Remittances and FDI: Drivers of Employment in the Economic Community of West African States

Abstract

Unemployment and weak economic productivity are significant global issues, particularly in West Africa. Recently, through diverse mechanisms, remittances and foreign direct investment (FDI) have been sources of foreign capital flow that have positively influenced many less developed economies, including ECOWAS (ECOWAS stands for Economic Community of West African States). Nevertheless, these financial flows have exhibited significant inconsistencies, primarily resulting from economic downturns in migrants’ destination countries, with remarkable implications for beneficiary economies. This study, therefore, examines the effect of remittances and FDI on employment in ECOWAS. Specifically, the study assesses the effects of the inflow of remittances and FDI on employment using panel dynamic ordinary least squares (PDOLS) and also investigates the shock effects of remittances and FDI by employing Panel Vector Error Correction (PVECM), which involves variance decomposition. The results show that foreign direct investment (FDI) positively and significantly affects employment. Other variables that show a significant relationship with employment are wage rate, education expenditure, and interest rate. The variance decomposition result revealed that external shocks on remittances and FDI have short- and long-term effects on employment. The above findings imply that foreign direct investment has a far-reaching positive impact on the economy-wide management of the West African sub-region and thus calls for relevant policy options.

1. Introduction

The relevance of remittances and foreign direct investment for the economic progress of developed and emerging economies is fundamental. The importance of foreign direct investment and personal remittance has been of great concern in Africa. Such funds have aided many economies in moving forward, raising their gross domestic product (GDP), living standards, advancement in technology, and development of human capital. Since the early 1980s, FDI has witnessed exceptional expansion, thereby enhancing the attractiveness of the global economy (Zameer et al., 2020). There is a growing fact that foreign direct investment (FDI) is an important economic growth driver in most developing countries, with ECOWAS member states inclusive (Wang et al., 2021; Epor et al., 2024). Remittances, FDI, and government development financial flows may all be significant factors that will influence the growth of most developing economies, including ECOWAS. Although remittances are primarily used for non-investment purposes such as food, shelter, and education, they have been reported to spur new investments as a source of finance. Several studies have established that remittances are crucial in establishing new businesses (Akpa et al., 2020; Ajide & Osinubi, 2022; Evans, 2023).

The increase in foreign direct investment (FDI) arises from global economic development, characterized by the integration of domestic and international economies. Through FDI, foreign investors can create business enterprises by entering domestic markets and enhancing them with much-needed capital, thereby fostering the economic development of host economies. This integration enables investors to gain from lower labour costs and comparatively higher profits on invested capital. Consequently, the presence of FDI in developing economies, like those within ECOWAS, can significantly stir economic growth. The availability of FDI generates a domain for keener rivalry between local and foreign companies. Given this, local companies are keener on utilizing their inadequate resources more judiciously and embracing modern technology (Mawutor et al., 2023; Abdulkarim, 2023). It is thus established that introducing foreign direct investment in an economy is evidence that the country’s businesses are performing favorably due to the creation of more goods and services, thereby boosting GDP growth (Hayat, 2018; ECB, 2021).

By the end of 2022, the economy of ECOWAS increased by 3.9%, down from 4.4% which was recorded in 2021. In like manner, Sub-Saharan Africa’s (SSA) growth was unenthusiastic, with economic activity rising by 3.9% in 2022, compared to 4.8% in 2021. The slowdown in economic growth reflected the reduced increase in the various economic segments of the continent, with ECOWAS growing by 3.9% in 2022, down from 4.4% in 2021. Despite significant economic growth, this has not yet resulted in meaningful advancements in the employment plight. The labour force in Western Africa is projected to grow from 133 million in 2020 to about 176 million in 2030, or almost 33% in 10 years. Another principal indicator is the degree of non-formality and youth joblessness affecting the job market in the ECOWAS sub-region. As indicated by the ILO approximations, in 2019, the youth rate of unemployment was approximated to be higher than 8% in eight ECOWAS nations, with Cabo Verde having the highest (28%), Mali (14.7%), and Nigeria (14%). It also appears clear that most employment is non-formal in overall and non-agricultural sectors (United Nations, 2019).

On average, unemployment across ECOWAS is projected to rise marginally to 4.42% in 2023, according to the projected drop in revenues and living standards. Generally, close to 38% of employed persons in the Economic Community of West African States (ECOWAS) sub-region are exceedingly impoverished, subsisting on less than 1.90 US dollars a day, and about 63% are impoverished, surviving on less than 3.10 US dollars (ECB, 2021). Hence, inclusive of other things, to the great extent of impoverishment, the economies of this sub-region are often vulnerable to insecurity, social tensions, and political unrest. Most economies, ECOWAS member states, are generally confronted by resource disparity disorder. This is because capital to finance wide-range development programs falls short of the expected quantity and quality to adequately finance broad-based development initiatives. In the past decades, a continuous drop in foreign aid inflows to the ECOWAS sub-region has also led to an investment gap for employment-boosting projects. This problem has weakened the ability of the government to carry out its major role of improving social welfare and ensuring security for its citizenry. Also, most West African countries have been witnessing low wages, high levels of unemployment, and heavy dependence on the non-formal sector due to the challenges of the investment shortfall (United Nations, 2019; World Bank, 2020). Hence, it becomes mandatory for the government to set up alternatives for augmenting this gap as it could initiate distortions and a lack of stability in policies put in place by the government.

