







































 
 

 

130 
© 2025 by the authors; licensee Asian Online Journal Publishing Group 
 

Economy 
Vol. 12, No. 2, 130-138, 2025 

ISSN(E) 2313-8181/ ISSN(P) 2518-0118 
DOI: 10.20448/economy.v12i2.7422 

© 2025 by the authors; licensee Asian Online Journal Publishing Group 

 
 

 
 
 
Moderating role of population growth rate on remittance-growth nexus in Nigeria 

 

Afamefuna Angus EZE1  
Stephen Okechukwu ANYAMADU2 
Emmanuel CHINANUIFE3 
Chiedozie ESOMNOFU4 
Esther Chioma Anakwue5 

 

            
( Corresponding Author) 

 
1,2Department of Economics, University of Nigeria, Nsukka, Nigeria. 
1Email: angus.eze@unn.edu.ng  
2Email: stephenanya@gmail.com  
3Department of Economics, Topfaith University, Mkpatak, Akwa Ibom. Nigeria. 
3Email: chinanuifeemma@gmail.com  
4Department of Economics, Nwafor Orizu College of Education, Anambra State, Nigeria.  
4Email: esomnofuchiedozie@gmail.com  
5Airforce Institute of Technology, Kaduna, Nigeria. 
5Email: anakwuee@gmail.com  

 
Abstract 

There has been debate about whether the population growth rate and remittance impacts are 
beneficial or detrimental to economic growth and whether population growth has any moderating 
role in the remittance-growth nexus. The purpose of this study is to empirically investigate the 
moderating role of population growth in the remittance-growth nexus, as well as to evaluate the 
direction of causality between these elements. The Autoregressive Distributed Lag (ARDL) model 
and the Granger causality test were employed to analyze the study's objectives. The analysis used 
data from the World Bank's World Development Indicators for the years 1990-2022. The findings 
of this study reveal that both population growth and remittances have a positive and significant 
impact on economic growth in the long run, whereas the population growth rate negatively and 
significantly moderates the impact of remittances on economic growth in the long run but is 
insignificant in the short run. The Granger causality test demonstrates unidirectional causation 
flowing from population expansion to economic growth. It consequently proposes that the 
government and individuals who receive these remittances invest them in more productive sectors 
such as health, education, and training so that they have a positive impact on the country's economic 
progress. 

 
Keywords: ARDL technique, economic growth, population growth, remittances, ECM, Granger causality. 

 
Citation | EZE, A. A., ANYAMADU, S. O., CHINANUIFE, E., 
ESOMNOFU, C., & Anakwue, E. C. (2025). Moderating role of 
population growth rate on remittance-growth nexus in Nigeria. 
Economy, 12(2), 130–138. 10.20448/economy.v12i2.7422 
History:  
Received: 8 August 2025 
Revised: 27 August 2025 
Accepted: 4 September 2025 
Published: 16 September 2025 
Licensed: This work is licensed under a Creative Commons 

Attribution 4.0 License  
Publisher:  Asian Online Journal Publishing Group 
 

Funding: This study received no specific financial support. 
Institutional Review Board Statement: Not applicable. 
Transparency: The authors confirm that the manuscript is an honest, accurate, 
and transparent account of the study; that no vital features of the study have 
been omitted; and that any discrepancies from the study as planned have been 
explained. This study followed all ethical practices during writing. 
Data Availability Statement: The corresponding author may provide study 
data upon reasonable request. 
Competing Interests: The authors declare that they have no competing 
interests. 
Authors’ Contributions:  All authors contributed equally to the conception 
and design of the study. All authors have read and agreed to the published 
version of the manuscript. 

 
Contents 

1. Introduction .................................................................................................................................................................................... 131 
2. Literature Review .......................................................................................................................................................................... 132 
3. Methodology ................................................................................................................................................................................... 132 
4. Presentation of Results and Findings ........................................................................................................................................ 134 
5. Discussion of Findings .................................................................................................................................................................. 135 
6. Conclusion and Recommendation .............................................................................................................................................. 136 
References ............................................................................................................................................................................................ 137 
 

 

mailto:angus.eze@unn.edu.ng
mailto:stephenanya@gmail.com
mailto:chinanuifeemma@gmail.com
mailto:esomnofuchiedozie@gmail.com
mailto:anakwuee@gmail.com
https://creativecommons.org/licenses/by/4.0/
https://creativecommons.org/licenses/by/4.0/
https://www.doi.org/10.20448/economy.v12i2.7422
https://orcid.org/0000-0003-1163-372X


Economy, 2025, 12(2): 130-138 

131 
© 2025 by the authors; licensee Asian Online Journal Publishing Group 

 

 

Contribution of this paper to the literature 
This study contributes to the existing literature by examining the interaction between population 
growth and remittances on economic growth in Nigeria. It aims to determine whether increasing 
population significantly moderates the impact of international remittances on Nigeria's economic 
growth. 

 

1. Introduction 
Economic growth and sustainability serve as key indicators of a nation’s overall development and prosperity. 

They involve the increase of gross product and the overall advancement of the standard of living of its citizens 
(Hossain, 2019; Korsah, 2022). Economic sustainability, therefore, is one of the major objectives of any government, 
encompassing advancements in infrastructure, technology, education, and social well-being (Odhiambo, 2019). Its 
great importance causes the government to employ different strategies to boost its economy while ensuring 
sustainability in other sectors, such as reducing poverty, creating employment opportunities, and enhancing the 
quality of life. A major economic indicator used in measuring economic growth is the Real GDP (RGDP). Over the 
past decades, it has seen an accelerating increase from $12.55 billion in 1970 to $440.84 billion in 2021 (World Bank, 
2022). This sustained growth is likely associated with factors such as increased productivity, investments, population 
dynamics, and overall economic expansion (Asiamah, Ofori, & Afful, 2019). 

