Should I stay or leave? The effect of remittances in the sub-Saharan region

Abstract

This research provides empirical evidence that the socioeconomic improvement effect of remittances is dependent on the local status in recipient countries. Using regression and the two-stage least squares (2SLS) method, we first show that remittance size is associated with migration travel intentions. Second, the article demonstrates that in an unstable environment, even though remittances have a positive immediate effect, the influence of remittances on other longer-term proxies is significantly negative. Such finding is different compared with most of the current studies on remittance and its effects. The reason may be attributed to the departure of skilled workers from their home country decreases local socioeconomic development. The remittances and foreign connections help people with migration intention to move out and more easily settle in destination countries. Finally, we propose a potential policy direction to encourage local residents to directly consume or invest remittances in local society to improve development and decrease migration intentions.

GRAPHICAL ABSTRACT

Keywords:

• Remittance
• poverty
• migration
• migration intention
• irregular migration
• foreign connection

REVIEWING EDITOR:

• Prakash Matura, Taylor and Francis, New Delhi, India

SUBJECTS:

• Sociology & Social Policy; Development Studies; Regional Development

1. Introduction

A remittance is the money sent by migrants to their family members, relatives and friends in the country from which they originally came. Migrants who follow both regular and irregular migration paths could remit financial resources back to the origin country. In some countries, the remittances received are large and have become important funds for socioeconomic development (Golder et al., 2023). The remittance improves the living standards of the recipients and maintains the connection between the migrants living in the destination country and their relatives in the origin country (Mahapatro, 2017). The higher level of well-being in the destination country could attract the remittance recipients, and the connection with the remitters could help the recipients to eventually settle in the destination country.

The goal of migration is usually to seek better income and well-being (Lim & Morshed, 2015). Migrants from more stable and affluent socioeconomic environments may receive more support from their families and be able to follow the regular migration path. For example, they may first study in developed countries and then become skilled workers to receive a more permanent immigration status. Residents struggling in extremely poor environments or living in environments with civil conflicts intend to leave the country and seek asylum using irregular migration paths (Osman et al., 2022). The different backgrounds of remitters may diversify their living standards in the destination country and their ability to make remittances. The status and the political statutes of their original country can affect the size of the remittances.

The remittance can immediately improve the consumption capacity of the recipient (Seydou, 2023). In some countries, people use remittances to make investments and improve social infrastructure to improve their hometowns. The remittance helps to increase productivity, improve human capital and elevate the future living standard expectation of the local residents. The remittance effect can therefore be classified as both short term and long term. The short-term effect immediately impacts the economy, but the long-term effect helps economic development and growth more. The remittance can directly affect the recipient market consumption and improve the local well-being in the short run (Samaratunge et al., 2020). In the longer term, the remittance could increase capital accumulation and contribute to technological growth, improving the recipient country’s investment and production (Manic, 2017). For example, effects on consumption capacity are more short term, and economic productivity and education improvements could be long-term effects (Nyamongo et al., 2012). Receiving remittances is not always a universal good, and sometimes remittances can cause internal conflict within the recipient’s family (Ikuomola, 2015). Remittance in developing countries may increase the local inflation. In most developing countries, the local economy size is small. If the remittance is large, then the inflow of wealth could push up the local price level, making the family worse off without remittance (Narayan et al., 2011; Ulyses Balderas & Nath, 2008). Even the remittance helps to stabilize household consumption (Combes & Ebeke, 2011), increases individual wealth, thereby reducing the likelihood of participating in civil conflicts and war (Batu, 2019), but the large remittance vibration could significantly increase economic volatility (Jackman et al., 2009).

The behavior and socioeconomic consequences of remittances are heterogeneous in the long run. In most countries, remittances improve local social development, but this is not always true (Francois et al., 2022). This article chooses a unique socioeconomic start-up region, sub-Saharan Africa, as the research target. Sub-Saharan Africa differentiates itself from other regions with a high rate of remittances such as Southeast Asia or Eastern Europe. Sub-Saharan countries frequently suffer from political instability and civil conflicts (Babajide et al., 2021). A stable political status with quality governance in public administration could enhance the positive effects of remittances on economic development (Ogunniyi et al., 2020). In contrast, it is difficult to successfully utilize remittances to develop economies and education to improve social well-being when conflict and war occur (Cazachevici et al., 2020). This unique environment provides an opportunity to understand the different effects of remittances and how recipients use remittances relative to recipients living in more stable societies.