Extensive studies have been carried out on economic catalysts in ECOWAS economies, focusing on areas such as the relationship between economic growth and foreign direct investment (FDI) (Hayat, 2018; Orji et al., 2021; Kukaj et al., 2022); the influence of foreign remittances on the growth of the economy (Adjei et al., 2020; Abanikanda & Akinbobola, 2023); the influence of remittances on employment (Cilliers, 2021; African Development Bank, 2022; Habib, 2023); and the effects of FDI on employment (Aderemi et al., 2022). While these studies have investigated the individual relationships among these variables, none have comprehensively examined their combined impact on labour employment within the ECOWAS region, leaving a gap in the literature. This study bridges that gap by investigating the joint effects of remittance inflows and FDI on labour employment in ECOWAS member states. The findings are expected to provide valuable insights for researchers, policymakers, and migrants and their families, as well as social workers and non-governmental organisations with a vested interest in migration and investment dynamics. Specifically, the study shows how remittance flows can be effectively channelled towards pressing developmental and investment needs to foster sustainable economic and labour market outcomes. Additionally, the results will offer actionable recommendations to government agencies and ministries involved in migration policy management and the strategic allocation of resources to address development challenges across ECOWAS member states. To attain the objective of this study, the research question addressed is as follows: What is the effect of remittance inflows and foreign direct investment on employment, and how do their shock impacts influence employment in ECOWAS during the study period?

2. Literature Review

2.1. Neoclassical Theory of Employment

This study hinges on the Neoclassical Theory of Employment, which is the most famous international migration theory. The Neoclassical Employment Theory is a fundamental economic theory that originated in the later part of the 18th and early 19th centuries, with notable contributions from scholars like Adam Smith, David Ricardo, and John Stuart Mill. The postulation is rooted in the reliance on the self-regulating nature of markets and the efficiency of free-market mechanisms. This theory posits that the emigration of labour emanates from imbalances that exist in the job market and dissimilarities between the supply and demand for labour (Lewis, 1954; Todaro, 1976). The postulation emphasizes that people move from lesser-paid zones to other locations having improved earnings, improved amenities, and other socio-occupational gains. People relocate for motivations which are largely along the line of remittances and other earnings from overseas. This is an incentive for work, particularly for people in growing economies with no marginal labour output and a very large population. These receipts are useful other income sources for contributing families; the remittance inflow stimulates the level of production in the emigrants’ home nation. The immediate family of the migrants is the direct recipient of remittance at the lower-class level, and the economy generally also is in a position to gain from investments established by the remittance-collecting families (Flahaux & De Haas, 2016; Wickramasinghe & Wijitapure, 2016). The neoclassical theory was criticized for being based mainly on economic interests and impracticable, depicting developed countries as willing migrant recipients (Prakash, 2009; Kurekova, 2011).

A lot of literature supports the notion that FDI is beneficial to host economies. Developing countries are thus encouraged to acquire FDI and portfolio equity inflows to bring about long-term growth prospects and are advised not to limit themselves to domestic savings alone (for example Moura & Forte, 2013; World Bank, 2017; Korsah et al., 2022). Many governments, therefore, have encouraged inflows of FDI and tried as much as they can to provide incentives (Tocar, 2018; Emako et al., 2020). The general belief is that the positives outweigh the negatives when developing countries decide on issues that relate to FDI. In addition, in spite of contrasting controversies, the need for FDI is gradually gaining popularity. Country-level as well as cross-border studies have put forward varied results on FDI’s effects on host countries and cannot be disseminated from one nation to another or one region to another. This impact has a lot to do with many factors like the microeconomic context, political strength, and several other factors (Moura & Forte, 2013). Foreign direct investment benefits in the host country also include the improvement of rivalling business contributions to foreign trade and advancement in enterprise development (Kurtishi-Kastrati, 2013; Alfaro, 2017; Tasinda et al., 2022). Aside from economic gains, FDI benefits the host nation by ameliorating the environment and social situation through initiating eco-innovation as well as guiding the host country to more socially dependable corporate guidelines (Tarasa, 2023; Phuong, 2021). These gains add to economic growth, which results in the alleviation of poverty in these host nations (Alfaro, 2017). In terms of accuracy, the economic impacts of FDI are not an easy task since gains vary from region to region, and country to country, and are therefore, not easy to separate and quantify.

2.2. Remittances and Employment

A study of some selected West African countries was conducted by Saidu and Salisu (2020). They analyzed the long-period relationship of remittances and economic growth in some chosen Sub-Saharan African (SSA) countries including Nigeria, Ghana, Kenya, and Senegal, employing annual panel data for the period spanning 1980–2018. The research used LLC and IPS panel unit root tests, Pedroni and Kao cointegration tests to explore the basic and causal link between variables. From the long-period cointegrating parameter approximations, the findings reveal that an increase in remittances, foreign direct investment, domestic investment, and trade openness boosts the economic growth of SSA countries.

Oyegoke and Amali (2022) empirically analyzed the effects of foreign job emigration and remittances on economic development in Nigeria, employing yearly time series data covering 1977–2021. The authors applied ordinary least squares (OLS) to estimate the model. Their results showed a notable positive effect on economic development in Nigeria. Hence, they concluded that job migration is a substitute source of money in Nigeria that meaningfully improves economic development.

