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Migration Internet and Social Networks in Africa

Richard Houessou, Afrobarometer Project Manager Francophone countries

Migration has recently risen to the top of the global agenda. According to the most recent World Migration report (IMO:2020), the number of migrants at the global level has risen more than threefold in the fifty year period between 1970 and 2020. Although precariousness and vulnerability are major factors in the decision to migrate, not every poor individual - especially the poorest workers - is forced to migrate (Adams, 1993). There are many drivers of migration, and the complexity of that phenomenon varies according to the social, cultural and economic environment, political exclusion and individual desire to migrate.


Several studies have assessed the key drivers of migration. Hatton and Williamson (2002) have observed that economic and demographic factors are the main drivers of migration. Others have looked at unemployment as a source of migration (Naude, 2010). Recent literature has reported that the inability of African countries to create economic opportunities for their citizens is a major push factor for emigration from the continent (Kainth, 2015; Stanojoska & Petreveski, 2015; Gheasi & Nijkamp, 2017). For their part, Flahaux & De Haas (2016) contend that social and political factors contribute greatly to increased emigration. Likewise, Stark and Taylor (1991) have shown that economic development that does not address the issue of income inequalities can be associated with migration. These factors would arguably contribute to the decision among the youth and more educated citizens in Africa to emigrate (Appiah-Nyamekye, Logan, and Gyimah-Boadi, 2019) However, Nayyar (2000) confirms that it is difficult to understand migration considering only economic analysis, seen from the perspective of migrating for work opportunities. Sometimes people migrate because they are forced by the laws in force in a country, or because of natural disasters, famine, etc.


This essay focuses on the role of the internet and social media technologies in migration. Several authors have studied the link between social networks and migration, focusing on the use of technological tools. These studies view new technologies as constituting stimuli to migration. McGregor and Siegel (2013), for example, have contributed to the literature on the link between social networks and migration by addressing four key points which are (1) the use of social media to trigger and facilitate migration; (2) the role of social media and the integration of migrants; (3) the use of social media in diaspora engagement; and (4) the use of social media to conduct research on migration. Dekker and Engberson (2012) advance a similar argument when they contend that new communication technologies can transform migrant networks and thus facilitate migration. In addition, Kimto (2011) found that new communication technologies strengthen internal cohesion within the same community. While encouraging a sense of belonging to communities, individuals use social networks linked to new communication techniques to exchange views. Information technology allows those who migrate to have access to information during and about their journey.


Thus, other than the standard drivers of migration, social networks related to new information and communication technologies should also be considered as one of the key factors in understanding the migration calculus. But at the same time, migration can also determine the use of social media tools to obtain information. Getting information through social networks depends on the access to mobile phone services and increased use of the internet.


This paper fills a gap in the literature on migration, in particular its link to social networks, by testing the effect of using the Internet to receive information on decisions to emigrate. Using rich national and representative surveys in several countries on the African continent and data from the World Bank, we demonstrate that social media networks are an important ingredient in the decision to migrate. Social networks are viewed in this article by not only receiving information on politics and other topics from certain channels such as Facebook, Twitter, WhatsApp and the internet. After having migrated, individuals may not continue to use this same channel to obtain information on several issues from their places of origin. This highlights the consequences of migration for social networks. This dual effect highlights the endogenous nature of using social networks to justify the decision to migrate.


With individual and aggregate data obtained in 34 African countries, this paper explores the drivers of the decision to emigrate and of net migration. Using multiple OLS regressions, we found out that exposure to the internet and social media through Facebook, WhatsApp, and Twitter strongly contributes to the decision to migration. This result remains robust when we control for economic factors such as lived poverty, receipt of remittances from abroad, unemployment and income. The results do not differ when we also control for satisfaction with the functioning of democracy. Finally, we offer evidence that there is a causality between internet exposure and migration by using a battery of instruments such as mobile phone coverage, population, and elevation.


The findings augment previous research which suggests that demographic factors such as age and educational level, as well as economic factors such as conditions of vulnerability, precariousness, and unemployment push people to emigrate. Our results further illustrate how social networks, and the use of the Internet are also an explanatory factor for migration. Specifically, we demonstrate that the use of the internet creates a convex relationship with migration. It is thus likely that the proliferation of internet users will lead to further increases in migration, which will in turn allow more people to use social networks to receive information. However, we suspect an endogeneity relationship with the use of the internet and social networks such as Facebook, WhatsApp or Twitter. This is because after migrating, people may also want to receive information from their home places, through the same technological channels.