The global population has seen a consistent increase attributed to growing populations in various countries; 
however, this population growth rate varies across regions and countries, with developing nations experiencing more 
significant increases compared to developed nations. Nigeria, in particular, has witnessed a significant surge in 
population, initially having a population of just 45.2 million people as of 1960, tripling the figure to over 200 million 
Nigerians within the last 56 years, with a projection of 262,580,426 in the year 2030, thereby positioning Nigeria as 
the third most populous country globally (World Bank, 2022).  This divergence introduces a dimension of global 
inequality, with implications for international trade, migration patterns, remittances, and the distribution of 
resources. A larger population can contribute to increased labor supply and consumer demand, potentially fostering 
economic growth (Peterson, 2017). However, rapid population growth can also cause limitations in resource 
allocation, infrastructure, and social services, potentially hindering economic progress (Headey & Hodge, 2009). The 
third school of thought holds that population increase is a neutral component in economic growth that is determined 
outside of typical growth models. Thus, even with declining returns to the population in the production of consumer 
goods, zero population growth is not required for a long-term rise in per capita consumption. 

Nigeria faces challenges in managing its population dynamics and harnessing the potential benefits of its 
demographic dividend. Remittances, defined as the transfer of funds by migrant workers to their home countries, 
have been recognized as a significant contributor to economic growth, particularly in developing economies (Abdulai, 
2023; Jackman, Moore, & Craigwell, 2011; Ratha, 2003). Remittances can stimulate domestic consumption, 
investment, and access to education and healthcare, thereby fostering economic development (Fayissa & Nsiah, 2010; 
Ratha, Mohapatra, & Silwal, 2011). In Nigeria, remittances have been a crucial source of external financing, with 
inflows reaching $19.2 billion in 2021, accounting for 3.8% of the country's GDP (World Bank, 2022), which 
increased to $19.5 billion in 2023, making remittances the second-largest source of foreign exchange and 
international inflows (Alechenu, 2021). 

Remittances are garnering increased attention due to substantial outflows to developing nations, both in terms 
of volume and their impact on recipient economies. Between 2010 and 2017, remittances to Sub-Saharan Africa 
increased by 9.6%, reaching approximately US $33 billion, while overall growth in developing countries was 26.2%. 
According to the World Bank's "Migration and Development Brief 35" (see Figure 1), the top ten remittance 
recipients in SSA in 2021 are Nigeria, Ghana, Kenya, Senegal, Zimbabwe, Democratic Republic of the Congo, 
Uganda, Mali, South Africa, and The Gambia, with the highest and lowest receiving US$19.2 billion and US$0.7 
billion, respectively. Ghana and Mali had remittance inflows exceeding 5% of GDP, Zimbabwe and Senegal exceeded 
10%, and The Gambia surpassed 20% (World Bank, 2022). 

 

 
Figure 1. 10 top remittance receiving countries in Sub-Saharan Africa. 

Source: World Bank (2022). 

 
The interplay between population growth, remittances, and economic growth has been the subject of ongoing 

research and debate. Studies have explored the potential moderating effects of population growth on the remittance-
economic growth relationship, with varying findings across different contexts. For instance, Jayaraman, Choong, 



Economy, 2025, 12(2): 130-138 

132 
© 2025 by the authors; licensee Asian Online Journal Publishing Group 

 

 

and Chand (2016) found that population growth strengthened the positive impact of remittances on economic growth 
in Pacific Island countries, while Azam (2015) reported a negative moderating effect in high-remittance countries. 
However, there has not been any study on the moderating role of population growth rate on remittances-growth 
nexus in Nigeria.  
 

2. Literature Review 
The theoretical framework of this study is hinged on the Neo-classical theory view of the impact of population 

dynamics and foreign remittances on economic growth. It emphasizes market forces leading to an analysis of how 
households allocate remittances based on local market conditions and the availability of goods and services. 
Furthermore, the theory suggests that remittances are used as investments in human capital, contributing to 
education, healthcare, and skill development, ultimately enhancing productivity and economic growth. Neoclassical 
economics also highlights the role of savings in capital formation and long-term economic growth, prompting an 
examination of how remittances influence household savings behavior and contribute to capital within communities. 
Additionally, the impact of remittances on labor market dynamics is explored, considering how increased resources 
may affect wage rates, employment patterns, and overall labor market structure, thereby influencing economic 
growth. 
 

2.1. Review on Population Growth, Remittances and Economic Growth in Nigeria 
There are several studies on either the impact of population growth on economic growth or the impact of 

remittances on economic growth, or both, but not on the moderating role of population growth on the remittances-
growth nexus in Nigeria. However, their findings are quite inconclusive. While some studies found positive and 
significant impacts of population growth and remittances on economic growth, others found negative and significant 
impacts, whereas some had mixed findings. This section will be partitioned in this manner for coherence purposes. 

First, studies that found a positive and significant correlation between population growth and economic growth, 
as well as remittances and economic growth, using different estimation techniques and variable proxies include 

(Adeseye, 2021; Efuntade & Efuntade, 2020; Kudaisi, Ojeyinka, & Osinubi, 2022; Kuhe, 2019; Muhammad, Özdeşer, 
& Adedeji, 2024; Ogbaro, Sanni, Adeoye, Akintaro, & Eseyin, 2023; Osei-Gyebi, Opoku, Lipede, & Kountchou, 2023; 
Ribadu, 2023). Second, studies that found a negative and significant correlation between population growth and 
economic growth and remittances and economic growth in Nigeria are: Okorie, Nwabufoh, and Oriaku (2022); 
Ogbaro et al. (2023); Raphael, Peter, and Kenneth (2024); Adeleye, Ologunwa, and Ogunjobi (2021); Oyegoke and 
Ebele (2023), and Effiong (2022). Other studies had mixed findings of either a positive and significant impact of 
population growth on economic growth or remittances on economic growth in the short run or in the long run and 
vice versa. Such studies include Didia and Tahir (2022), who found that remittances hurt economic growth in the 
short run while having no impact in the long run. Similarly, studies by Omoniyi and Owoeye (2024) shows that 
remittance inflow has an insignificant negative impact on economic growth in the short run; however, in the long 
run, remittance inflows have a significant impact on the GDP growth rate. Others include Oyegoke and Ebele (2023) 
and Didia and Tahir (2022).  
 