Xia et al. (2022) conducted a study on 10 remittance recipient countries. The motivation of the study is to assess the role of remittances in the process of human capital development in the top 10 remittance-receiving countries from 1980 to 2019. The study utilised symmetric and asymmetric estimations to assess the effects of remittances, FDI, and gross capital formation on the development of human capital. The study reported a positive and statistically significant association between remittances and human capital development; a similar association was revealed for FDI and gross capital formation. Moreover, asymmetric shocks in remittances and FDI also exposed positive and statistically significant human capital development.

The study carried out by Nasim (2019) investigates the role of remittances on capital formation in SAARC countries by examining data spanning 38 years. Findings from the study revealed that remittance inflows in SAARC countries do not accumulate domestic capital, particularly in the long run.

A pessimistic view, however, contends that remittances to developing economies could not spur economic growth because they are mainly used for basic consumption needs rather than productive outlay. Remittances could also hinder economic growth when they lower the incentive of recipients to work. Conversely, a hopeful view contends that remittances could boost economic growth directly through savings and investment in tangible and human (education and health) assets, and indirectly through consumption regulation and strengthening financial markets (Keho, 2024). Empirically, a very large body of literature has assessed the growth effect of remittances in individual countries or groups of countries. The results have been blended, ranging from pessimistic effects to optimistic effects.

2.3. Foreign Direct Investment (FDI) and Employment

A lot of studies have been conducted in relation to the FDI and employment link over time. Although researchers have conducted studies on the impact of foreign direct investment on employment generation in developing countries, not many of such studies have been conducted on ECOWAS countries. For example, Adelowokan et al. (2023) estimated the causal relationship between Employment Generation, FDI inflows, and poverty reduction in the ECOWAS Region using pairwise Dumitrescu Hurlin Panel Causality Tests. The findings from the two-way association state that poverty reduction in terms of human capacity development is a vital variable causing employment creation and FDI inflows in the ECOWAS sub-region in the last three decades. Aderemi et al. (2019) applied Panel Cointegration alongside Pairwise Dumitrescu Hurlin Panel Causality Tests in assessing how FDI and economic growth were linked in seven developing economies between 1990 and 2017. Their research validated the presence of a long-term convergence among the pertinent variables of interest.

Employing 43 African nations between 2002 and 2018, Poumie and Claude (2021) applied the augmented mean group (AMG), dynamic ordinary least square (DOLS), and the common correlated effects means group (CCEMG) to assess how foreign capitals like FDI and migrant remittances impact both total employment and sectoral job generation. The findings of the research showed that FDI and migrant remittances had a direct impact on total employment. Nevertheless, only FDI had both direct and significant influence on job creation in the industry, agriculture, and service segments of the African nations. In Nigeria, Osabohien et al. (2020) estimated the level of employment due to inflows of FDI from 1985 to 2017, applying the fully modified ordinary least squares (FMOLS). Their results showed that FDI contributed meaningfully to employment in the country.

From the studies reviewed, it could be stated that despite the fact that FDI has a significantly strong impact on economies in this present age, yet not many studies exist that have assessed this effect on employment within the West Africa sub-region in recent times. In addition, it is useful to point out that FDI and employment creation are ongoing concerns in developing nations.

3. Definition and Measurement of Variables

To assess the effect of remittances and foreign direct investment on employment, the dependent variable is employment. It typically represents the number of people employed in a given economy. The main independent variables are remittance inflow and foreign direct investment. Other variables which can also explain outcomes in the dependent variables are wage, gross domestic product (GDP), and human capital (proxied as expenditure on education). Others include the exchange rate and interest rate.

Remittances are money transfers from workers abroad to their families and friends in their original countries. They can influence employment in various ways. On one hand, remittances can raise household income, potentially reducing the need for household members to seek formal employment. On the other hand, they can stimulate local economies and create job opportunities (Dash, 2022). Remittances can have a positive impact on employment if they stimulate local economic activity, or a negative impact if they reduce the necessity for household members to work. Remittances can impact output per capita by increasing the income of households, which can raise consumption and potentially lead to investment in local businesses. However, if remittances are not invested in a productive manner, their impact on output per capita may be limited. Remittances might impact output per capita positively if they cause increased consumption and investment in productive activities. The impact may vary based on how these funds are used in the local economy.

FDI involves investment by international establishments in the local economy of another nation, often resulting in the creation of new businesses or the expansion of existing ones. This is capable of generating new job opportunities and improvements in employment levels. It can lead to increased capital stock, technological advancement, and enhanced productivity. This, in turn, can contribute to higher output per capita (Azam & Feng, 2021; Kulu et al., 2021; Mawutor et al., 2023). FDI is generally anticipated to show positive effects on employment as it creates new job opportunities and stimulates economic growth. FDI is also anticipated to have a positive effect on output per capita by raising capital formation and technological transfer, thereby enhancing economic productivity.

Wages refer to the income earned by workers. Higher wages might increase employment if they make jobs more attractive. On the other hand, they might reduce the incentive for workers and cause them to back out of the job market. Conversely, higher wages have the potential to reduce employment if they lead to higher costs for employers, thus making them reduce hiring (Cammeraat et al., 2021; Fontanari, 2024). The impact of wages on employment could be complex and context-dependent. Higher wages might cause more workers to be attracted to the labour market but could also reduce employment if they cause higher production costs for employers.

GDP estimates the overall economic output of a nation. A rising GDP is an indication of economic expansion and can lead to increased demand for labour and higher employment levels (Blanchard & Katz, 2020; Mankiw, 2021). GDP is generally anticipated to have a positive effect on employment, as economic growth usually creates more job opportunities. Human capital (proxied as expenditure on education in the study) measures the education, skills, and health of the workforce. Higher human capital generally implies a more skilled and productive workforce, which is capable of enhancing employment prospects and job creation. Higher human capital generally leads to increased productivity and innovation, which can boost output per capita by enhancing labour efficiency and economic productivity (Bakhytgu et al., 2025).

