepts in Nigeria using data from 1981 to 2024. Findings from the study indicated a unidirectional relationship between population growth rate and economic growth in Nigeria, and that the population growth rate exerts an insignificant impact on Nigeria's economic growth. Furthermore, foreign direct investment, government expenditure in education, agricultural output and gross fixed capital formation were significant and positively related to economic growth in the country.

Policy recommendations
In view of the empirical outcome of this study, we make the following policy recommendations:
1.        Nigeria should pursue the policy objective of economic growth and that of population
growth independently because economic growth decisions are not primarily made to
stimulate the growth of the country's population, nor does population growth translate to a
catalyst that stimulates growth in the country's economic activities. Invest in population-
related development strategies. Improved human capital development can ensure that
population growth contributes more effectively to economic productivity in Nigeria. The
government should provide a more conducive investment climate and infrastructure to
attract more foreign direct investment into our economy.
2.        Also, annual budgetary allocation to the educational sector should be reviewed upwards
in order to enhance the training and development of abundant human resources in Nigeria
3.        The agricultural sector must be given adequate attention by the three tiers of the
government in Nigeria so that the sector will assume its former position in the country as
the backbone of Nigeria's economy. The government should encourage domestic savings
by reducing tax rates, as higher national savings will increase the supply of loanable funds
to investors at very low interest rates, thereby deepening investment in the Nigerian
economy.

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