2.2. Review on Population Growth, Remittance and Economic Growth Outside Nigeria 
Similarly, research on the impact of remittances and population expansion on economic growth has produced 

conflicting results, depending on the methodology and scope used. Several studies, including Islam (2022), Bucevska 

(2022), Kajtazi and Fetai (2022), Depken, Nikšić Radić, and Paleka (2021), Sghaier (2021), Mohamed Aslam and 
Alibuhtto (2023), Gniniguè and Ali (2021), Dutta and Saikia (2024), Imran, Wu, Yu, Zhong, and Moon (2021), and 
Ramanayake and Wijetunga (2018), discovered a positive and significant impact of remittances on economic growth. 
However, several studies have revealed that remittances can have a negative and considerable impact on economic 
growth. These studies include Nyasha and Odhiambo (2022); Siifa, Teniola, and Zayyad (2023); Abdulai (2023), and 
Qutb (2022). Furthermore, other research showed contradictory findings, particularly when interacting with other 
macro factors. For example, Ur Rehman and Hysa (2021) discovered that remittances and financial development had 
a good impact on economic growth in Western Balkan nations (WBC), but when remittances were combined with 
financial development, they had a large and negative effect on economic growth. Some studies had mixed results 
when different approaches were used. Golder, Rumaly, Hossain, and Nigar (2023) employed both linear and non-
linear ARDL models and concluded that remittances had a positive and negative impact on Bangladesh's economic 
growth, respectively. Similarly, Odugbesan, Sunday, and Olowu (2021) discovered that both financial development 
and economic growth in MINT countries stimulate economic growth positively when panel linear ARDL was used, 
but that both positive and negative shocks in financial development increase economic growth, while a positive and 
negative shock in remittance increases economic growth in the long run when panel Non ARDL was used. 
Furthermore, Yadeta and Hunegnaw (2022) discovered that remittances have a negative short-run influence on 
economic growth in Ethiopia, but a positive long-run effect. The study also discovered unidirectional causality 
between remittances and economic growth. In contrast, studies by Abdulai (2023) show that remittances have a long-
term association with Ghana's economic growth but have a negative impact when combined with unemployment. 
 

3. Methodology 
3.1. Theoretical Framework 

The theoretical framework of this study is based on the Neo-classical theory regarding the impact of population 
dynamics and foreign remittances on economic growth. It emphasizes market forces, leading to an analysis of how 
households allocate remittances based on local market conditions and the availability of goods and services. 
Furthermore, the theory suggests that remittances are used as investments in human capital, contributing to 
education, healthcare, and skill development, ultimately enhancing productivity and economic growth. Neoclassical 
economics also highlights the role of savings in capital formation and long-term economic growth, prompting an 
examination of how remittances influence household savings behavior and contribute to capital within communities. 



Economy, 2025, 12(2): 130-138 

133 
© 2025 by the authors; licensee Asian Online Journal Publishing Group 

 

 

3.2. Model Specification 
The section covers the many statistical tools and packages used for data analysis. First, we performed a statistical 

descriptive analysis of the components. Second, the study used the Augmented Dickey-Fuller (ADF) test to 
determine stationarity for all series. After determining that there were no unit roots, the bound cointegration test 
was employed to evaluate the series' cointegration. The bound F-statistic was used to compare the null hypothesis 
of no level cointegration to the alternative of level cointegration. If the computed F-statistic exceeds the upper 
bound's critical F-statistic, we reject the null hypothesis and accept the alternative that the series have long-term 
cointegration. Once the long-term link between the series has been confirmed, we can estimate the conditional ARDL 
long-run model. Our empirical model takes the following functional form. 

𝐿𝑅𝐺𝐷𝑃 =  𝐹 (𝑃𝑂𝑃𝑅, 𝑁𝑀, 𝐿𝐺𝐹𝐶𝐹, 𝐿𝑅𝐸𝑀, 𝐿(𝑅𝐸𝑀 ∗ 𝑃𝑂𝑃𝑅))       (1) 
Where; 
LRGDP = Log of real gross domestic product (Proxy for economic growth). 
POPR = Population growth rate. 
NM = Net migration. 
LGFCF = Log of gross fixed capital formation. 
LREM = Log of remittances. 
L(rem*popr) = Log of the interactive term of remittances and population growth rate.  
The following is a linear form of Equation 1, which can be expressed as:  

𝐿𝑅𝐺𝐷𝑃𝑡 =  𝜃0  + 𝜃1𝑃𝑂𝑃𝑅𝑡  + 𝜃2𝑁𝑀𝑡  + 𝜃3𝐿𝐺𝐹𝐶𝐹𝑡  +  𝜃4𝐿𝑅𝐸𝑀𝑡  +  𝜃5 𝐿(𝑅𝐸𝑀 ∗ 𝑃𝑂𝑃𝑅)𝑡  +   𝜔𝑡     (2) 
Because it can handle various levels of integration, the ARDL model is used. It also appears to be more effective 

than traditional cointegration models, such as the Phillips-Ouliaris test, the Johansen test, and the Engle-Granger 
method (Engle & Granger, 1987). This is because it can simultaneously estimate both the short-run and long-run 

estimates (Işık, 2013). Last but not least, adding lags to the model also solves the endogeneity issue (Amin, Shahbaz, 
& Mahalik, 2020; Menegaki, 2019; Sam, Nyongesa, & Ouma, 2019). It also yields trustworthy results for small sample 
sizes (Wang, Ali, Khan, Tiwari, & Bhat, 2021). The following describes the Autoregressive Distributed Lag model 
that needs to be estimated: 

ΔLRGDP = α0 +∑ 𝜙𝑖𝛥LRGDP − 𝑖
𝑝
𝑖=1 + ∑ 𝛳𝑖𝛥𝑃𝑂𝑃𝑅𝑡 − 𝑖 

𝑝
𝑖=0 + ∑ ϻ𝑖𝛥𝑁𝑀𝑡 − 𝑖 

𝑝
𝑖=0 + +∑ ʘ𝑖𝛥𝐿𝐺𝐹𝐶𝐹𝑡 − 𝑖 

𝑝
𝑖=0 +

 ∑ 𝛹
𝑝
𝑖=0 𝑖𝛥𝐿𝑅𝐸𝑀𝑡 − 𝑖   +∑ 𝛺

𝑝
𝑖=0 𝑖𝛥L(REM ∗ POPR)𝑡 − 𝑖  +δ1POPRt-1 + δ2NMt-1 + δ3LGFCFt-1 + δ4REMt-1 + 

δ5(REM ∗ POPR)t-1 + ϖt    (3) 
Where; 

Δ = first difference operator.  