A higher human capital is expected to positively affect employment by improving the overall productivity and employability of the workforce. It is also expected to positively affect output per capita by improving worker productivity and economic output.

Exchange rates have the tendency to boost employment through their effect on trade and investment. A depreciating currency might enhance export-oriented industries, thus creating jobs, while the opposite effect may hold for an appreciating currency. A depreciated currency has the tendency to make exports cheaper and imports more expensive, potentially boosting domestic production and output per capita. Conversely, a strong currency might have the opposite effect (Alagidede & Ibrahim, 2017; Vasani et al., 2019; Ribeiro et al., 2019).

The effect of the exchange rate on employment can vary; a weaker currency might raise employment in export-oriented sectors, while a stronger currency might reduce employment in those sectors. The influence of the exchange rate on output per capita is likely to be positive if a weaker currency boosts export competitiveness and domestic production but could be negative if it leads to higher import costs and reduced consumption.

Interest rates usually affect the cost of borrowing and also influence investment and consumption. Lower interest rates can stimulate investment and consumption, thereby potentially increasing employment. Conversely, higher rates of interest might dampen economic activity and reduce employment. Since lower rates of interest spur investment by lowering borrowing costs, they can result in higher capital formation and productivity, which can raise output per capita. However, higher rates of interest may have the reverse effect by dampening investment and consumption (Lukasz & Lawrence, 2020; Eggertsson et al., 2021).

Lower interest rates are anticipated to have a positive influence on employment by encouraging investment and the growth of the economy, while higher interest rates could have a negative impact. Lower interest rates are also anticipated to have a positive effect on output per capita by encouraging investment and economic growth, whereas higher interest rates might negatively affect output per capita as they reduce investment.

As shown in

Table 1. Variable symbols, Definition and Units of Measurement.

Variable Symbol	Definition	Unit of Measurement	Expected Sign	A Priori	Source
LAB	Labour employment	No. of hours worked/period	+	It is expected to impact the economy positively	World Bank (2022), World Development indicators
FDI	Foreign direct investment	% of GDP in each country	+	It is expected to impact labour employment and labour productivity positively, as it creates employment opportunities	World Bank (2022), World Development indicators
RMM	Remittances inflow	Remittances received as a % of GDP	+/−	Remittances might impact labour employment and labour productivity positively or negatively. The impact depends on how the funds are used in the local economy	World Bank (2022), World Development indicators
WAG	Wage	Labour/hour	-	It is expected to have a negative relationship with labour employment	World Bank (2022), World Development indicators
GDP	Gross domestic product	USD	+	It is expected to have a positive effect	World Bank (2022), World Development indicators
HUC	Human capital formation (proxied as expenditure on schooling)	USD	+	Positive relationship with employment	World Bank (2022), World Development indicators
EXR	Exchange rate	LCU per USD	+/−	Positive if a weaker currency boosts export competitiveness; Negative if it causes higher import costs.	World Bank (2022), World Development indicators
INR	Interest rate	%	+/−	A lower interest rate is expected to have positive impacts.	World Bank (2022), World Development indicators

Source: Authors’ Perception.

, the variable symbols, their definitions, and units of measurement of the dependent and independent variables are summarized. Also incorporated are the expected signs of variables, their a priori expectations, and the sources of data utilized for analysis.

4. Methodology

Model Specification and Justification

The study investigates the effects that remittances and foreign direct investment (FDI) have on employment and was examined in all the fifteen nations that make up ECOWAS, namely Benin, Burkina Faso, Cabo Verde, Côte d’Ivoire, the Gambia, Ghana, Guinea, and Guinea-Bissau. Others are Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone and Togo. The model is hereby expressed following the study by Babasanya (2018) with some adjustments in an operational form as follows:

LAB_it = f(FDI_it, RMM_it,WAG_it, GDP_it, HUC_it, EXC_it, INT_it)

(1)

In Equation (1), LAB is employment, FDI is foreign direct investment, RMM is remittance, WAG is wage rate, GDP is the gross domestic product at a constant price, HUC is human capital, EXC is the exchange rate, and INT is the interest rate.

Rewriting Equation (1) explicitly as follows:

LAB_it = β₀ + β₁FDI_it + β₂RMM_it + β₃WAG_it + β₄GDP_it + β₅HUC_it + β₆EXC_it + β₇INT_it + μ_it

(2)

The Vector Error Correction model can be stated as

EMP_t = β₀ + β₁REM₁ + β₂FDI₁ + ⴎ₁

(3)

This can further be expressed as

$$\begin{gathered} \Delta {\mathrm{EMP}}_t={ꭤ}_1({\mathrm{EMP}}_{t-1}-{\mathsf{\beta }}_0-{\mathsf{\beta }}_1{\mathrm{RMM}}_{t-1}-{\mathsf{\beta }}_2 {\mathrm{FDI}}_{t-1})+{\sum }_{i=1}^{n-1}\mathrm{ꝩ}11,\Delta {\mathrm{E}\mathrm{M}P}_{t-1}+{\sum }_{i=1}^{n-1}\mathrm{ꝩ}12,\Delta {\mathrm{R}\mathrm{M}\mathrm{M}}_{t-1}+ \\ {\sum }_{i=1}^{n-1}\mathrm{ꝩ}13,\Delta {\mathrm{F}\mathrm{D}\mathrm{I}}_{t-1}+{\mathrm{ⴎ}}_{it} \end{gathered}$$

