This paper examines the possibility of directing remittances from Burkinabè migrants to the municipalities of their home country through loans. The descriptive results indicate that 94% of Burkinabè migrants agree to lend to the municipalities of their country. The econometric results obtained using the Tobit model show that variables of interest and economic variables such as profit, economic development, poverty reduction and job creation do not influence loan consent to the municipalities. On the other hand, cultural variables such as community spirit, unity, and mutual support, belief in God, conformism, and gerontocracy explain agreement to lend.
There is no doubt that migrant remittances (MRs) represent a source of economic development for recipient countries. According to the World Bank (2007), they compensate the lack of public investment. In fact, studies show that MRs have made it possible to fund public infrastructures such as roads, buildings, electricity, drinking water, irrigation systems, mills, factories, dams, etc., social development projects: community centers, literacy projects, schools, dormitories or university dorms, churches and mosques, etc. [
loans for real estate investments and entrepreneurs in Morocco. The Unlad organization in the Philippines mobilizes the MRs for productive and community investments. It identifies productive investments and facilitates access to loan. In India, the investment center facilitates business development by working with non-Indian residents to identify sources of capital and technology. In Lesotho, the association of mining workers in South Africa set up a deferred payment plan to ensure that money earned by migrant workers was invested and spent in the domestic economy [
The idea is to analyze the agreement to lend (AL) of Burkinabè migrants to municipalities in their home country. This article is based on a field survey that we conducted in 2014 with 600 Burkinabè migrants living in Côte d’Ivoire. To determine the explanatory factors for agreement to lend, we prefer the Tobit model because we only examine the behavior of people who consent to lend to the municipalities of their country so as to take into account the censored nature of the dependent variable. The rest of the article is presented as follows. We present the situation of decentralization in the first part. The second part explains the methodology and the data used. The third part examines the empirical results obtained.
Decentralization in Burkina Faso, like decentralization in sub-Saharan Africa, faces two challenges: “the weakness of resources and the legitimacy of local authorities. The legality and the legitimacy of the decentralization in Africa remain still ambiguous. Indeed, there are two legitimacies” that of the universal suffrage and that of the usual and/or traditional succession. The mayor is obliged to cooperate with traditional village chiefs [
The financing of the decentralization in the countries of sub-Saharan Africa is a real challenge. Indeed, in these countries, only 5% of the state resources are assigned to regions against 10% for all the developed countries [
In the end, it is essential to integrate the cultural aspect into the decentralization process in order to allow local authorities to function [
Our study is based on data from a 2014 survey of Burkinabè migrants in Côte d’Ivoire. Since there was no survey frame, building a representative sample with probabilistic methods is impossible. Among the most common non-probabilistic methods is the snowball method, which is appropriate for the study of hard-to-reach populations [
Studies dealing with migrants are confronted with a number of obstacles. Indeed, there is no database on migrants in the host countries of the migrants and it is very costly to carry out a survey on migrants in the cases where host countries are many [
In order to determine the explanatory factors for the loan consent of Burkinabè migrants, we prefer the Tobit model because we only examine the results from people who agree to lend money to the municipalities of their country. Therefore, it is important to consider the censored nature of the dependent variable since there are migrants who do not consent to lend money. The loan consent variable (LC) of individuals is censored on the left (LC > 0). Besides, we assume that the loan decisions and the choice of the amount of the loan are made simultaneously.
We define our LC as follows:
Y i ∗ = X i β + ε i (1)
Y* is the dependent variable that captures the LC of the individual i; Xi is the vector of the independent variables that explains the LC of the individual i, β is a vector of k fixed coefficients to be estimated and εi is a vector of independent residuals normally distributed of zero mean and variance σ². So:
Y i = 0 s i Y ∗ ≤ 0
Y i = Y ∗ s i Y ∗ > 0
However, the Tobit model estimators are biased in the presence of heteroscedasticity of residues. To fix this problem, we use the Breusch-Pagan Test to test the homoscedascity of our regression.