This research contributes to the current literature in the following ways. First, we propose that the effect of remittances could have different social consequences based on the level of socioeconomic development and the civil political environment. Most of the current research on remittance focuses on its effects on socioeconomic improvements in the receiving countries. We argue that in the earlier stage of socioeconomic development in an unstable civil political environment, remittance recipients may use the money to cover travel costs to escape from the country. Second, the number of irregular migrations is used as the instrumental variable, and the research further demonstrates that the long-term effect of remittances may be negative when people intend to migrate upon receiving remittances. Such a view is not well discussed in current research.

The rest of the article is organized as follows. This section introduces the general concepts and reasons for migration and remittances to help relatives living in the original country. Section 2 reviews the literature and proposes hypotheses. The data collection strategies and empirical methodology are described next. The empirical results are analyzed in Section 4. Finally, Section 5 concludes the article.

2. Literature review and hypotheses

Migration has complicated reasons, and most migrants experience a difficult but careful decision-making process. The most common incentives for self-decided regular migration include seeking better economic opportunities, education and foreign connections. In some regions with high political uncertainty and civil conflict, people are forced to leave their hometowns or choose to follow irregular migration as refugees. Migrant remittance happens after migrants move into a better environment, which tends to help the family stay in the original country. The remittance shows the altruistic motivation of the migrants to help their relatives (Mallela et al., 2020). The migrants’ destination country regulations, the employee market participation and status, affect the remittance (Mahmud, 2016). The degree of remittance is higher for people from less developed original countries (Azizi, 2019). The migrant labor’s remit could have a significant social and economic impact in countries with a large labor force seeking opportunities in foreign markets (Iskander, 2017; Rodriguez, 2010).

2.1. Remittance and migration intention

Most current research suggests that remittances can significantly help improve local development and alleviate poverty (Caarls et al., 2013). When local residents in countries at an earlier stage of development receive large remittances from their overseas relatives (Garip et al., 2015), they can use that money to make investments for future profit generation, cover their health expenditures, spend it on children’s education or simply increase their current consumption capacity. If the local environment is difficult and local residents do not expect large changes in the short term, they may simply use remittances as travel costs and leave the country to seek opportunities in a more developed society (Song & Liang, 2019). The remittance amount is positively related to the distance between the remitter and the receiver (Ferriani & Oddo, 2019). The remittances sent from relatives are significantly related to migration intention (Leeves, 2009). The main reason for people leaving their home countries is poverty (Lokshin et al., 2010), and the probability of migration increases with their foreign connections (Khoo, 2003) and remittances (Diallo, 2022). Most research points to the most significant reason for migration as seeking a higher income, but the income effect is insignificant in irregular migrations (Restelli, 2023). This happens when the local residents are extremely disappointed with the environments in their original countries, probably not only with the economic situation and level of poverty but also with human rights, education, health and other basic elements of well-being (Truong, 2006). Considering the high level of overseas connections and the ability to compare other places with the local social environment among refugees, we use the number of refugees as a proxy of migration intention to argue that people may compare other more stable and developing societies with their own situation and that their migration intention is associated with receiving remittances from their relatives in destination countries.

H1: Higher remittances are associated with higher migration intention.

2.2. Remittance and local socioeconomic development

Regarding the economic and consumption effects, most of the recent research focuses on the consequences of receiving remittances. Most research indicates a positive and poverty-reducing effect when local residents receive remittances (Musakwa & Odhiambo, 2020; Chowdhury, 2016; Ramanayake & Wijetunga, 2018). If remittance inflows can be well managed and efficiently utilized (Hossain et al., 2019; Dutta & Saikia, 2022), it will help local socioeconomic development (Apanisile & Oliseyenum, 2023) and improve local welfare (Koc & Onan, 2004). At the country level, some studies indicate that there is no causal relationship between remittances and local economic growth if the recipient country is economically in a later, rather than an early, stage as a developing country (Nyasha & Odhiambo, 2020). When the remittances are large, compared with the local income, these remittances may decrease the willingness of the local recipient to work and thus reduce the labor supply (Dey, 2022). It is worth noting that most people intending to leave are skilled workers; the remittances they send back home are larger since it is easier for them to access better jobs in destination countries (Eversole & Shaw, 2010)), and their departure can negatively affect the local economy. Given the local situation in our sample region and their local socioeconomic environment, the research proposes the following hypothesis:

H2: Higher levels of remittances lead to lower per capita gross domestic product (GDP) values in harsh socioeconomic settings.

