Linear regression is a technique to quantify the relationship between the dependent variable and only one independent variable

y = β₀ +β₁x

In this equation, y is the dependent variable, is the variable on the vertical axis of the graph or the explained variable, while x, represents the variable on the horizontal axis or the independent variable. The value β₀ (which can be negative, positive or zero) is called the intercept, while the value β₁ (which can be positive or negative) is called slope or coefficient of regression or rate of change. Both, β ₁ and β₀ can be calculated from the following equations:

and

This paper is based on multiple regression analysis in which two or more variables are modeling and analyzing. The multiple regression analysis is to describe the relationship between one dependent variables called response variable and several independent variables called exogenous variables^7,8, identified that and at the same time the spreads in which some independent variables have on the dependent variable.

The multiple regression models can be much more accurate than the mono-factorial regression model. In our study, the dependent variable for the multiple regression analysis is development intervention (employment in agriculture) and the independent variables are net migration, net official aid received, economic growth, and net official development assistance and official aid received. All of the variables were used for the analysis throughout the periods from 1969-2016. Data were collected from WDI and used to obtain the regression equation and calculate the standard error, the t-statistic, the p-value and the R-squared. All these variables measure the goodness of fit or accuracy of the estimates of the model, especially the R-squared, which is called coefficient of determination in which the proportion of how much the total variance is explained by the independent variables in the model. Other tests were also used like F- statistic, t-ratios and p-values to test the hypothesis and indicate the rejection region in the model with degrees of freedom.

If y is a dependent variable and x1,…, xk are independent variables, then the multiple regression model provides a prediction or forecast of y given xi of the form

Where the assumption on the error terms are exactly as in simple linear regression. In order to estimate the coefficients and se (standard error of the estimate), one follows a process very similar to that followed in the case of only one predictor value. The left hand size variable is the dependent variable and the right hand size variable is the independent variables. The paper used the multiple regression analysis to direct predict the values of development intervention (employment in agriculture) to migration in Gambia.

Do aid/development interventions/personal remittance affect irregular migration specifically? This is linear regression between aid and net migration and between development intervention and net migration decision and between personal remittances received and net migration.

Does net migration affect total bilateral aid received in Gambia?

Does personal remittance received affect net migration?

(2)

Do personal remittances received affect economic growth?

Does net migration affect economic growth?

Does net migration impacts on development intervention, when we considered employment in agriculture as a proxy for development intervention?

Does development affect aid?

Does aid affect economic growth?

Multiple linear regression models between development intervention (proxy agriculture employment), net migration, personal remittances, bilateral aids and economic growth are given below.

Do the net migration, net official aid received, personal remittances received and economic growth affect development intervention (employment in agriculture)?

Does aid affect personal remittances received, net migration, development intervention and economic growth?

Does net migration affect personal remittances received, aids, development intervention and economic growth?

NM_it

Do personal remittances received affect net migration, aids, development intervention and economic growth?

Where:

EADI: Development Intervention (Proxy employment in agriculture)

NM: Net migration

EG: GDP growth

Taid: total aid which is Net bilateral aid flows from DAC donors, United States+ Net bilateral aid flows from DAC donors, European Union institutions+ Net official development assistance and official aid received.

PR: Personal remittance received

A brief descriptive of the data, the name of the variables, data sources and comment used in this study are presented in the Table 2 and to cleaned the data for missing data, where interpolation was used to fill the missing values, because its advantages over the other methods is that, Linear interpolation is quick and easy to use, and may be adequate for well-resolved data comparing to Polynomial interpolation, Cubin Spline Interpolation. The periods 2018-2022 was used for forecasting purpose only. This means that the aim was to know the forecasted economic growth, net migration, personal remittance, employment in agriculture and bilateral aid received in Gambia for the upcoming years.

For all the following tests, 0.05 level of significance was used. The decision rule is: If the value of the probability is higher than the 0.05 level, then we accept the null hypothesis H₀ .If the value of the probability is smaller than the 0.05 level, and then we reject the null hypothesis H₀. To test the correlation, the test of hypothesis is as follows: H₀ : X and Y are not correlated and Ha : X and Y are correlated.

In the Table 3, the linear correlation coefficient of 0.636 has a p-value of 0.0000 indicating that Development Intervention when we take employment in agriculture as a proxy and economic growth of Gambia are positively correlated. Thus, the linear correlation coefficient of 0.057 has a p-value of 0.668 meaning that economic growth and net migration are not correlated in Gambia, because the p-value = 0.668>0.05. For the linear correlation coefficient of the relationship between net migration and personal remittance received are positively correlated. Net migration increases, personal remittances received from outside rises at approximately 58% the study confirmed. Current Total aid from donors outside has positively correlated with net migration, personal remittances received, economic growth and even development intervention when we considered employment in agriculture as proxy, because their p-values are less than 0.05.