The parameters α1 – α5 = Short-run relationship parameters.  

The parameters β1 – β5= Long-run relationship parameters.  
(t – i) = Lagged term on respective variables.  

Σ ϖi = Summation operator and error term of the equation. 
Where:  
L(REM*POPR), POPR, NM, LGFCF, LREM and t remains as defined in equation 3 above. 

ε𝑡 = The random, error, or stochastic term. 

θ0 = Intercept term or constant parameter. 

θ1, θ2, θ3, θ4, and θ5 = The regression parameters and slopes of the respective explanatory variables. 
 

3.3. Justification of Variables 
3.3.1. Real Gross Domestic Product (RGDP) 

Real GDP is a measure that looks at the rate at which all goods and services are produced in a country for a 
given year, accounting for inflation. According to economic theory, the expansion of the workforce, market size, and 
consumption habits are only a few of the ways that population growth can impact economic growth. 
 

3.3.2. Population Growth Rate (POPR) 
The average annual rate of change in population size during a given time period is known as population growth. 

One of the main factors influencing economic growth is population expansion. According to Orji, Ogbuabor, 
Iwuagwu, and Anthony-Orji (2020), a higher population growth rate may result in stronger demand for products 
and services, consumption, and labour force involvement, all of which could have a beneficial impact on economic 
growth. 
 

3.3.3. Remittances Received (REM) 
Personal remittances refer to the amount of money sent home by individuals abroad. They may serve different 

purposes, either in the form of financial support to family or as an investment, in which the remitter could fall back 
on. Remittances play a crucial role in many developing economies, contributing to poverty alleviation, consumption, 
and investment, thereby stimulating economic growth. 
 

3.3.4. Net Migration Rate (NM) 
The difference between the number of immigrants (those entering a country) and emigrants (those departing) 

per 1,000 inhabitants is known as the net migration rate. Economic development, labor markets, remittance patterns, 
and population dynamics can all be strongly impacted by migration trends. 
 
3.3.5. Gross Fixed Capital Formation (GFCF) 

This is a stand-in for investment; it is the sum of changes in stocks (inventory) and fixed asset values. Future 
profits are the reason for investing. Over time, Nigeria's GFCF as a percentage of RGDP has been erratic. 
 



Economy, 2025, 12(2): 130-138 

134 
© 2025 by the authors; licensee Asian Online Journal Publishing Group 

 

 

4. Presentation of Results and Findings 
4.1. Descriptive Statistics of the Variables 

The data set used for this study will be described in this section using two major approaches: the tabular 
statistical measures, which showcase the central tendency and dispersion of the variables through mean, median, 
mode, variance, and standard deviation; and the graphical approach, which displays the movement of trends over 
time. 

 
Table 1. Descriptive statistics of the variables. 

 
Table 1 shows the statistical description of the data based on its face value information only without any 

manipulation or in-depth analysis. That is to say, the table displays the measures of cluster, dispersion, and variability 
of the variables under consideration. From the results above, the mean value of logged remittance and population 
growth rate the major dependent variables for this study are 21.38985 and 2.631667, respectively. The mean indicates 
the average values or anticipated observations of the variables in question over the course of the study in Nigeria. In 
terms of their individual mean values, this interpretation is comparable to that of other variables. The range is the 
difference between the data set's maximum and minimum values. The table does not imply that there are any outliers 
in the data set, according to mathematical understanding. Additionally, the standard deviations show that there are 
some variances in the variables and that around two of the variables in the data set are favorably skewed. 

 

 
Figure 2. Descriptive graph of the variables. 

Source: Author’s computation using e-views. 
 

 
Figure 2 illustrates multiple line graphs displaying various data trends over this study time span. The log of 

Gross Domestic Product and Exchange Rate shows a generally upward trend, while Log of Gross Capital Formation, 
Remittance Received, and Inflation Rate exhibit more volatile or fluctuating patterns. Net Migration and Population 
Growth Rate also display sharp peaks or dips at certain points in time. 

 

4.2. Pre-Estimation Test Results 
Pre-estimation tests are usually prerequisites for any econometric analysis because they help to avoid the 

occurrence of spurious regression results. Regarding this, the two major pre-estimation tests listed below were 
employed in this study: 

i. Stationarity/Unit Root Test. 

Variables LRGDP LREM LGFCF LEXCHR L(REM*POPR) INF NM POPR 

 Mean 31.3 21.4 29.8 4.30 22.4 19.8 -0.28 2.63 
 Median 31.3 22.5 29.7 4.85 23.5 12.9 -0.29 2.62 
 Maximum 32.0 23.9 30.1 6.05 24.8 72.8 -0.17 2.80 
 Minimum 30.5 14.7 29.4 1.39 15.7 5.39 -0.51 2.41 
 Std. Dev. 0.51 2.82 0.17 1.35 2.83 17.4 0.09 0.10 
 Skewness 0.05 -0.97 -0.20 -0.71 -0.97 1.74 -0.42 -0.17 
 Kurtosis 1.39 2.80 2.41 2.26 2.88 4.71 2.50 2.16 
Jarque-Bera 3.91 5.71 0.75 3.82 5.70 22.5 1.44 1.22 
 Probability 0.14 0.06 0.69 0.15 0.06 0.00 0.49 0.54 
 Sum 1125 770 107 155 805 713 -10.1 94.7 
 Sum Sq. Dev. 8.97 279 1.03 64.1 280 106 0.26 0.38 
 Observations 36 36 36 36 36 36 36 36 



Economy, 2025, 12(2): 130-138 

135 
© 2025 by the authors; licensee Asian Online Journal Publishing Group 

 

 

ii. Cointegration Test. 
 