2.3. Remittance and primary education

Most research indicates that remittances can significantly improve participation in local education (Stanley & Fleming, 2019). Some research mentions that remittances increase school attendance and educational attainment (Mansour et al., 2011; Bouoiyour & Miftah, 2016). The effect becomes insignificant when education is no longer compulsory (Sawyer, 2016). In the case of regular migration, it is often the case that international students later join the cohort of skilled workers (Baas, 2019). Since most irregular migrants are young to middle-aged workers, when the local environment is bad, they usually choose to move the whole family (Heger Boyle & Ali, 2010). Most remittances improve education in a comparatively stable society, and funds are used to support families with living expenditures and reduce school dropout rates. In most sub-Saharan countries, unstable political status and civil conflict are reasons for people to evacuate and for children to drop out of school (Williams, 2004; Taher et al., 2022). When the remittances are large enough to afford the cost for the whole family, including young children, to leave in either regular or irregular ways, the school completion rate is negatively affected. Considering the unique political and civil situation, this study presents the following hypothesis:

H3: Higher remittances lead to lower primary education completion rates in harsh socioeconomic settings.

2.4. Remittances and health improvement

In contrast to economic growth, expenditures on health are not affected by whether skilled laborers choose to stay or leave. The inflow of remittances could immediately improve healthcare affordability (Kan, 2021; Kapri & Jha, 2020; Sahoo et al., 2020). Another way to analyze how remittances help to improve health is through the consumption of healthcare services (Petreski et al., 2018) and nutrition factors (Lu, 2013). Greater financial availability increases consumption capacity and improves the health of remittance receivers. Such improvement may be temporary and immediate (Paul et al., 2011). When focusing on the long-term effect, skilled doctors and education in professional medication services are essential factors to improve the overall conditions of health in the community.

H4: Higher remittances lead to immediate higher health expenditures.

2.5. Robustness and endogeneity problems

The number of refugees is a good instrumental variable for measuring the social impact of remittances. Inevitably, remittances and social behavior outcomes may suffer problems with endogeneity; for example, it is difficult to determine whether poverty causes relatives from overseas to send money to local residents (Hunte, 2004) or whether the potential for remittances causes local residents to leave, making the local social and economic environments even worse. The education and economic development level in the original country can affect their skill and ability to obtain higher paid jobs in a new environment (Zhai & Kono, 2021). The number of migrants is closely related to remittances but does not directly affect social outcomes such as local education and local health expenditures. Although leaving the labor force may affect the per capita GDP, the number of migrants is small compared with the total labor population, so the direct influence would be minor. The two-stage least squares (2SLS) instrumental variable method can alleviate the endogeneity problem and enhance the robustness of the analysis of causality.

3. Data and methodology

3.1. Data

This research collects data from the World Bank’s World Development Indicators database. The sample period covers 2010–2019. The COVID-19 period is excluded since social behaviors are affected by the pandemic. The total country-year observation should be 480, but there are some missing observations for each variable. The final sample constitutes imbalanced panel data. The variable ‘POOR’ is defined as a dummy variable if the per capita GDP is below average. Tables 1 and 2 show the general statistics and the variable definitions, respectively. Variables in dollars (‘RIM’, ‘FDI’ and ‘GDP’) and number of people (‘REFUGEE’) are log-treated to alleviate the effects of heteroskedasticity. Countries with unstable social conditions cannot collect local statistics or do not have a strong incentive to collect social statistics when they know the outcome is not impressive, resulting in missing data in the World Bank Indicator database. For example, in Table 1, the primary education rate is not well reported. The World Bank Indicator database provides much smaller primary education rate observations than other research variables for the same sample period. Also, note that in the sub-Saharan region, the remittances are almost as large as the net inflow of foreign direct investment. This indicates that the region does not attract much foreign investment because of its social instability.

Table 1. General statistics.

Statistic	N	Mean	St. Dev	Min	Pctl(25)	Pctl(75)	Max
RIM	417	5.296	1.760	−1.586	4.156	6.366	10.098
FDI	456	5.641	1.903	−2.893	4.657	6.903	9.213
GDP	463	7.199	0.950	5.599	6.453	7.750	9.726
CORR	480	−0.659	0.662	−1.784	−1.177	−0.258	1.211
EDU	327	71.949	17.894	21.473	59.953	86.348	112.646
EDUFEMALE	320	70.909	19.968	19.293	55.988	88.132	112.776
EDUMALE	320	72.722	16.227	35.424	60.929	85.120	115.129
HEALTH	463	37.481	20.204	2.993	21.804	53.126	80.461
REFUGEE	478	8.377	3.172	1.609	5.726	10.596	14.707
POOR	480	0.533	0.499	0	0	1	1

Table 2. Variable definitions.