Assumptions
To evaluate the variables that explain the agreement to lend of Burkinabè migrants, we assume that:
The gender variable has an influence on the agreement to lend. Based on the economic role of women in African culture, we expect the gender variable to have a positive sign. The “Age” variable: the responsibilities assigned to individuals increase with age, something that places elderly people at the top of the hierarchy. Elderly people are more willing than young people to lend to municipalities because they have more responsibilities than young folks regarding the African family. The correlation between age and willingness to lend is positive. The “matsit” variable: the union between man and woman in Africa implies the union of two families and consequently a larger family for man in terms financial responsibilities. Therefore we expect married men to be less interested in lending to municipalities in their home country, which implies a negative sign of the “matsit” variable. The variable “Level of education”: the concept of socio-economic development is better understood by people with a high level of education. The more people are educated, the better they understand the importance of everyone participation in development and poverty reduction. We expect this variable to positively influence our dependent variable. The “profit” variable: migrants lend to municipalities in order to make profits, that is, to increase their earnings. In fact, this is a variable that measures personal interest. The more the migrant agrees to lend, the more he earns profits. Profit increases the willingness to lend. The variable “I love my country”: it represents the bonds of affection that exist between migrants and their country as well as the relations that exist between migrants and their families. This love for the country expresses both a sense of belonging and a sense of attachment to the country. There is therefore a positive relationship between the “I love my country” variable and the willingness to lend. The “By unity” variable: expresses the obligations of unity that comes from the community-based spirit of African culture. The migrant feels obliged to help the weakest for the well-being of the community. The relationship between this variable and the willingness to lend is positive. The variable “Helping the family”: expresses altruism, that is, the migrant’s concern for the well-being of his family. This is therefore a variable that has a positive influence on the willingness to lend. The variable “Citizen”: indicates the active contribution of the migrant in the national public life and its peaceful management. To feel as citizen of the country encourages the migrant to act for the improvement of living conditions in the country. This variable has a positive influence on the willingness to lend. The variable “Reduce Poverty”: measures the participation of migrants in reducing poverty in the country, which means enabling people to meet the basic needs of their own population. We assume that this variable has a positive influence on the willingness to lend. The variable “Express my success”: expresses the migrant’s desire to raise his profile, upon return, he shows everyone that he has taken away the shame on his family. In other words, the migrant saves the family’s honor. Therefore he makes lavish expenses in plain view of the entire community. By contributing to the loan consent, the migrant occasionally shows his success the whole country. This variable is positively related to the willingness to lend. The variable “Job creation”: unemployment is the first reason for immigration of Burkinabè. This variable measures the ability of the migrant to reduce unemployment in his country. In that way, he reduces the migration flows to neighboring countries and outside Africa in order to maintain workforce active in the country. We expect this variable to increase loans to municipalities. The “helping others” variable: expresses support to the weakest, mutual support also comes from the community spirit. This variable positively influences the willingness to lend. The variable “Blessing of God”: the belief in a supreme being is also a feature of African culture. The actions people do in their community aims at attracting God’s blessings in their lives. By seeking to attract God’s blessing, the migrant increases his willingness to lend because he is doing a good work. The variable “All that I have belongs to this country and what belongs to the country is mine” measures the community spirit that implies the responsibility to build a caring, sustainable and right response for the community (the country). The relationship between the willingness to lend and this variable is positive. The variable “economic development”: measures the participation of the migrant in the economic development of his country. That means these actions are in favor of improving the socio-economic situation of the country. This variable has a positive influence on the agreement to lend. By integrating our variables in the Equation (1) we get:
Y i ∗ = β 0 + β 1 G e n d e r + β 2 A g e + β 3 M a t s i t + β 4 E d u c + β 5 p r o f i t + β 6 L o v e + β 7 S o l + β 8 F a m + β 9 C i t + β 10 P o v + β 11 H o n + β 12 E m p + β 13 M u t s u p + β 14 b l e s s + β 15 C o m s p i + β 16 d e v + ε i (2)
Matsit represents the marital status; Educ, the level of education; Profit, the interest rate of the migrant; Love, the feeling of attachment and belonging; Sol, unity for the country; Fam, the weight of the family; Cit, citizenship; Poverty, the reduction of poverty; Hon, honor of the migrant and his family; Emp, job creation; Mutsup, support to the weakest; Bless, blessing of God; Comspi, community spirit; and Dev, economic development.
