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. 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