Table 2. Unit root result. 

Variables 
ADF t-stat 

@ levels 
ADF 5% critical 

@ levels 
ADF t-stat @ 
1st difference 

ADF 5% critical @ 
1st difference 

Order of 
integration Decision 

INF -3.48 -3.54 -6.01 -3.55 I (1) Stationary 
L(REM*POPR) -2.59 -2.95 -6.68 -2.95 I (1) Stationary 
LEXCHR -2.11 -3.54 -5.79 -3.56 I (1) Stationary 
LGFCF -5.95 -3.55   I (0) Stationary 
LREM -2.57 -2.95 -6.70 -2.95 I (1) Stationary 
LRGDP -2.93 -3.56 -3.74 -3.55 I (1) Stationary 
NM 0.11 -3.55 -20.0 -3.55 I (1) Stationary 
POPR -1.15 -3.55 -4.02 -3.55 I (1) Stationary 

Source:   Author’s estimation using e-views. 

 

Table 2 shows that the variables are stationary and lack a unit root, according to the ADF's unit root test results. 
In particular, the other variables became stationary after the first difference, but LGFCF remains stable at level. This 
most likely suggests both co-integration and a dynamic interplay between the variables. Pesaran, Shin, and Smith 
(2001) state that an admixture of orders of co-integration or stationarity is one of the fundamental requirements for 
the estimation of an ARDL model. Therefore, the above result's observation of the order of stationarity meets the 
need for conducting an ARDL model in this study. 
 
Table 3. Bounds test for co-integration result. 

Test Statistic Value Signif. I(0) I(1) Result 

F-statistic 5.50 10% 2.08 3  
  5% 2.39 3.38 Co-integrated 

  2.5% 2.7 3.73  

  1% 3.06 4.15  
Source:   Author’s estimation using e-views. 

 
Table 3 shows that at 5% level of significance, the F-statistic is greater than both the upper and lower bounds; 

therefore, we conclude that there is a long-run relationship among the variables. 
 

4.3. Empirical Analysis  
 
Table 4. Long-run regression result. 

Dependent Variable: LRGDP 

Variable Coefficient Std. Error T-Statistic Prob. Value 

POPR 20.9 6.43 3.26 0.02 
NM -0.36 2.02 -0.18 0.86 
LREM 3.84 1.51 2.55 0.05 
LGFCF 2.16 0.61 3.53 0.02 
L(REM*POPR) -0.83 0.24 -3.51 0.02 
C -3.62 15.1 -0.24 0.82 

R-squared 0.10  F-statistic 696. 

Adjusted R-squared 1.00  Prob (F-statistic) 0.0000 
Durbin-Watson stat 2.08    

 
Table 5. Short run and ECM regression result. 

Variable Coefficient Std. Error T-statistic Prob. Value 

D(POPR) 4.77 2.55 1.87 0.12 
D(NM) -0.45 2.23 -0.20 0.85 
D(LREM) 0.56 0.31 1.82 0.13 
D(LGFCF) -0.36 0.16 -2.25 0.07 
D(L(REM*POPR)) -0.22 0.12 -1.84 0.13 
ECM(-1) -0.55 0.08 7.36 0.00 
Source:   Author’s estimation using e-views. 

 

5. Discussion of Findings 
This study empirically explored the moderating function of population growth rate in remittances received and 

its impact on Nigeria's economic growth. According to the long-run results in Table 4, the coefficient of the log of 
the interacting term for population growth rate and remittances (LREM*POPR) is -0.83, which is statistically 
significant at the 5% level. This indicates that, all other variables being equal, a 1% increase in the interaction term 
leads to approximately an 83% decrease in the country's economic growth, and this result is statistically significant. 
This demonstrates that an increase in the population growth rate has a negative moderating effect on remittances 
received, which in turn negatively influences the country's economy. The findings have two major implications: first, 
the remittances received may not be invested in productive sectors such as health, education, and training; second, 
the country's high population may be overwhelming the inflow of remittances due to the unproductive nature of the 
majority of the population. Additionally, the study found that excessive consumption and investment in unproductive 
sectors of transferred money are negatively associated with economic progress. This finding is consistent with prior 
investigations by Nyasha and Odhiambo (2022) and Chowdhury, Dhar, and Gazi (2023). Other variables, such as 
population growth rate, remittances, and gross fixed capital formation, all had a positive and considerable long-term 
impact on economic growth. These findings conform to previous studies like Obere, Thuku, and Gachanja (2013); 



Economy, 2025, 12(2): 130-138 

136 
© 2025 by the authors; licensee Asian Online Journal Publishing Group 

 

 

Loiboo, Luvanda, and Osoro (2021); Bucevska (2022) Islam (2022); Saha (2021); Ur Rehman and Hysa (2021); Abdulai 
(2023) and Yadeta and Hunegnaw (2022). Also, the net migration showed a negative and insignificant impact on 
economic growth both in the short run and long run. 

Table 5 presents the short-run results of the moderating role of population growth on the remittance-growth 
nexus in Nigeria. It shows that population growth negatively moderates the relationship between remittances and 
economic growth, though it is statistically insignificant. 

With a negative sign, the parameter of the error correction term, which co-integrates the long and short-run 
effects, shows conformity with economic expectations, suggesting the possibility of adjusting the lags or 
disequilibrium in the long run. The error correction model has a coefficient of -0.552260, and it is statistically 
significant. This indicates that approximately 55.2% of the disequilibrium in the model will be corrected within the 
short-run period in the long run. 
 