This section provides the hypotheses that are tested in the paper. Firstly, the article investigates the relationship between exposure to internet, social network, and migration. We assume that more and more citizens are exposed to the internet and get information through social media such as Facebook, Twitter, and WhatsApp. With the explosion of the internet and social media, people have the flexibility to get information from their home about their destination. The paper then asks how this shapes the decision to emigrate. Secondly, we test the link between economic conditions and migration. Citizens that do not have better economic opportunities, like those looking for better job or having experience lived poverty may end up migrating. Thus, the lack of economic opportunities may increase the likelihood of the decision to emigrate. We also facto in thirdly, the political environment as a driver to emigration, by testing the link between a stable democratic environment and the decision to migrate. The assumption behind this is that citizens that are satisfied with the way democracy is functioning in their country are less likely to intend to emigrate. Finally, other factors may also drive the decision to migrate. There are for instance the previous travelling experiences or demographic groups. We test these against the decision to migrate and assume that citizens travelling experiences background may likely intend to migrate. In addition, the more that people age, the less they intend to migrate. We do not expect any difference between men and women regarding the decision to emigrate.


To test these hypotheses, we used two different sources of data. Data on migration intentions are drawn from the Afrobarometer, which covers 34 African countries. Afrobarometer is a nationally representative survey of adult citizens with margin of error that varies from +/-2 to +/-3 percentage at the 95% confidence level. The data used a sample of 45,823 citizens of 18 years old and above collected between 2016 and 2018. The second source of data is for the World Bank. The data from the World Bank is secondary data and capture information for each country that are considered by the Afrobarometer surveys.

Descriptive Statistics According to the Afrobarometer, nearly three of every four (73%) African Citizens have never considered moving to another country to live (Table 1). However, there are variations from one country to another as is shown in Table 2. The World Bank defines net migration as the difference between net number of migrants over a period, i.e., the total number of immigrants minus the annual number of emigrants, comprising both citizens and non-citizens. Afrobarometer findings indicate that in West and North Africa, most citizens from Benin, Burkina Faso, Côte d’Ivoire, Ghana, Guinea, Mali, Morocco, Niger, Nigeria, Senegal, and Tunisia, do not consider moving to another country to live. Most citizens from Cape Verde, Gambia, Liberia, and Togo, however, have considered moving to other countries to live. Yet, the World Bank data provides a different picture of the movement of the population in those countries. The net migration is negative, except Niger, indicating that the population of people (citizens or non-citizens) that leave those country to live abroad is more than those that come in those country to live. The situation is similar for the other countries covered by the Afrobarometer surveys between 2016 and 2017, except Botswana, Gabon, and South Africa. In those countries, Afrobarometer findings show that most citizens do not consider emigrating in other country to live according to Afrobarometer findings, while World Bank data shows that more people go to those countries to live than leave to live abroad. These findings presented in the table 2 are very crucial to figure out the direction of the movement of the population in those countries that are considered for the paper.

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Now the paper defines an arithmetic variable that factors in the frequency of getting information from internet and social media such as Facebook, WhatsApp, etc. Basically, 62% of respondents never get news from the internet or social media, while 38% of African citizens that were interviewed said that at least less than once a month, they received news from both internet and social media (Table 3). The findings suggest strong correlation between social network and the decision to migrate. The citizens that have no social network access are less likely to consider moving to another country to live (Table 4).

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In addition to access to social media networks, the descriptive findings further suggest a link between experience of poverty and contemplation to migrate. Bratton et al, 2006 defined lived poverty as a composite variable that captures the experience of poverty along five dimensions, namely: going without enough food to eat; clean water for home use, medicines or medical treatment, fuel to cook food and cash income. When correlated against considerations to migrate, the data suggests that African citizens that have never experienced lived poverty are less likely to consider moving to another country to live (Table 5).

The findings from Tables 4 and 5 enable us to say that considering to move to another country to live may strongly depend on the poverty status and news that are received from internet and social media.


As economic factor may be one of the key drivers to the decision to migrate, the paper then maps out the countries included in this study, regarding the level of their income and the net migration. It appears that countries with low or middle low income are typically countries where emigration is higher than immigration. Among the countries that are considered as middle and upper income, Namibia is the only one for which emigration is higher than immigration.