(4)

$$\begin{gathered} \Delta {\mathrm{R}\mathrm{M}\mathrm{M}}_t={ꭤ}_2({\mathrm{EMP}}_{t-1}-{\mathsf{\beta }}_0-{\mathsf{\beta }}_1{\mathrm{RMM}}_{t-1}-{\mathsf{\beta }}_2 {\mathrm{FDI}}_{t-1})+{\sum }_{i=1}^{n-1}\mathrm{ꝩ}21,\Delta {\mathrm{E}\mathrm{M}\mathrm{P}}_{t-1}+{\sum }_{i=1}^{n-1}\mathrm{ꝩ}22,\Delta {\mathrm{R}\mathrm{M}\mathrm{M}}_{t-1}+ \\ {\sum }_{i=1}^{n-1}\mathrm{ꝩ}23,\Delta {\mathrm{F}\mathrm{D}\mathrm{I}}_{t-1}+{\mathrm{ⴎ}}_{2t} \end{gathered}$$

(5)

$$\begin{gathered} \Delta {FDI}_t={ꭤ}_3({\mathrm{EMP}}_{t-1}-{\mathsf{\beta }}_0-{\mathsf{\beta }}_1{\mathrm{RMM}}_{t-1}-{\mathsf{\beta }}_2 {\mathrm{FDI}}_{t-1})+{\sum }_{i=1}^{n-1}\mathrm{ꝩ}31,\Delta {\mathrm{E}\mathrm{M}\mathrm{P}}_{t-1}+{\sum }_{i=1}^{n-1}\mathrm{ꝩ}32,\Delta {\mathrm{R}\mathrm{M}\mathrm{M}}_{t-1}+ \\ {\sum }_{i=1}^{n-1}\mathrm{ꝩ}33,\Delta {\mathrm{F}\mathrm{D}\mathrm{I}}_{t-1}+{\mathrm{ⴎ}}_{3t} \end{gathered}$$

(6)

where

• Δ indicates first differences;
• ꭤ_1, ꭤ_2, ꭤ₃ are the rate of change coefficients toward long-run equilibrium;
• $\mathrm{ꝩ}ij$ represents short-run dynamic coefficients;
• P is the optimal lag order.

In Equation (2), the subscript _it represents the individual country and estimation period (i = 1, 2, 3, …, 15; N = 15 ECOWAS member countries); t refers to the time dimensions (1990–2022), and µ_it is the random disturbance term. First, a preliminary analysis was carried out, which included correlation analysis, unit root test, and cointegration test. The outcome motivates this study to use the panel dynamic ordinary least squares method. The shock effect was measured using Panel Vector Error Correction (PVECM), which involves variance decomposition and the impulse response function.

The ordering of variables in the VECM is grounded in theoretical and empirical evidence to capture the dynamic relationships. Since employment (LAB) is the target variable, it was placed in a position that reflects its dependence on other macroeconomic indicators. The ordering is as follows: gross domestic product (GDP), Foreign direct investment (FDI), wages (WAG), remittance (RMM), human capital (HUC), exchange rate (EXC), interest rate (INT), and employment (LAB). GDP is placed first because it serves as the foundational measure of economic activity, influencing all other variables in the system. Theoretical models, such as Solow’s growth model, suggest that GDP drives investment and employment, as economic growth creates demand for labour and resources (Yuan & Zhang, 2024). Empirical studies, including Eyre and Grover (2024), demonstrate that changes in GDP precede shifts in labour market conditions and foreign direct investment flows. FDI follows GDP because it responds to economic stability and growth, affecting host economies’ employment and wage structures (Neifar & Smaoui, 2024).

Wages are positioned after GDP and FDI, showing their sensitivity to labour market conditions and productivity. Wage adjustments often lag changes in output and employment due to structural and institutional factors (Fontanari, 2024). Remittance is followed due to the slow effect of the nature of its openness to economic activities (Asaleye et al., 2021). Human capital is ordered next as a medium- to long-term determinant of productivity and the labour market. Its development is influenced by wage levels and employment opportunities, creating feedback with GDP and FDI (Akinyele, 2024). The exchange and interest rates are placed later in the sequence, given their indirect impact on employment. Exchange rates influence trade competitiveness and investment flows, while interest rates reflect monetary policy responses to macroeconomic conditions (Rumasukun, 2024). Employment is positioned last to show its role as the dependent variable influenced by economic growth, investment, and wages; this ordering allows the model to isolate the factors driving changes in employment and assess their relative significance.

The study utilises data from the World Development Indicators to determine the impact of remittances and foreign direct investment (FDI) on employment. Employment is the dependent variable, while remittances and foreign direct investment are the independent variables. Other variables include expenditure on education, wage rate, GDP, exchange rate, and interest rate.

5. Empirical Findings and Discussion

We present the findings of the correlation tests of model regressors in

Table 2. Correlation matrix test results for multicollinearity.

	LAB	RMM	FDI	EXC	INT	HUC	GDP	WAG
LAB	1.0000
RMM	−0.0692	1.0000
FDI	0.0507	0.0881	1.0000
EXC	0.0325	−0.1500	−0.4487	1.0000
INT	0.0390	0.2565	0.1379	−0.6368	1.0000
HUC	0.0877	−0.1256	−0.1911	0.2329	−0.3324	1.0000
GDP	0.1597	−0.1522	−0.4331	0.7209	−0.4250	0.3775	1.0000
WAG	0.0544	0.5007	−0.2464	0.1416	0.1766	−0.0406	0.4439	1.0000

Source: Authors’ Computations.