5.1. Post Estimation Test 
Stability Test (CUSUM Test) for the Model: 
 

-8

-6

-4

-2

0

2

4

6

8

2018 2019 2020 2021 2022

CUSUM 5% Significance
 

Figure 3. CUSUM plots for stability test. 

 
Figure 3 illustrates that every coefficient in the calculated model remains constant over time within the crucial 

5% range. This stability test allows us to accept the model's output. 
 

5.2. Granger Causality Test Results 
The Granger causality test is an estimation used to determine the direction of causality between population 

growth rate (POPR), foreign remittance (LREM), and economic growth (LRGDP) in Nigeria. 
Hypothesis: 
H0: No causal relationship. 
H1: There is causal relationship. 
Decision Rule: 
Reject H0 if P-Value ≤ 0.05 level of significance. Otherwise, fail to reject the null hypothesis. 

 
Table 6. Granger causality test result. 

Null Hypothesis: Obs. F-statistic Prob. Value 

LRGDP does not granger cause POPR 32 0.84 0.51 
POPR does not granger cause LRGDP  5.77 0.00 
 LREM does not granger cause POPR 2 0.26 0.90 
POPR does not granger cause LREM  1.42 0.26 
LREM does not granger cause LRGDP 32 3.35 0.03 
LRGDP does not granger cause LREM  8.74 0.00 

Source:   Author’s estimation using e-views. 

 
From Table 6 there is no causal relationship between LRGDP and POPR, LREM and POPR, and, POPR and 

LREM, because the probability value of their null hypothesis is higher than the 5% level of significance. Whereas, 
there is a unidirectional causality flowing from POPR to LRGDP and also a bidirectional causality running from 
LREM to LRGDP and from LRGDP to LREM. This conforms to the results earlier estimated.  

 

6. Conclusion and Recommendation 
According to the study's conclusions, the population growth rate has a negative long-term impact on remittances. 

The causation result revealed a one-way causality from population increase to economic growth, as well as a two-
way causality between remittances and economic growth. It consequently proposes that the government and 
individuals who receive these remittances invest them in more productive sectors such as health, education, and 
training so that they have a positive impact on the country's economic progress. They should likewise establish 



Economy, 2025, 12(2): 130-138 

137 
© 2025 by the authors; licensee Asian Online Journal Publishing Group 

 

 

robust monitoring and evaluation mechanisms to track progress and make necessary adjustments to ensure long-
term economic stability and growth. 
 

References 
Abdulai, A. M. (2023). The impact of remittances on economic growth in Ghana: An ARDL bound test approach. Cogent Economics & Finance, 

11(2), 2243189. https://doi.org/10.1080/23322039.2023.2243189 
Adeleye, O. K., Ologunwa, O. P., & Ogunjobi, V. O. (2021). Foreign direct investment, remittances and economic growth in Nigeria: Do these 

inflows stimulate growth. Global Journal of Arts, Humanities and Social Sciences, 9(2), 72-82. 
https://doi.org/10.13140/RG.2.2.28305.51048 

Adeseye, A. (2021). The effect of migrants remittance on economy growth in Nigeria: An empirical study. Open Journal of Political Science, 
11(01), 99–122. https://doi.org/10.4236/ojps.2021.111007 

Alechenu, B. E. (2021). Economic impact of diaspora remittance on Nigerian economy. London Journal of Social Sciences(1), 79–87. 
https://doi.org/10.31039/ljss.2021.1.41 

Amin, M., Shahbaz, M., & Mahalik, M. K. (2020). Financial development, remittances, and economic growth: Evidence from Asian economies. 
Economic Modelling, 91, 1–12.  

Asiamah, M., Ofori, D., & Afful, J. (2019). Analysis of the determinants of foreign direct investment in Ghana. Journal of Asian Business and 
Economic Studies, 26(3), 1–16.  

Azam, M. (2015). The role of migrant workers' remittances in fostering economic growth: The four Asian developing countries' experiences. 
International Journal of Social Economics, 42(8), 690–705. https://doi.org/10.1108/IJSE-11-2013-0255 

Bucevska, V. (2022). Impact of remittances on economic growth: Empirical evidence from South-East European countries. South East European 
Journal of Economics and Business, 17(1), 79-94. https://doi.org/10.2478/jeb-2022-0006 

Chowdhury, E. K., Dhar, B. K., & Gazi, M. A. I. (2023). Impact of remittance on economic progress: evidence from low-income Asian Frontier 
countries. Journal of the Knowledge Economy, 14(1), 382-407. https://doi.org/10.1007/s13132-022-00898-y 

Depken, C. A., Nikšić Radić, M., & Paleka, H. (2021). Causality between foreign remittance and economic growth: Empirical evidence from 
Croatia. Sustainability, 13(21), 12201. https://doi.org/10.3390/su132112201 

Didia, D., & Tahir, S. (2022). Enhancing economic growth and government revenue generation in Nigeria: The role of diaspora remittances. 
The Review of Black Political Economy, 49(2), 175-202. https://doi.org/10.1177/00346446211025647 

Dutta, U. P., & Saikia, B. (2024). Remittances and economic growth: empirical analysis from a panel of selected Asian Nations. Millennial Asia, 
15(1), 5-23. https://doi.org/10.1177/09763996221086745 

Effiong, U. E. (2022). Population-economic growth nexus in Nigeria and Poland: Does quality or quantity matter? International Journal of 
Academic Pedagogical Research, 06(07), 44–70.  

Efuntade, O. O., & Efuntade, A. O. (2020). Effect of population growth on economic growth in Nigeria. International Journal of Business and 
Finance Management Research, 8(4), 48–55.  

Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 
251–276. https://doi.org/10.2307/1913236 

Fayissa, B., & Nsiah, C. (2010). The impact of remittances on economic growth and development in Africa. The American Economist, 55(2), 92–
103.  