Variable	Symbol	Variable treatment
Personal remittances	RIM	Personal remittances received in current US dollars
Foreign direct investment	FDI	Foreign direct investment, net inflows, current US dollars
Corruption control index	CORR	Corruption control index from World Bank database
GDP per capita	GDP	GDP per capita, constant 2015 dollars
Primary school finish rate	EDU	Primary school finish rate
Primary school finish rate for males	EDUMALE	Primary school finish rate for males
Primary school finish rate for females	EDUFEMALE	Primary school finish rate for females
Out-of-pocket expenditures on health	HEALTH	The out-of-pocket expenditures as a percentage of current health expenditures
Number of refugees	REFUGEE	The number of people entering other countries as refugees
Dummy variable	POOR	If the country’s per capita GDP is lower than average, POOR = 1, otherwise it is 0

3.2. Methodology

3.2.1. Remittance and migration intention

The first test involves the behavior of recipients living in the sub-Saharan region when they receive remittances. Equation (1)(1) $${\mathit{\text{RIM}}}_{i,t}={\beta }_0+{\beta }_1{\mathit{\text{REFUGEE}}}_{i,t}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(1) checks the causality between receiving remittances and the number of people leaving their original country following the irregular migration path. If the region suffers political instability and a high unemployment rate, the expectation is that the ‘REFUGEE’ term should have a positive coefficient, which indicates that high levels of irregular migration are associated with receiving higher remittances. The remittance may be used to cover travel costs and to seek opportunities in more stable socioeconomic environments. Since the missing observations in the sample data are severe and occur in almost all variables, the imbalanced panel data are clustered by the ‘POOR’ term to control for the fixed effect rather than implement individual controls for each variable. The variable ‘Year’ controls the time effect. (1) $${\mathit{\text{RIM}}}_{i,t}={\beta }_0+{\beta }_1{\mathit{\text{REFUGEE}}}_{i,t}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(1)

3.2.2. Remittance and local socioeconomic development

The second test focuses on the long-term effect of remittances on GDP growth. Equation (2)(2) $${\mathit{\text{GDP}}}_{i,t}={\beta }_0+{\beta }_1{\mathit{\text{RIM}}}_{i,t}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(2) tests how remittances affect GDP in recipient countries. Unlike most other studies in more developed environments, if skilled laborers choose to leave the country upon receiving remittances, then the local economy may be negatively affected. Of course, the remittance itself can help local development, and the problem occurs when the political and socioeconomic environment is in chaos. The remittance recipient would make different decisions than the remittance recipient in a more stable environment based on the local situation. (2) $${\mathit{\text{GDP}}}_{i,t}={\beta }_0+{\beta }_1{\mathit{\text{RIM}}}_{i,t}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(2)

3.2.3. Remittances and primary education

Similar to the last argument on the relationship between remittances and GPD, education is also a long-term indicator of socioeconomic development. If young and middle-aged people make migration plans, they may choose to take their family with them rather than reunite after many years. If the migration intention is obverse and high, then the children’s school dropout rate increases with migration intentions. Equation (3)(3) $${\mathit{\text{EDU}}}_{i,t}={\beta }_0+{\beta }_1{\mathit{\text{RIM}}}_{i,t}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_{3}F{I}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(3) checks this relationship. (3) $${\mathit{\text{EDU}}}_{i,t}={\beta }_0+{\beta }_1{\mathit{\text{RIM}}}_{i,t}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_{3}F{I}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(3)

3.2.4. Remittance and health improvement

Equation (4)(4) $${\mathit{\text{HEALTH}}}_{i,t}={\beta }_0+{\beta }_1{\mathit{\text{RIM}}}_{i,t}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(4) tests the relationship between remittances and health expenditures. Health expenditures are a relatively short-term proxy that measures remittance recipients’ well-being. Sub-Saharan regions suffer harsh hygiene problems and lower quality of governance. The public health service system may be difficult to rely on, and medication costs largely need to be covered by the residents themselves. When they receive remittances, a more bounteous financial status should improve their medical coverage and therefore increase expenditures on health. (4) $${\mathit{\text{HEALTH}}}_{i,t}={\beta }_0+{\beta }_1{\mathit{\text{RIM}}}_{i,t}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(4)