From Table 4. Below, the results found out that personal remittances received from outside has significant positive impacts on economic growth in Gambia. 10% increase in personal remittances from abroad, raises the economic growth in Gambia by approximately 0.11%.

From Table 5, in Gambia, migration has positive, but fairly small impact on economic growth. The results of the study confirmed that migration does have impacts on economic growth. If migration increases by 0%, economic growth in Gambia will reduce by 1.8%. This reflects that migration has impact on economic growth of Gambia. If no migration, Youth migration both skilled migrates and unskilled migrates send remittances back home and that remittances is used to do social function, households consumption expenditure-children school fees, health care for children, food, clothing and some used to build houses etc.

Though, foreign aids increase the economic growth in most of the poor countries if aids are the only sources of funding. If total bilateral aids received are utilized in good way, it can be an important sources of income to reduces poverty and improve economic development of Gambia.

As the results generated in Table 6 showed that the statistical analysis of migration has non-significant effect on employment in agriculture. As peoples migrates, those left behind there will be scarcity of employment in agriculture and in- turn will negatively impacts on food security and economic growth. Not only that, but those left behind are mostly women, children, elderly and disable peoples and in that their contribution to agriculture, food security and nutrition will be minimal. In the likelihoods they can be affected by poverty and hunger, malnutrition and diseases, lack of education especially children etc. That is one sided of the story. Another sides of migrates remittances also help those left behind to have quality education, good health, food security, new agriculture technology etc. In the most of the literatures that links migration and employment in agriculture found out that food security and migration can be direct, due to food insecurity and fluctuations of income.

The results from Table 7 explained that migration and economic growth have non- significant impacts on total aids in Gambia, while remittance and employment in agriculture showed are significant impacts on the total aids in Gambia. 10% increase in migration, increases total aids by 50.3%.

The study confirmed that the total aids, employment in agriculture and economic growth has significant impacts on remittance. From the existing literatures, migration and remittances have both direct and indirect effects on the welfare of the population in the migrant sending countries.

There is empirical evidence that remittances contribute to economic growth, through their positive impact on consumption, savings, and investment in macroeconomic. Remittances can also have negative impact on growth in recipient countries by reducing incentives to work, and therefore reducing labor supply. From Table 7, in Gambia remittance, migration and total aids have significant impacts on economic growth. An increase of 10% of remittance, increase economic growth by 0.14%. Only employment in agriculture has negative impacts on economic growth.10% increases in employment in agriculture, decrease economic growth by 0.04%. The economy of Gambia should deal more on export to improve agricultural development. For foreign aid can have both negatively and positively contribution to economic growth depending on the utilization of the funds.

One of the studies that looks at the impact of migration on economic growth for 22 OECD countries between 1986 and 2006 proved an optimistic, but small impact of the human capital brought by migrants on economic growth. The involvement of immigrants to human capital accumulation tends to counteract the impact of population increase on capital per worker, but the net effect is fairly small. An increase of 50% in net migration of the foreign-born makes less than one tenth of a percentage point difference in productivity growth 8.

Thus, remittances improve the likelihoods of reduction in poverty, increases education enrolment, improve investment, decreases food in-security, improve health. The results confirmed that remittances benefits both individuals, entire countries and the continents like in sub-Saharan Africa, Asia etc.

In their parts, Galiani, et al.9 confirmed that 1% percent increase in the aid to gross net income ratio increases annual real per capita GDP growth by 0.031%. A large number of studies to evaluate the impact of bilateral aid in promoting economic growth and development of recipient countries have been carried out. The results of these studies are differed, depending on the methods, country(ies) and even the time periods. For example, numerous studies ^10-13, deliver evidence that bilateral aid have optimistic impact on growth. Adam ^14,, and Carden 15find evidence for unimportant and even negative role of aid on economic growth. Several studies ^16-19 provided an evidence that positive role of aid on economic growth can be realized only when certain conditions such as good macroeconomic condition, political stability and less corruption exist.

A cross-country study of 71 developing countries found that a 10% increase in per capita, official international remittances will lead to 3.5 percent decline in the share of people living in poverty 20. Evidence from Latin America, Africa, South Asia, and other regions suggests that remittances reduce the depth and severity of poverty, as well as indirectly stimulate economic activity 21.

Migration is a choice that influences the welfare of the household, the home community, and in the end the whole economy in various ways 22. The welfare implications of migration on the origin country are most often, though not always, sizable and positive. The economic impact of migration has been intensively studied but still often driven by ill-informed insights, which, in turn, can lead to public resentment towards migration. These negative opinions risk efforts to adapt migration policies to the new economic and demographic challenges facing many countries 23. Figure 3, Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9. Table 8.