. The correlation test is specifically conducted to ensure that the problem of multicollinearity is not acute. As expected, no two independent variables of both models are associated with a higher degree, implying that the specified models are not disturbed by multicollinearity issues.

In

Table 3. Panel unit root tests for stationarity.

Variables	Levin, Lin & Chu t		Breitung t-Stat
	Level	First Difference	Level	First Difference
LAB	−0.52758	−3.80260 **	0.72617	4.76025 **
RMM	0.46948	−7.69436 ***	1.84114	−3.18718 ***
FDI	−1.10967	−8.40087 ***	0.01525	−8.41024 ***
EXC	1.11963	−5.03805 ***	0.45203	4.06789 ***
INT	−4.76945 *	−12.5953 ***	−2.75278 *	−3.60206 ***
HUC	−1.14041	−7.29537 ***	−0.49082	−5.95095 ***
GDP	−0.25237	−7.69722 ***	1.59041	−5.79301 ***
WAG	−2.64596*	−1.85087 **	−0.15194	−2.27502 **

Note: ***, ** and * indicate significance for 1%, 5% and 10%, respectively. Source: Authors’ Computation.

, we present the results of the unit root test. The table provides information about the stationarity of the variables under consideration. The Levin, Lin & Chu (LLC) and Breitung t-stat assessed whether a variable has a unit root or is stationary or non-stationary. The table is separated into two categories: “level” and “first difference.” The study reveals that the variables (LAB, RMM, EXC, INT, HUC, and GDP) exhibit signs of non-stationarity in their level form, with p-values over 0.05 for both LLC and Breitung t-stat. However, all the variables are stationary at first difference. Evidence from this test, therefore, suggests that the regression models employed in examining the effects of remittances and FDI on employment are appropriate and consistent. The evidence of stationarity and differenced variables supports the reliability of the regression analysis. It enhances the validity of the study’s conclusions regarding the effect of remittances and FDI on employment in ECOWAS.

In

Table 4. Johansen Fisher panel cointegration test results.

Hypothesized	Fisher Stat.		Fisher Stat.
No. of CE (s)	Trace Test	Prob.	Max-Eigen Test	Prob.
None	966.5	0.0000	398.0	0.0000
At most 1	480.7	0.0000	260.0	0.0000
At most 2	291.3	0.0000	127.6	0.0000
At most 3	183.3	0.0000	68.12	0.0000
At most 4	130.0	0.0000	54.77	0.0008
At most 5	93.32	0.0000	54.59	0.0009
At most 6	64.19	0.0000	48.70	0.0045
At most 7	56.02	0.0006	56.02	0.0006

Source: Authors’ Computation.

, we present the Johansen cointegration test results. The test shows the possibility of long-term relationships existing among the variables. If cointegration is observed, this is an indication that the variables move together in the long period, and departures from this balanced association are mean-reverting. If the trace and Max statistics values are higher than the 5% critical value, the null hypothesis is not accepted, indicating that the sequences are cointegrated. In this study, however (see Table 4), there are at least six cointegration equations at the 5% level for both the trace and Max-eigen tests. Johansen Fisher trace and maximum eigenvalue cointegration tests, therefore, fail to accept the null hypothesis of no cointegration between variables, establishing the existence of a long-run panel cointegration association between labour employment, remittances, foreign direct investments, wage, gross domestic product, expenditure on education, exchange rate, and interest rate. According to these results, employment could affect all the independent variables in the long run.

We present the results of Panel Dynamic OLS in

Table 5. Panel dynamic ordinary least squares (PDOLS) results.

Variable	Coefficient	Std. Error	t-Statistics	Prob.
RMM	0.584767	0.54095	1.080999	0.2821
FDI	1.195205 ***	0.356305	3.354447	0.0011
WAG	−0.418418 *	0.226514	−1.847209	0.0674
GDP	−1.13 × 10−6	2.54 × 10−6	−0.444294	0.6577
HUC	3.327362 ***	0.259023	12.84581	0.0000
EXC	0.006214	0.005381	1.154873	0.2506
INT	0.491815 *	0.292463	1.681633	0.0955
R-squared	0.646571		Adjusted R-Square	0.549855

Note: *** and * indicates significance for 1% and 10%, respectively. Source: Authors’ Computation.

. Panel Dynamic OLS was employed to analyse the effect of remittance inflow and foreign direct investment on employment in ECOWAS member states. From the table, foreign direct investment (FDI) showed a positive and significant (0.001 < 0.05) relationship with employment. The positive coefficient is an indication that a unit increase in FDI will raise labour employment by 1.19. The result implies that foreign direct investment is vital to economic growth and employment in ECOWAS and developing countries generally. This finding aligns with studies like Awunyo-Vitor and Sackey (2018), Mohamed (2018), Ato-Mensah and Long (2021), and Aderemi et al. (2022), which revealed that FDI shows a positive and statistically significant influence on the rate of employment and that for every 1% rise in FDI, real employment can rise by 0.008%. The results suggest that foreign direct investment (FDI) significantly contributes to the creation of employment opportunities. Furthermore, the studies reveal that FDI not only raises job prospects but also plays a crucial role in poverty alleviation.