Gniniguè, M., & Ali, E. (2021). Migrant remittances and economic growth in ECOWAS countries: Does digitalization matter? The European 
Journal of Development Research, 34(5), 2517–2542. https://doi.org/10.1057/s41287-021-00461-6 

Golder, U., Rumaly, N., Hossain, M. K., & Nigar, M. (2023). Financial progress, inward remittances, and economic growth in Bangladesh: Is 
the nexus asymmetric? Heliyon, 9(3), e14454. https://doi.org/10.1016/j.heliyon.2023.e14454 

Headey, D. D., & Hodge, A. (2009). The effect of population growth on economic growth: A meta‐regression analysis of the macroeconomic 
literature. Population and Development Review, 2, 221–248. https://doi.org/10.1111/j.1728-4457.2009.00274.x 

Hossain, M. S. (2019). Investigating the connections between China's economic growth, use of renewable energy, and research and development 

concerning CO₂ emissions: An ARDL bound testing approach. Environmental Science and Pollution Research, 26(3), 2802–2814.  
Imran, M., Wu, M., Yu, R., Zhong, Y., & Moon, H. C. (2021). Nexus among foreign remittances and economic growth indicators in South 

Asian Countries: An empirical analysis. Korea International Trade Research Institute, 17(1), 263–275. 
https://doi.org/10.16980/jitc.17.1.202102.263 

Işık, C. (2013). The effects of foreign direct investment on economic growth: A case study of Turkey using ARDL approach. International 
Journal of Economics and Financial Issues, 3(3), 493–502.  

Islam, M. S. (2022). Do personal remittances influence economic growth in South Asia? A panel analysis. Review of Development Economics, 
26(1), 242-258. https://doi.org/10.1111/rode.12842 

Jackman, M., Moore, W., & Craigwell, R. (2011). Remittances and economic growth in developing countries. International Journal of Development 
Issues, 10(2), 132–151.  

Jayaraman, T. K., Choong, C.-K., & Chand, P. (2016). Do foreign aid and remittance inflows hurt competitiveness of exports of Pacific Island 
countries? An empirical study of Fiji. Journal of Economic Development, 41(2), 111–125. 
https://doi.org/10.35866/caujed.2016.41.2.005 

Kajtazi, K., & Fetai, B. (2022). Does the remittance generate economic growth in the South east European countries? Scientific Annals of 
Economics and Business, 69(1), 57-67. https://doi.org/10.47743/saeb-2022-0004 

Korsah, M. A., Adjei-Mensah, M., & Osei-Bonsu, E. (2022). LED policy to empower and create jobs to boost Ghana's growth. Ghana: Ministry of 
Local Government, Rural Development and Decentralization. 

Kudaisi, B. V., Ojeyinka, T. A., & Osinubi, T. T. (2022). Financial liberalization, remittances and economic growth in Nigeria (1990–2018). 
Journal of Economic and Administrative Sciences, 38(4), 562-580. https://doi.org/10.1108/JEAS-09-2020-0164 

Kuhe, A. (2019). The impact of population growth on economic growth and development in Nigeria: An econometric analysis. Nigeria: ResearchGate. 
Loiboo, D., Luvanda, E., & Osoro, N. (2021). Population and economic growth in Tanzania. Tanzania Journal for Population studies and 

Development, 28(2), 20-42.  
Menegaki, A. N. (2019). Renewable energy, growth, and employment: The case of Europe. Energy Economics, 81, 1–15.  
Mohamed Aslam, A. L., & Alibuhtto, M. C. (2023). Workers' remittances and economic growth: new evidence from an ARDL bounds 

cointegration approach for Sri Lanka. Journal of Economic and Administrative Sciences, 41(2), 825–843. https://doi.org/10.1108/JEAS-
05-2022-0132 

Muhammad, F., Özdeşer, H., & Adedeji, A. N. (2024). Analysis of the Effects of FDI and remittance on economic growth: Empirical evidence 
from Nigeria. Journal of Arid Zone Economy, 3(1), 60-82.  

Nyasha, S., & Odhiambo, N. M. (2022). The impact of remittances on economic growth: Empirical evidence from South Africa. International 
Journal of Trade and Global Markets, 15(2), 254-272. https://doi.org/10.1504/IJTGM.2022.121457 

Obere, A., Thuku, G. K., & Gachanja, P. (2013). The impact of population change on economic growth in Kenya. International Journal of 
Economics and Management Sciences, 2(6), 43–60.  

Odhiambo, J. (2019). Relationship between selected community capitals and level of parental participation in primary education in Migori County. Kenya: 
DSpace Home. 

Odugbesan, J. A., Sunday, T. A., & Olowu, G. (2021). Asymmetric effect of financial development and remittance on economic growth in MINT 
economies: An application of panel NARDL. Future Business Journal, 7(1), 39. https://doi.org/10.1186/s43093-021-00085-6 

Ogbaro, E. O., Sanni, O., Adeoye, J. O., Akintaro, A. A., & Eseyin, O. S. (2023). Accounting for the role of financial development in the nexus 
between remittances and economic growth in Nigeria. International Research Journal of Economics and Management Studies, 2(3), 154–
166. https://doi.org/10.56472/25835238/IRJEMS-V2I3P121 

Okorie, G. C., Nwabufoh, E., & Oriaku, E. C. (2022). Remittances and economic growth of Nigeria. GOUni Journal of Faculty of Management 
and Social Sciences, 9(1), 168-175.  

https://doi.org/10.1080/23322039.2023.2243189
https://doi.org/10.13140/RG.2.2.28305.51048
https://doi.org/10.4236/ojps.2021.111007
https://doi.org/10.31039/ljss.2021.1.41
https://doi.org/10.1108/IJSE-11-2013-0255
https://doi.org/10.2478/jeb-2022-0006
https://doi.org/10.1007/s13132-022-00898-y
https://doi.org/10.3390/su132112201
https://doi.org/10.1177/00346446211025647
https://doi.org/10.1177/09763996221086745
https://doi.org/10.2307/1913236
https://doi.org/10.1057/s41287-021-00461-6
https://doi.org/10.1016/j.heliyon.2023.e14454
https://doi.org/10.1111/j.1728-4457.2009.00274.x
https://doi.org/10.16980/jitc.17.1.202102.263
https://doi.org/10.1111/rode.12842
https://doi.org/10.35866/caujed.2016.41.2.005
https://doi.org/10.47743/saeb-2022-0004
https://doi.org/10.1108/JEAS-09-2020-0164
https://doi.org/10.1108/JEAS-05-2022-0132
https://doi.org/10.1108/JEAS-05-2022-0132
https://doi.org/10.1504/IJTGM.2022.121457
https://doi.org/10.1186/s43093-021-00085-6
https://doi.org/10.56472/25835238/IRJEMS-V2I3P121