3.2.5. Robustness and endogeneity problems

The number of refugees is selected as the instrumental variable to remeasure the impact of the remittances on all socioeconomic proxies to test for the robustness of the relationship. The number of refugees represents expectations about the future of the home country from the view of local residents. When the view is optimistic, there is a lower number of local residents leaving their country and following the irregular migration path. When the view is pessimistic, the number of refugees increases. The remittances may be associated with other factors, including local productivity and human capital, which are also factors that affect GDP but are omitted. The number of refugees has no connection with productivity or human capital, but it may be positively associated with the amount of remittances received, and it well represents behavior and attitude. When analyzing the primary school completion rate, remittances may be connected to other unobservable donations for school construction. Using the number of refugees as the instrumental variable can solve the potential variable omission problem. Such a relationship makes the number of refugees a well-qualified potential instrumental variable. Equations (5)(5) $${\mathit{\text{GDP}}}_{i,t}={\beta }_0+{\beta }_1\stackrel{}{R{\widehat{\mathit{\text{IM}}}}_{i,t}}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(5) and (6)(6) $$\mathit{\text{HEAL}}T{H}_{i,t}={\beta }_0+{\beta }_1\stackrel{}{R{\widehat{\mathit{\text{IM}}}}_{i,t}}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(6) represent the remittances by number of refugees and implement 2SLS to remeasure causality. (5) $${\mathit{\text{GDP}}}_{i,t}={\beta }_0+{\beta }_1\stackrel{}{R{\widehat{\mathit{\text{IM}}}}_{i,t}}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(5) (6) $$\mathit{\text{HEAL}}T{H}_{i,t}={\beta }_0+{\beta }_1\stackrel{}{R{\widehat{\mathit{\text{IM}}}}_{i,t}}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(6)

Furthermore, to check the robustness, education is divided into education for males and education for females, and the number of refugees is also used as the instrumental variable. (7) $${\mathit{\text{EDUMALE}}}_{i,t}={\beta }_0+{\beta }_1\stackrel{}{R{\widehat{\mathit{\text{IM}}}}_{i,t}}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(7) (8) $${\mathit{\text{EDUFEMALE}}}_{i,t}={\beta }_0+{\beta }_1\stackrel{}{R{\widehat{\mathit{\text{IM}}}}_{i,t}}+{\beta }_2{\mathit{\text{CORR}}}_{i,t}+{\beta }_3{\mathit{\text{FDI}}}_{i,t}+{\beta }_4\left[{\mathit{\text{CORR}}}_{i,t}\text{*}{\mathit{\text{FDI}}}_{i,t}\right]+{\beta }_5{\mathit{\text{POOR}}}_{i,t}+\sum \mathit{\text{YEAR}}+{\epsilon }_{i,t}$$(8)

4. Results

4.1. Remittances and migration intention

The relationship between remittances and the number of refugees is shown in Table 3. The coefficients of the number of refugees are all positive and significant, which indicates that larger remittances are associated with a higher number of people leaving their home country in the sub-Saharan region. Hypothesis 1 is supported. Notably, the corruption coefficient is negative, indicating that corruption could decrease the remittance inflow. Corruption may increase the difficulty of successfully sending money to recipients. Compared with the negative effect on the size of remittances, higher foreign direct investment could improve local development and alleviate local corruption and other unethical political issues, which consequently increase the size of remittances.

Table 3. Remittances and refugee travel budget.

	Dependent variable:
	RIM
	(1)	(2)	(3)
REFUGEE	0.239***	0.233***	0.233***
	(0.031)	(0.031)	(0.031)
CORR	−0.998**	−0.956**	−0.940**
	(0.425)	(0.430)	(0.436)
FDI	0.143**	0.140**	0.139**
	(0.067)	(0.068)	(0.068)
CORR*FDI	0.169**	0.159**	0.158**
	(0.071)	(0.072)	(0.072)
POOR			0.038
			(0.161)
Constant	2.616***	2.405***	2.388***
	(0.440)	(0.487)	(0.494)
Year control	N	Y	Y
Observations	394	394	394
R^2	0.207	0.215	0.215
Adjusted R^2	0.199	0.188	0.186
Residual Std. Error	1.513 (df = 389)	1.523 (df = 380)	1.525 (df = 379)
F Statistic	25.398*** (df = 4; 389)	7.993*** (df = 13; 380)	7.408*** (df = 14; 379)

Note: *, ** and *** denote the statistical significance at the 1%, 5% and 10% levels; standard errors are shown in parentheses.

4.2. Remittance and local socioeconomic development

Table 4 shows the results of the relationship between remittances and per capita GDP. The significant negative coefficients show that higher remittances sent into the country lower the local per capita GDP. Hypothesis 2 is supported. One of the reasons is that the local income is too low, and if the remittances can cover the living expenditures, it could lower the incentive for the local resident to participate in production. The other is that young and middle-aged skilled workers find it easier to find matching jobs in potential destination countries, and receiving remittances increases their migration intentions. If highly skilled laborers leave, it inevitably negatively affects local productivity.