As displayed in
The descriptive results (
Characteristics | Percentage (%) |
---|---|
Gender | |
Men | 89.8 |
Women | 10.2 |
Age | |
19 - 29 | 39.1 |
30 - 39 | 43.2 |
40 - 49 | 13.6 |
50 and above | 4.1 |
Level of education | |
None | 37.8 |
Koranic | 25.1 |
Primary | 30.1 |
Secondary | 6.2 |
Higher education | 0.8 |
Number of obervations | 532 |
Source: survey from the author.
Variables | Percentage (%) |
---|---|
Love for their country | 87.7 |
Unity for their country | 51.5 |
Attraction of God’s blessing | 43.7 |
Expression of their success | 34.8 |
Everything that belongs to them belongs to Burkina Faso | 33.7 |
Support to parents | 15.5 |
Mutual support in life | 11.5 |
As Burkinabè citizen, the country needs them | 9.9 |
Participation in development | 9.8 |
Job creation | 7.2 |
Poverty reduction | 7.1 |
Profit making | 2, 8 |
Other reasons | 2.8 |
Source: survey from the authors.
The econometric results show (
Independant variables | Estimated coefficients | Probabilities | Stats de collinearity (VIF) | 1/VIF (tolerance) |
---|---|---|---|---|
Gender | −0.5346159 | 0.555 | 1.68 | 0.595238 |
Age | 0.4324816 | 0.087* | 1.16 | 0.862068 |
Matsit. | −0.5432178 | 0.043** | 0.58 | 1.724137 |
Educ. | −0.5463782 | 0.141 | 1.23 | 0.813008 |
Profit | 0.0000163 | 0.954 | 2.04 | 0.490196 |
Love | 2.5122213 | 0.000*** | 0.95 | 1.052631 |
Unity | 2.0013534 | 0.001*** | 1.05 | 0.952381 |
Fam | 1.8998756 | 0.021** | 1.13 | 0.884955 |
Citizen | 0.5467321 | 0.865 | 2.99 | 0.334448 |
Pov | 1.5467341 | 0.643 | 2.25 | 0.444444 |
Hon. | 1.7621345 | 0.019** | 1.14 | 0.877192 |
Emp. | 0.6543297 | 0.742 | 2.83 | 0.353356 |
Mutsup | 0.4983241 | 0.058* | 2.09 | 0.478468 |
Bless | 2.1983216 | 0.006*** | 0.49 | 2.040816 |
Comspi | 0.6090744 | 0.028** | 1.43 | 0.458715 |
Dev. | −0.9854372 | 0.551 | 2.18 | 0.686695 |
β0 | 0.2009321 | 0.706 | - | |
Number of observations = 532, Prob > F = 0.0134 R-squared = 0.4374 Adj R-squared = 0.4122 |
***significant at 1%;**significant at 5%; *significant at 10%.
Average | Coef. | Std.err. | t | P > |t| | [95% conf. interval] | |
---|---|---|---|---|---|---|
hat | −1.999932 | 1.045883 | −1.91 | 0.056 | −4.050104 | 0.0511757 |
hatsq | −0.8231398 | 1.048584 | −0.79 | 0.433 | −2.879545 | 1.233266 |
Cons | 1.028620 | 0.9372526 | 2.44 | 0.000 | 0.1905560 | 2.866069 |
F (2, 532)= 182.37, Prob > F = 0.0000 R-Squared = 0.3847 Adj R-Squared = 0.3826 |
Breusch-Pagan test: Homoscedasticiity, chi2 (1) = 4.57 Prob > chi2 = 0. 3392.
below the 5% threshold. It is possible to state that the explanatory variables taken together have a global effect on the dependent variable. Besides, the VIF values associated with the explanatory variables are less than 5, which mean that the regression does not suffer from multicollinearity. The homoscedasticity of the model is verified with the Breusch-Pagan test. The most P-value (Prob > chi2 = 0.3392) is greater than 0.05, so the model is homoscedastic. The Linktest test shows that our model is correctly specified because the predictor squared coefficient is 0.433 (greater than 0.05). So the coefficient is not significant.