Wages also exhibit a positive and significant relationship with employment, although the level of significance is marginal (p-value = 0.067, which is slightly above the conventional 5% threshold). The negative coefficient is an indication that a unit rise in wages brings down labour employment by −0.41. The result corroborates Cammeraat et al. (2021) and Fontanari (2024), who affirmed that higher wages have the potential to reduce employment if they lead to higher costs for employers, thus making them reduce hiring. The finding aligns with a priori, as it represents the theoretical relationship which suggests that with a wage increase, the cost of production goes up, causing the retrenchment of workers. On the other hand, with lower wages, investors and entrepreneurs can afford to employ more workers. From the result (Table 5), education expenditure has a positive and significant (0.000 < p = 0.05) relationship with labour employment. The positive coefficient conforms to a priori. A unit increase in education spending increases labour employment by 3.33, which aligns with a priori expectation. The finding agrees with Bakhytgu et al. (2025) who reported that higher human capital generally leads to increased productivity and innovation, which can boost output per capita by enhancing labour efficiency and economic productivity.

Interest rates have a positive and significant association with labour employment. A unit increase in interest rate increases employment generation by 0.49. From the result, FDI positively impacts labour employment in ECOWAS member countries. The finding is in consonance with Onimisi (2014) and Abdulkarim (2023), who affirmed that interest rates have a significant positive impact on employment and long-term growth. The hypothesis, which says remittances inflow and foreign direct investment do not contribute positively to employment generation in ECOWAS, is therefore not accepted.

The result of the Vector Error Correction model (VECM) is presented in

Table 6. Vector Error Correction model (VECM) result.

Variable	Coefficient	Standard Error	t-Statistic
LAB(−1)	1.000000	-	-
REM(−1)	2.239380	0.67497	3.31776
FDI(−1)	−3.876201	0.37590	−10.3118
Constant (C)	−57.09894	-	-

Source: Authors’ Computation.

. Labour is normalized to 1. This is common in cointegration equations. Remittances have a positive coefficient and are statistically significant with a t- statistic close to 3.32. This means that in the long run, an increase in remittances results in an increase in employment. Remittances might improve household incomes, allow the setting up of businesses, enable investment in education, or engage more in the labour market. On the other hand, remittances could boost demand for goods and services, creating jobs and thus expanding the workforce.

Foreign direct investment has a negative coefficient and is strongly significant (high absolute t-value of about 10.31). Although FDI is usually expected to create more jobs, in this context it might be reducing employment by coming up with capital-intensive technologies which replaces labour with machine. It may also be in favour of sectors such as mining and oil extraction which are less labour intensive thereby causing structural transformation that leads to labour displacement.

Table 7. Variance decomposition test results.

Variance Decomposition of FDI
Period	S.E.	GDP	FDI	WAG	RMM	HUC	EXC	INT	LAB
1	3.600174	0.454722	99.54528	0.00000	0.00000	0.00000	0.00000	0.00000	0.000000
2	4.785132	0.776829	87.55981	0.754584	3.67707	2.101056	0.147912	4.179123	0.803614
3	5.938369	0.505155	75.41898	1.081612	9.847484	4.090479	0.548339	7.92523	0.582721
4	7.010565	0.362454	65.96109	0.986893	13.59155	7.569593	0.393791	10.70073	0.433895
5	7.980925	0.296695	61.03204	0.953484	15.74166	9.56669	0.310154	11.76389	0.335384
6	8.857071	0.30662	57.89647	0.888945	16.91848	10.96461	0.260287	12.48471	0.279875
7	9.657715	0.358032	55.84122	0.839422	17.7507	11.82388	0.22551	12.9162	0.245032
8	10.39596	0.404562	54.12822	0.818431	18.43828	12.51769	0.194621	13.28071	0.217486
9	11.08677	0.46401	52.77039	0.797402	18.97513	13.02662	0.171307	13.6006	0.194537
10	11.73934	0.528397	51.68304	0.774697	19.37315	13.44795	0.153285	13.86306	0.17643
Period	S.E.	GDP	FDI	WAG	RMM	HUC	EXC	INT	LAB
1	1.291995	2.506324	0.132864	2.023031	95.33778	0.00000	0.00000	0.00000	0.00000
2	2.343809	4.11825	0.067758	1.45195	93.58159	0.00048	0.013067	0.011157	0.755753
3	3.18262	5.538383	1.202876	0.907388	91.36893	0.062586	0.03027	0.007762	0.881802
4	3.910056	6.814767	2.061602	0.763634	89.22142	0.095412	0.057447	0.008633	0.977086
5	4.566479	8.172928	2.363344	0.64845	87.72646	0.120618	0.044329	0.036982	0.886891
6	5.167211	9.404375	2.417752	0.581278	86.52997	0.110794	0.046389	0.089103	0.82034
7	5.716712	10.40896	2.384842	0.516245	85.66551	0.09634	0.060985	0.141063	0.726049
8	6.225207	11.31395	2.34694	0.468569	84.87934	0.084142	0.073447	0.181623	0.651988
9	6.697681	12.09199	2.317812	0.423412	84.21654	0.075403	0.079381	0.212091	0.583376
10	7.141509	12.74423	2.294339	0.389061	83.65683	0.069185	0.087516	0.23289	0.525944

Source: Authors’ Computation.