Table 4. Remittances and GDP.

	Dependent variable:
	GDP
	(1)	(2)	(3)
RIM	−0.059**	−0.063**	−0.059***
	(0.024)	(0.025)	(0.014)
CORR	0.643***	0.657***	−0.029
	(0.222)	(0.225)	(0.133)
FDI	0.082**	0.082**	0.100***
	(0.035)	(0.035)	(0.020)
CORR*FDI	0.008	0.006	0.078***
	(0.037)	(0.037)	(0.022)
POOR			−1.325***
			(0.049)
Constant	7.418***	7.344***	7.902***
	(0.226)	(0.250)	(0.146)
Year control	N	Y	Y
Observations	390	390	390
R^2	0.296	0.301	0.766
Adjusted R^2	0.289	0.277	0.757
Residual Std. Error	0.773 (df = 385)	0.779 (df = 376)	0.451 (df = 375)
F Statistic	40.485*** (df = 4; 385)	12.459*** (df = 13; 376)	87.665*** (df = 14; 375)

Note: ***, ** and * denote the statistical significance at the 1%, 5% and 10% levels; standard errors are shown in parentheses.

4.3. Remittances and primary education

The coefficients of remittances in Table 5 are negatively significant when ‘POOR’ is not controlled. In Column (3), even though the coefficient of remittances is negative, the p value is slightly larger than the 10% level. Hypothesis 3 is partially supported and requires further investigation. The term ‘POOR’ explains a large negative effect on education, indicating that there is a large difference between the two groups. The heterogeneities between the countries based on ‘POOR’ (POOR is categorized based on per capita GDP) demonstrate and support the original general hypothesis that the usage of remittances, whether for making local investments and consumption or for investing in travel costs to leave, is based on expectations about local socioeconomic conditions.

Table 5. Remittances and education.

	Dependent variable:
	EDU
	(1)	(2)	(3)
RIM	−1.261**	−1.368**	−0.756
	(0.558)	(0.572)	(0.479)
CORR	−2.229	−2.165	−7.231**
	(4.245)	(4.314)	(3.620)
FDI	0.650	0.638	0.897*
	(0.626)	(0.638)	(0.532)
CORR*FDI	2.869***	2.821***	3.130***
	(0.703)	(0.716)	(0.596)
POOR			−15.733***
			(1.439)
Constant	83.991***	83.141***	87.897***
	(4.437)	(4.883)	(4.087)
Year control	N	Y	Y
Observations	281	281	281
R^2	0.385	0.395	0.583
Adjusted R^2	0.376	0.366	0.561
Residual Std. Error	13.198 (df = 276)	13.307 (df = 267)	11.074 (df = 266)
F Statistic	43.186*** (df = 4; 276)	13.418*** (df = 13; 267)	26.526*** (df = 14; 266)

Note: ***, ** and * denote the statistical significance at the 1%, 5% and 10% levels; standard errors are shown in parentheses.

4.4. Remittances and health improvement

The relationship between health expenditures and remittances is shown in Table 6. All coefficients of remittances are positively significant, indicating that higher remittances lead to improved health expenditures. Hypothesis 4 is supported. Higher remittances can lead to immediate short-term well-being improvements.

Table 6. Remittances and health.

	Dependent variable:
	HEALTH
	(1)	(2)	(3)
RIM	1.794***	1.895***	1.898***
	(0.540)	(0.549)	(0.550)
CORR	−3.461	−3.917	−4.170
	(4.922)	(4.981)	(5.048)
FDI	0.386	0.423	0.428
	(0.766)	(0.776)	(0.777)
CORR*FDI	−1.741**	−1.654**	−1.628*
	(0.819)	(0.829)	(0.834)
POOR			−0.590
			(1.828)
Constant	16.157***	18.346***	18.609***
	(5.004)	(5.528)	(5.595)
Year control	N	Y	Y
Observations	389	389	389
R^2	0.278	0.283	0.283
Adjusted R^2	0.271	0.258	0.257
Residual Std. Error	17.033 (df = 384)	17.179 (df = 375)	17.199 (df = 374)
F Statistic	37.052*** (df = 4; 384)	11.400*** (df = 13; 375)	10.568*** (df = 14; 374)

Note: ***, ** and * denote the statistical significance at the 1%, 5% and 10% levels; standard errors are shown in parentheses.