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To test the hypotheses, we use Ordinary Least Square -OLS- and run regressions with the following equation



The second model that is also OLS reflected through the following equation


Firstly, the first three columns (1) - (3) of Table 6 point out the findings regarding the decision to emigrate on connectivity to social networks, lived poverty, the fact of receiving remittances from the outside and employability status. The results indicate that African citizens who receive news information from the internet and social networks are more likely to decide to migrate to another country in order to live. Likewise, the more citizens experience a greater lack of basic necessities, the more likely they are to contemplate emigrating. The findings further suggest that receipt of remittances from abroad increase the likelihood to consider emigrate. This suggests that there is a social network created around the relatives who sent the remittances and therefore affect the decision to migrate. In addition, unemployment status has not changed the decision to migrate. Whether or not people have a job, those with networks abroad still consider moving to another country to live. Hatton and Williamson (2002) have shown that the expectation of getting better working conditions leads those who are looking for work or have a situation of employability to emigrate. Finally, the findings also indicate that those who are satisfied with how democracy works do not decide to migrate abroad to live. When controlling with those that have experience of travelling, age, sex, place of residence and level of education, the findings are still consistent.


Secondly, regressions in Table 6 explain the net migration by the use of internet, unemployment, active population, mobile phone subscription, country income classification. The findings suggest increased internet use or mobile phone subscribers are associated with the likelihood of emigrating. The positive correlation means those that use internet or subscribe to mobile phone are more likely to consider moving from their country to another in order to live. Moreover, there is a convex relationship between internet use and net migration. The findings are the same for the active population and unemployment.


By controlling with income, the results indicate the positive correlation with net migration. In the country with low middle income and upper middle income, emigration is more observed than lowincome country. In addition to this, likelihood of emigration is more observed in East and Central Africa compared to West Africa. To the contrary, in Southern and North Africa, immigration is more noted than in West Africa. People prefer moving to South and North Africa compared to West Africa. Southern and East Africans tend to migrate within the continent, while migration from West and North Africa is usually transcontinental, mostly to Europe and the United States. Migrating within the continent is relatively easier and therefore a more likely option for many compared to transcontinental migration.

Instrumental variables

This paper has investigated the drivers of the decision to move to another country to live and the net migration. The main determinants are the social network and the internet use. The social network in this paper is defined by the arithmetic mean of the getting news from internet and social media such as WhatsApp, Facebook, Twitter. The assumptions are that internet use and social network can also be explained by mobile phone coverage, the elevation and the density of active population. Those variables are instruments to the internet use and social network.


This section seeks to underline the causality that may exist between consideration to move to other country and the social network. Likewise, the causal relationship that may occur between the net migration and the internet use. Thus, the following model is describing as such:

The findings are still consistent with previous results. They suggest that the internet use and social network explain the prospects for migrating and net migration through mobile phone coverage, place of residency, elevation, and density of the active population. This mechanism is quite straightforward. In fact, mobile phone coverage allows many people to get connected and create their own social network by getting and exchanging information through internet and social media. That information is essential in their decision to migrate, and it permits them to communicate with their relatives that are abroad. It may enable them also to seek information about their potential destination. On the other hand, the same process will allow them once they arrive to their destination to communicate with their relatives to give or get information. Elevation shapes mobile phone coverage. This means depending on their location, users will have fully access to internet and then can communicate with their relatives for information. Likewise, mobile phone coverage, elevation and active population also explain the use of internet that drives the net migration. People that are more exposed to the internet are more likely to emigrate because it allows them to get needed information for their trip.


Conclusion and Discussions

This paper has brought a contribution to the literature by identifying causality between migration and the use of internet and social media. Typically, the paper allows to claim that the rural areas or remote places where there is weak internet coverage because of weak mobile coverage, citizens are less likely to emigrate because they cannot get news from internet and social media. The use of internet and social media have become widely relevant for the emigrants, and it brought the idea that incumbents have also to play a role to provide the necessities that allow Africans to decide whether to migrate or stay. The findings also have suggested that poverty lived is associated with the decision to migrate. Typically, those that with high poverty lived are certainly looking for better outcomes. In fact, economics opportunities are the most important reasons for emigrating. There is a need for incumbents to put in place what can prevent for huge traffic of migration. Among them, better jobs, better democratic environment, better social protection. It is evidence that despite better conditions, there are citizens that may decide to emigrate because they have other perspectives. The paper has also brought the density of the population as one of the key drivers of migration. Although some have jobs, active population seems to be a time bomb as inequal equation for the incumbents. African states need to look for better industrialization as a solution to maintain validated arms on the ground.

This paper also points out the link between migration and exposure to the internet and social networks on the one hand and economic and political factors on the other. Individual data informs the decision to emigrate, while aggregate data on net migration. The findings suggest that that there is a positive correlation between internet and social media exposure and the decision to emigrate. By considering aggregate data, the results indicate that the more internet is used, the more will African citizens consider the option of migrating. The paper proves the causal effect of internet exposure on the decision to emigrate or net migration using a combination of variables such as mobile phone coverage, active population and elevation. The results suggest that internet exposure explains migration through those instruments.



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