provides the variance decomposition analysis for foreign direct investment (FDI) and remittances (RMM). The results reveal that FDI’s innovations predominantly explain its variance over the forecast horizon, particularly during the initial periods. Specifically, in period two, the interest rate is most affected by the forecast error shock of FDI. However, from periods three to ten, the influence of remittances becomes increasingly pronounced. Notably, employment (LAB) consistently exhibits the least impact from FDI shocks across all periods. For remittances, the variance decomposition analysis similarly indicates that its forecast error variance is predominantly driven by its own shocks throughout the ten-period horizon. The forecast error of FDI affects RMM and GDP the most, followed by employment. A comparative analysis of FDI and RMM shocks on employment reveals that RMM shocks exert a more substantial influence on employment than FDI shocks. This finding aligns with existing studies showing the role of remittances in stabilizing household income and supporting the labour market in developing economies (Jijin, 2024; Swain et al., 2025). The findings indicate that FDI might consider stabilizing interest rates and enhancing the complementary role of remittance flows to attract sustained foreign investment. Also, the pronounced impact of remittances on employment shows their role in mitigating unemployment and driving economic inclusivity, particularly in labour-intensive economies.

In

Table 8. Diagnostic tests results.

Heteroskedasticity Test: Breusch-Pagan-Godfrey
Null hypothesis: Homoskedasticity
F-statistic	1.594421	Prob	0.1851
Breusch-Godfrey Serial Correlation LM Test
Null hypothesis: No serial correlation
F-statistic	0.459034	Prob	0.7649
Ramsey RESET Test
Omitted Variables: Powers of fitted values
F-statistic	1.548925	Prob	0.2247

Source: Authors’ Computation.

, we present the diagnostic test results. We evaluate key issues such as heteroscedasticity, omitted variable bias, and serial correlation, which could otherwise lead to biased estimates. The findings indicate no evidence of heteroscedasticity, confirming the model’s homoscedasticity. Specifically, the Breusch–Pagan–Godfrey test for heteroscedasticity yields an insignificant probability value, supporting the null hypothesis of homoscedasticity.

Furthermore, the diagnostic test for serial correlation reveals no concerns, as the insignificant p-value confirms the absence of serial correlation among the variables in the employment model. The Ramsey RESET test for model specification indicates no omitted variable bias, with the insignificant p-value for the F-statistic supporting the null hypothesis of correct model specification. These diagnostic results collectively validate the robustness and reliability of the model used in this study.

6. Conclusions of the Study

This study explores the multifaceted impact of remittances, FDI, human capital, wages, GDP, exchange rates, and interest rates on employment in ECOWAS member countries. Arising from Panel Dynamic OLS results, it can be concluded that FDI positively impacts labour employment in ECOWAS member countries. Significant foreign direct investment (FDI) inflows can greatly boost the economic development of a host country by raising capital availability, creating employment, enhancing competitiveness, transferring technology, and improving the balance of payments. However, FDI also carries potential risks, including the crowding out of local businesses, profit repatriation, increased vulnerability to external shocks, and possible social and environmental challenges.

Other variables like wages, human capital formation, and interest rates also significantly influence employment in ECOWAS countries. Wage growth is capable of creating a more attractive labour market and encouraging businesses to employ more workers. Human capital, encompassing knowledge, skills, and experience, is directly connected to employment opportunities and wages. Investment in education and training programs can therefore enhance the skills of the workforce, thereby making them more competitive in the labour market. Fluctuations in exchange rates can impact the competitiveness of a country, potentially causing changes in employment in export-oriented industries. The impact of these factors on employment can vary significantly across countries, depending on factors like the economic system, policy environment, and administrative capacity.

The Vector Error Correction model (VECM) results, however, suggest that remittances play a critical role in supporting labour market outcomes, while foreign direct investment (FDI) may negatively affect employment levels in the long run which may be caused by replacement of labour with capital-intensive technology. Additionally, the analysis of external shocks from remittances and FDI on employment, as conducted through variance decomposition, demonstrates that these shocks exert significant influence both in the short-term and over-extended periods. These findings underscore the importance of considering the dual impact when formulating policies to stabilize or enhance employment levels and productivity in the face of such external economic variables.

Based on the findings, the study recommends that policymakers should implement strategies to promote and stimulate remittance flows, such as lowering transaction costs and strengthening monetary systems that channel remittances into lucrative investments. The authorities in ECOWAS member states should also try to encourage foreign direct investment and channel it into economically viable areas to help raise GDP and lower unemployment. Governments also need to motivate foreign direct investment (FDI) by providing monetary stimulus, creating sound infrastructure, and developing an agreeable organizational and regulatory environment. There is a need to promote educational investment and to secure economic, political, and legal stability. In addition, while attracting FDI remains crucial for economic growth, it is essential to direct FDI towards labour-intensive sectors like agriculture and manufacturing, especially in developing economies like ECOWAS. Furthermore, workforce policies should focus on labour market skills enhancement and training to better align the domestic workforce with the technological and structural requirements brought by FDI. A fair approach will ensure that both remittances and FDI enhance employment generation and inclusive economic development. ECOWAS member states need to build comprehensive and dynamic economies that can resist external disruptions to achieve persistent well-being.

The study recognizes the possibility of limitations, such as data availability and consistency for some of the ECOWAS countries. Data restrictions, such as missing or inconsistent data, may have influenced the analysis and interpretation of data. In addition, the model may be subject to omitted variable bias, as key factors such as technological changes and labour market policies were not included. Endogeneity is another concern, as variables like FDI, GDP, and wages may be simultaneously influenced by employment. Furthermore, important regional variations may be masked using aggregate national data.