4.5. Robustness and endogeneity problems

The recalculation of causal relationships between remittances and GDP and health expenditures using 2SLS are shown in Table 7. Both coefficients in Columns (2) and (3) keep the same sign as in the original tests. The remittances negatively affect GDP but positively contribute to the improvement of health expenditures. The instrumental variable result on education is shown in Table 8. In the original test, after adding economic status controls, the coefficient of remittances becomes insignificant. In the instrument variable tests, all coefficients of remittances in any regression show significant negative results. The previous ordinary panel results may have suffered from an omitted variable problem and endogeneity. In typical cases, low-quality education may also increase the amount of remittances sent by relatives from destination countries. The 2SLS instrumental variable is more trustworthy and stable than the original estimation, and Hypothesis 3 can be confirmed.

Table 7. 2SLS refugees as the instrumental variable for GDP and health.

	Dependent variable:
	RIM	GDP	HEALTH
	OLS	Instrumental	Instrumental
		variable	variable
	(1)	(2)	(3)
REFUGEE	0.233***	−0.197***	6.084***
	(0.031)	(0.043)	(1.575)
CORR	−0.940**	−0.234	2.136
	(0.436)	(0.160)	(5.854)
FDI	0.139**	0.122***	−0.227
	(0.068)	(0.024)	(0.866)
CORR*FDI	0.158**	0.097***	−2.234**
	(0.072)	(0.025)	(0.920)
POOR	0.038	−1.320***	−0.839
	(0.161)	(0.054)	(1.966)
	(0.494)
Constant	0.233***	8.415***	3.111
	(0.031)	(0.222)	(8.086)
Year control	Y	Y	Y
Observations	394	390	389
R^2	0.432	0.707	0.172
Adjusted R^2	0.411	0.696	0.141
Residual Std. Error	2.354 (df = 379)	0.505 (df = 375)	18.484 (df = 374)
F Statistic	20.582*** (df = 14; 379)

Note: ***, ** and * denote the statistical significance at the 1%, 5% and 10% levels; standard errors are shown in parentheses.

Table 8. 2SLS refugees as instrumental variables in education.

	Dependent variable:
	RIM	EDU	EDUFEMALE	EDUMALE
	OLS	Instrumental	Instrumental	Instrumental
		variable	variable	variable
	(1)	(2)	(3)	(4)
REFUGEE	0.233***	−6.960***	−6.852***	−6.162***
	(0.031)	(2.147)	(2.271)	(2.001)
CORR	−0.940**	−16.504***	−16.616***	−17.904***
	(0.436)	(5.552)	(5.887)	(5.187)
FDI	0.139**	1.455**	1.763**	1.144*
	(0.068)	(0.704)	(0.752)	(0.662)
CORR*FDI	0.158**	4.102***	4.512***	3.920***
	(0.072)	(0.827)	(0.880)	(0.776)
POOR	0.038	−13.557***	−13.109***	−14.506***
	(0.161)	(1.974)	(2.077)	(1.830)
Constant	2.388***	111.732***	108.720***	110.646***
	(0.494)	(9.473)	(10.222)	(9.007)
Year control	Y	Y	Y	Y
Observations	394	281	274	274
R^2	0.432	0.320	0.357	0.317
Adjusted R^2	0.411	0.284	0.322	0.280
Residual Std. Error	2.354 (df = 379)	14.139 (df = 266)	14.956 (df = 259)	13.178 (df = 259)
F Statistic	20.582*** (df = 14; 379)

Note: ***, ** and * denote the statistical significance at the 1%, 5% and 10% levels; standard errors are shown in parentheses.

4.6. Summary of findings and discussion

4.6.1. Summary of findings

Table 9 shows a summary of the findings.

Table 9. Summary of findings.

Hypotheses	Validation
H1. Higher number of refugees is associated with higher remittance.	Supported
H2. Higher remittances decrease the GDP in harsh socioeconomic environments.	Supported
H3. Higher remittances increase the primary school dropout rate in harsh socioeconomic environments.	Supported
H4. Higher remittances increase health expenditures and healthcare affordability	Supported

4.6.2. Discussion

Numerous circumstances push people to leave sub-Saharan Region, as evidenced by constant media coverage and references. Armed wars, such as those in South Sudan and the Democratic Republic of the Congo, create dangerous living circumstances, forcing individuals to seek asylum for their own protection. Authoritarian governments, such as those in Eritrea and Zimbabwe, restrict political liberties, leading residents to seek asylum overseas. Widespread poverty, particularly in countries such as the Sahel, drives migration in search of better economic opportunities. People depart their houses due to environmental degradation, which is visible in places affected by climate change. As a result, people frequently relocate with their money or with help from foreign organizations, relying mostly on remittances from family.