Economy, 2025, 12(2): 130-138 

138 
© 2025 by the authors; licensee Asian Online Journal Publishing Group 

 

 

Omoniyi, O. B., & Owoeye, T. (2024). Effect of remittance inflow on economic growth of Nigeria. Journal of Applied And Theoretical Social 
Sciences, 6(1), 74-87. https://doi.org/10.37241/jatss.2024.104 

Orji, A., Ogbuabor, J. E., Iwuagwu, C., & Anthony-Orji, O. I. (2020). Empirical analysis of the impact of population increase on the economic 
growth of Africa’s most populous country. Socio-Economic Research Bulletin, 2(73), 27–45. 
https://doi.org/10.33987/vsed.2(73).2020.27-45 

Osei-Gyebi, S., Opoku, A., Lipede, M. O., & Kountchou, L. K. (2023). The effect of remittance inflow on savings in Nigeria: The role of financial 
inclusion. Cogent Social Sciences, 9(1), 2220599. https://doi.org/10.1080/23311886.2023.2220599 

Oyegoke, E. O., & Ebele, A. (2023). Labour emigration, remittances and economic development: An empirical analysis. African Journal of Social 
Issues, 5(1), 239–259. https://doi.org/10.4314/ajosi.v5i1.16 

Pesaran, H. M., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of long run relationships. Journal of Applied 
Econometrics, 16(3), 289-326. https://doi.org/10.1002/jae.616 

Peterson, E. W. F. (2017). The role of population in economic growth. SAGE Open, 7(4), 215824401773609. 
https://doi.org/10.1177/2158244017736094 

Qutb, R. (2022). Migrants’ remittances and economic growth in Egypt: An empirical analysis from 1980 to 2017. Review of Economics and 
Political Science, 7(3), 154–176. https://doi.org/10.1108/REPS-10-2018-0011 

Ramanayake, S. S., & Wijetunga, C. S. (2018). Sri Lanka’s labour migration trends, remittances and economic growth. South Asia Research, 
38(3_suppl), 61S81S. https://doi.org/10.1177/0262728018792088 

Raphael, A., Peter, O. I., & Kenneth, I. (2024). The effect of population dynamics on economic growth performance in Nigeria. GPH-
International Journal of Social Science and Humanities Research, 7(04), 75-88. https://doi.org/10.5281/zenodo.11164027 

Ratha, D. (2003). Workers' remittances: An important and stable source of external development finance. Washington, D.C: World Bank. 
Ratha, D., Mohapatra, S., & Silwal, A. (2011). Migration and remittances factbook 2011. Washington, D.C: World Bank. 
Ribadu, M. (2023). Remittance flows: Examining the frequency and relevance in Nigeria. Sapientia Global Journal of Arts, Humanities and 

Development Studies, 6, 2695-2327.  
Saha, S. K. (2021). The impact of remittance on economic growth in Bangladesh. Scholars Journal of Arts, Humanities and Social Sciences, 9(9), 

462-470. https://doi.org/10.36347/sjahss.2021.v09i09.013 
Sam, C., Nyongesa, W., & Ouma, A. (2019). The relationship between foreign remittances, financial development, and economic growth in 

Sub-Saharan Africa. African Development Review, 31(4), 410–423.  
Sghaier, I. M. (2021). Remittances and economic growth in MENA countries: The role of financial development. Economic Alternatives, 1, 43-

59. https://doi.org/10.37075/EA.2021.1.03 
Siifa, B., Teniola, B. B., & Zayyad, M. A. (2023). Statistical analysis of effect of population on economic growth in Uganda (2000-2020). 

Technology and Investment, 14(2), 101–118. https://doi.org/10.4236/ti.2023.142006 
Ur Rehman, N., & Hysa, E. (2021). The effect of financial development and remittances on economic growth. Cogent Economics & Finance, 9(1), 

1932060. https://doi.org/10.1080/23322039.2021.1932060 
Wang, X., Ali, Z., Khan, S. T., Tiwari, C. K., & Bhat, M. A. (2021). Unveiling the drivers of climate change: The impact of economic indicators, 

renewable energy consumption, and human development through a panel ARDL approach. Discover Sustainability, 6(691), 1–15.  
World Bank. (2022). World development indicators. Washington, D.C: World Bank. 
Yadeta, D. B., & Hunegnaw, F. B. (2022). Effect of international remittance on economic growth: Empirical evidence from Ethiopia. Journal of 

International Migration and Integration, 23(3), 383-402. https://doi.org/10.1007/s12134-021-00833-1 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Asian Online Journal Publishing Group is not responsible or answerable for any loss, damage or liability, etc. caused in relation to/arising out of the use of the content. 
Any queries should be directed to the corresponding author of the article. 

 

https://doi.org/10.37241/jatss.2024.104
https://doi.org/10.33987/vsed.2(73).2020.27-45
https://doi.org/10.1080/23311886.2023.2220599
https://doi.org/10.4314/ajosi.v5i1.16
https://doi.org/10.1002/jae.616
https://doi.org/10.1177/2158244017736094
https://doi.org/10.1108/REPS-10-2018-0011
https://doi.org/10.1177/0262728018792088
https://doi.org/10.5281/zenodo.11164027
https://doi.org/10.36347/sjahss.2021.v09i09.013
https://doi.org/10.37075/EA.2021.1.03
https://doi.org/10.4236/ti.2023.142006
https://doi.org/10.1080/23322039.2021.1932060
https://doi.org/10.1007/s12134-021-00833-1