Given the lack of documentation on the agreement to lend, we refer to studies on the intent of migrant remittances and the study by Funkhouser [
Contrary to our expectations, “the level of education and economic development” negatively influence the agreement to lend. Several reasons can explain these results. In fact, as far as the level of education is concerned, only 0.8% of migrants have a higher level of education, 6.2% have the secondary level. Even so, the higher the education level is, the less people are subjected to culture. For example, 38.5% of migrants with primary education transfer money because “all that belongs to them belongs to Burkina Faso” compared to 25.5% for migrants with secondary level and 0% for migrants with a higher level of education. Finally, the most educated migrants have less confidence in the country’s political authorities. With regard to economic development, given that the vast majority of migrants are out of school, the notion can be misunderstood by migrants. Further, migrants possibly identify economic development with political authorities that have legality but not legitimacy [
The “age” variable is positive and significant at 10% threshold. The older the Burkinabe migrant, the more he agrees to lend to the municipalities of his country. This result reinforces that of Tasiran and Horner [
The “matsit” variable is negative and significant at the 5% threshold according to our assumptions. It expresses the size of the household the migrant is responsible of. This result implies that the more the migrant has fewer expenses, the more he agrees to lend to municipalities. It reinforces Tasiran and Horner’s study [
The “Love” variable which expresses the sense of belonging and deep attachment to the country is positive and significant at 1%. Burkinabè migrants agree to lend money to municipalities because of the patriotic feeling and they contribute as a fulfillment of their duties as citizen of the country. This contribution allows them to maintain their membership rights and their identity. The “unity and mutual support” variables are positive and significant at 1% and 10% respectively. This means that the migrant agrees to lend to municipalities in order to accomplish the requirements of unity and mutual support towards the weakest, in this case the municipalities. These variables confirm Fiske’s statement [
The “support to the family” variable represents the altruism. It is positive and significant at 5%. Migrants agree to lend to municipalities in order to help their families. It highlights the pressure that the family exerts on the migrant, reinforcing Schrieder and Knerr’s conclusion [
The “God’s blessing” variable means that migrants agree to lend in order to attract God’s blessing. It is positive and significant at 1% threshold. In fact, in religions, being charitable attracts God’s blessing which helps people achieve success in all their projects, actions and achievements as they practice charity. She emphasizes the vertical relationship that the African maintains with deity. The “comspi” variable that represents the community spirit is positive and significant at 5%. Migrants agree to lend to municipalities because all that belongs to them belongs to their country. This requires that they participate in the sustainability and good organization, protection and fulfillment of each member of the community (the country). The most important thing for the African migrant is the sense of belonging to the community. This is not for profit or materialist belongings. These results indicate that culture is a powerful determinant in the intention to lend to Burkinabè municipalities. They relate to the study by Clark and Drinkwater [
This study examined the possibility of migrant remittances as a source of funding for municipalities in their home country through an agreement to lend. To do this, we determined the motivations for an agreement to lend. The results showed that migrant remittances can be used to fund municipalities through loans. Given the lack of a study on the agreement to lend, the results were compared to studies on the determinants of remittances. We relied on the Tobit model, which assumes that transfer decisions and transfers are made simultaneously. The results are in contradiction to the utilitarian theory of Cox et al. [
Ballo, Z. and Alphonsine, C.O. (2018) Migrants’ Remittances as a Source of Funding Local Development: Case of Burkinabè Migrants in Côte d’Ivoire. Theoretical Economics Letters, 8, 1412-1426. https://doi.org/10.4236/tel.2018.87091