A noteworthy example and case study of the rise of migrants and remittances from their home country as a result of violence is when Siyad Bare, Somalia’s dictatorial president, launched the Isaaq genocide against the northern portion of Somalia, currently known as Somaliland. The genocide began in 1989 and resulted in a massive migration, killing hundreds and displacing half a million people. To escape the chaos, most individuals sought assistance from relatives in the diaspora.

The worldwide consequences of Bare’s leadership and the aftermath fueled the rise of the Somali diaspora, as individuals abandoned their home country in search of safety and better opportunities overseas. Due to their common experiences of hardship and relocation, people in the diaspora remained bonded to Somalia by sending remittance even though they were geographically separated from it. As a result, the war has boosted both the number of migrants and the quantity of remittances transferred to Somalia.

Moreover, there is a clear correlation between the migratory dynamics that drive individuals to leave their place of origin and the significant doubling of remittance flows to Somalia over time as the study has explained above. This financial safety net not only supports families back home but also shows the diaspora’s steadfast commitment to upholding and elevating their communities despite ongoing instability. The relationship between migration, remittances and war draws attention to the complex interplay of socio-political factors that influence the Somali diaspora’s collective experience and resilience in the face of hardship.

When remittance recipients receive funds, they consider the best way to use the funds to maximize their current and future discounted utilities. In any cross-temporal study, expectations about the future are important in decision-making. Different from residents living in more stable but developing societies, people in the sub-Saharan region have lower trust in local governance and experience social disorder from civil conflicts. The remittances along with connections to the destination family members or relatives help them to move out and settle down in destination countries. The panel model used in this research finds that the short-term effect of receiving remittances could immediately improve recipients’ well-being, but the long-term effects are different from those of research using an autoregressive distributed lag model (ARDL) targeting more developed societies. Since the data in almost all variables have continuity problems in the sample period, data gaps prevent the use of ARDL. When the long-term effect of remittances is opposite, it shows that the expectations of the recipients are different and that there is a negative outlook for local developments.

One of the potential policies that could help to alleviate the increase in migration intention is to minimize processing costs and encourage smaller but more frequent remittances. Most banks do not handle the remittances if they are too small, so the remitters must switch to microfinance providers. The process cost of using microfinance providers is high, which forces them to make more irregular lumpsum payments rather than regular remittances. Microfinance institutions experience less cost-effectiveness because they must handle much smaller amounts of money more frequently than traditional financial institutions. The requirements of monitoring to follow the transaction required by the relegation force the microfinance institutions to have more labor expenses, significantly affecting their efficiency (Weiss & Montgomery, 2005). Some microfinance providers do not strictly follow the regulation and involving money laundry and other illegal activities, the cost and risk of following the commercial irregular path could be high for local residents.

If local governance could meet their expectations for socioeconomic development, lower the transaction cost of the remittance, the incentive for migration may decrease. One of the successful contributions of microfinance institutions in some countries is they can provide additional job and skill training to reduce poverty while providing financial services (Montgomery & Weiss, 2011). If it is possible to combine the remittance with the skill training services, it could efficiently increase local development.

5. Conclusion and future research

In this article, we provide empirical evidence and a novel concept that when the socioeconomic environment is harsh, remittances do not improve the socioeconomic environment in the long term. Rather than investing in local society, people choose to use remittances to cover travel costs and leave. Such migration intentions are reflected in the long-term proxies used in the test. The short-term effect is the same as in most of the research done in more developed countries, and consumption could increase immediately. The results are further confirmed by using the 2SLS method.

A further focus could be on how to minimize the cost of sending the remittances and organize the usage of the remittances in a more efficient way. When the remittances are small and there are many transactions, the bank documentation and verification costs could be high. The same dilemma occurs in microfinance institutions; most large banks give up these business opportunities since the monitoring cost is too high. Looking for a solution could help encourage local residents to use remittances locally and support socioeconomic development, but the stability of the political status is probably a prerequisite.

Authors’ contributions

Conception and design – D.S., S.H. and C.L.; analysis and interpretation of the data – Data is from World Development Indicators database, analyzed by D.S., S.H. and C.L.; drafting of the paper – D.S., S.H. and C.L.; revising it critically for intellectual content – D.S., S.H. and C.L.; final approval – D.S.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are openly available in World Bank’s World Development Indicators database at https://databank.worldbank.org/source/world-development-indicators.

Additional information

Funding

No funding was received.